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1
Blazhynska, Marharyta. "Modeling and Standard Binding Free Energy Calculations of Complex Biological Objects." Electronic Thesis or Diss., Université de Lorraine, 2023. http://www.theses.fr/2023LORR0149.
Abstract:
Pendant ma thèse, j'ai consacré mes recherches à l'analyse des calculs d'énergie libre de liaison absolue dans des complexes protéine-ligand. J'ai utilisé des approches basées sur la dynamique moléculaire, intégrant des restreintes telles que les itinéraires alchimiques et géométriques. Mon travail comprenait l'étude de trois complexes protéine-ligand distincts, contribuant ainsi à l'évaluation du logiciel BFEE2 pour l'automatisation de ces calculs. En poursuivant mes investigations, j'ai appliqué cette méthodologie aux interactions protéine-protéine, qui impliquent des phénomènes de reconnaissance et d'association plus complexes. J'ai examiné un exemple spécifique : un dimère d'insuline porcine dans lequel la dimérisation était induite par des interactions hydrophobes à l'interface des monomères. Ensuite, j'ai comparé les résultats des estimations d'énergie libre obtenus par calcul avec les données expérimentales correspondantes. Pour approfondir ma compréhension des calculs d'énergie libre de liaison dans les complexes protéine-ligand et protéine-protéine, j'ai réalisé une recherche méthodologique. J'ai évalué la robustesse de la méthode géométrique par rapport à une version simplifiée, où les degrés de liberté supplémentaires étaient maintenus non restreints lors de la séparation physique des partenaires. Après avoir démontré l'exactitude de la méthode géométrique, j'ai élargi son application à la prédiction et à l'évaluation des affinités de liaison des variants du SARS-CoV-2 en interaction avec un récepteur humain et des anticorps. De plus, j'ai exploré des stratégies visant à accélérer les calculs en utilisant l'option MTS disponible dans le module Colvars, avec ou sans l'astuce d'HMR. En ajustant les paramètres de Colvars, j'ai réussi à obtenir une accélération des calculs presque triplée, sans compromettre la précision des calculs d'énergie libre de liaisonDuring my thesis, I focused my research on analyzing the calculations of absolute binding free energy in protein-ligand complexes. I utilized approaches based on molecular dynamics, incorporating restraints such as alchemical and geometrical routes. My work involved studying three distinct protein-ligand complexes, contributing to the evaluation of the BFEE2 software for automating these calculations. Continuing my investigations, I applied this methodology to protein-protein interactions, which involve more complex recognition and association phenomena. I examined a specific example: a dimer of porcine insulin, where dimerization was induced by hydrophobic interactions at the interface of the monomers. Subsequently, I compared the results of calculated estimates of binding free energy with the corresponding experimental data. To deepen my understanding of binding free energy calculations in protein-ligand and protein-protein complexes, I conducted methodological research. I evaluated the robustness of the geometrical route compared to a simplified version, where additional degrees of freedom remained unrestrained during the physical separation of the partners. After demonstrating the accuracy of the geometrical route, I expanded its application to predict and evaluate the binding affinities of SARS-CoV-2 variants in interaction with a human receptor and antibodies. Additionally, I explored strategies to accelerate the calculations using the MTS option available in the Colvars module, with or without the HMR trick. By adjusting the parameters of Colvars, I achieved an almost threefold acceleration of the calculations without compromising the accuracy of the binding free energy calculations
2
Ranganathan, Anirudh. "Protein – Ligand Binding: Estimation of Binding Free Energies." Thesis, KTH, Skolan för kemivetenskap (CHE), 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-147527.
Abstract:
Accurate prediction of binding free energies of protein-ligand system has long been a focus area for theoretical and computational studies; with important implications in fields like pharmaceuticals, enzyme-redesign, etc. The aim of this project was to develop such a predictive model for calculating binding free energies of protein-ligand systems based on the LIE-SASA methods. Many models have been successfully fit to experimental data, but a general predictive model, not reliant on experimental values, would make LIE-SASA a more powerful and widely applicable method. The model was developed such that There is no significant increase in computational time No increase in complexity of system setup No increase in the number of empirical parameters. The method was tested on a small number of protein-ligand systems, selected with certain constraints. This was our training set, from which we obtain the complete expression for binding free energy. Expectedly, there was good agreement with experimental values for the training set On applying our model to a similar sized validation set, with the same selection constraints as for the training set, we achieved even better agreement with experimental results, with lower standard errors. Finally, the model was tested by applying it to a set of systems without such selection constraints, and again found good agreement with experimental values. In terms of accuracy, the model was comparable to a system specific empirical fit that was performed on this set. These encouraging results could be an indicator of generality.
3
Rocklin, Gabriel Jacob. "Predicting charged protein-ligand binding affinities using free energy calculations." Thesis, University of California, San Francisco, 2013. http://pqdtopen.proquest.com/#viewpdf?dispub=3587895.
Abstract:
Predicting protein-ligand binding free energy from physical principles is a grand challenge in biophysics, with particular importance for drug discovery. Free energy calculations compute binding affinities by using classical mechanics to model the protein and ligand at atomic resolution, and using statistical mechanics to analyze simulations of these models. The binding affinities computed from these simulations are fully rigorous and thermodynamically correct for the model (with adequate sampling), and will agree with experimentally measured binding affinities if the model is accurate. Because free energy calculations capture the full statistical complexity of binding for flexible molecules at ambient temperature, they offer the greatest potential for quantitative accuracy of any physical method for predicting binding.
Here, I (& coauthors) present several studies relating to using free energy calculations to predict protein-ligand binding affinities for charged compounds. First, we introduce the Separated Topologies method, an approach for using free energy calculations to predict relative binding affinities of unrelated ligands. This method is useful for studying charged compounds because charged compounds are very difficult to study using absolute binding calculations, increasing the importance of relative binding calculations. Second, we use free energy calculations to predict absolute binding affinities for charged molecules to a simplified protein binding site, which is specially designed for studying charged interactions. These predictions are compared to new experimental affinity measurements and new high-resolution structures of the protein-ligand complexes. We find that all affinities are predicted to be too strong, and that this error is directly correlated with the polarity of each ligand. By uniformly weakening the strength of electrostatic interactions, we are more successful at predicting binding affinity. Third, we design and validate an analytical correction scheme to correct binding free energy calculations of ions for artifacts caused by the periodic boundary conditions employed in simulations. Fourth, we examine the sensitivity of binding affinities from free energy calculations to the force field parameters used in the simulations. This provides insight into the strength of electrostatic interactions in protein simulations, complementing our previous work comparing simulation results to experiments. Finally, we discuss potential future directions of this work.
4
Cabedo, Martinez Ana. "Computing free energy, binding and competition within Fragment Based Drug Discovery." Thesis, University of Southampton, 2016. https://eprints.soton.ac.uk/403850/.
Abstract:
The development of JAFS, a new computational method to study the binding geometries of small fragment molecules to protein cavities, estimate their binding affnities and analyse how they compete for a common protein binding site, all in the context of Fragment Based Drug Discovery, is presented in this thesis. Fragment Based Drug Discovery is an approach to drug development which studies the binding of small ligands (fragments) forming high quality interactions with their target. Further optimization of these fragments into drug-like molecules, adding functionalities to increase affnity while controlling other relevant properties such as toxicity and absorption then takes place. JAFS studies the binding of fragments to their target proteins. The JAFS method consists of the execution and analysis of Monte Carlo simu-lations of fragments (and waters) in the binding cavities of proteins with an added degree of freedom which accounts for the scaling of the interaction energy of the fragment (and water). Sampling of states at very low interaction energies gives a boost in fragment con?gurational sampling while competition between di?erent fragments to remain at unscaled (high) interaction energies at a given binding site provides information on their relative binding a?nities. JAFS is built on the JAWS formulation for water binding to protein cavities. The performance of the JAFS method on a range of different test cases (T4 Lyzozyme, Major Urinary Protein I, Cyclin Dependent Kinase 2 and Heat Shock Protein 90) was studied. JAFS is divided in two protocols to rank fragments by affnity and locate binding geometries, respectively. The ranking of fragments by affnity to a common protein target was satisfactory (as compared to experimen-tal data) for the simpler systems (T4 Lyzozyme and Major Urinary Protein I). However, more demanding systems proved problematic, where the ranking of nine different ligands to the binding site of Cyclin Dependent Kinase 2 provided results unrelated to experimental binding affnities. Studying pose generation in sets of five repeats per simulation, the crystal binding geometry of every fragment studied was found in at least one of the re-peats, without providing any previous information on the system (such as the presence or location of water mediated interactions or the hydration state of the cavity). Consistency between repeats was however found to be problematic and no method is currently able to select the optimal binding geometry among all the gen-erated poses. Suggestions are given for further developments which would provide a methodology to rank poses.
5
Lee, Lee-Peng 1969. "Optimization of electrostatic binding free energy : application to barnase and barstar." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/85331.
6
Wall, Ian. "New simulation methods for the prediction of binding free energies." Thesis, University of Southampton, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.313217.
7
Durmaz, Vedat [Verfasser]. "Atomistic Binding Free Energy Estimations for Biological Host–Guest Systems / Vedat Durmaz." Berlin : Freie Universität Berlin, 2016. http://d-nb.info/1122111215/34.
8
He, Peng. "FREE ENERGY SIMULATIONS AND STRUCTURAL STUDIES OF PROTEIN-LIGAND BINDING AND ALLOSTERY." Diss., Temple University Libraries, 2018. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/531465.
Abstract:
ChemistryPh.D.
Protein-ligand binding and protein allostery play a crucial role in cell signaling, cell regulation, and modern drug discovery. In recent years, experimental studies of protein structures including crystallography, NMR, and Cryo-EM are widely used to investigate the functional and inhibitory properties of a protein. On the one hand, structural classification and feature identification of the structures of protein kinases, HIV proteins, and other extensively studied proteins would have an increasingly important role in depicting the general figures of the conformational landscape of those proteins. On the other hand, free energy calculations which include the conformational and binding free energy calculation, which provides the thermodynamics basis of protein allostery and inhibitor binding, have proven its ability to guide new inhibitor discovery and protein functional studies. In this dissertation, I have used multiple different analysis and free energy methods to understand the significance of the conformational and binding free energy landscapes of protein kinases and other disease-related proteins and developed a novel alchemical-based free energy method, restrain free energy release (R-FEP-R) to overcome the difficulties in choosing appropriate collective variables and pathways in conformational free energy methods like umbrella sampling and metadynamics.
Temple University--Theses
9
Bertazzo, Martina <1990>. "Dynamic Docking, Path Analysis and Free Energy Computation in Protein-Ligand Binding." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amsdottorato.unibo.it/9290/1/TESI.pdf.
Abstract:
Comprehending how drugs interact with biological macromolecules to form a complex with consequent biological response is particularly relevant in drug design to guide a rational design of new active compounds. The establishment and the duration of the protein-ligand binding complex is principally determined by thermodynamics and kinetics of the dynamical process of molecular recognition. Thus, an accurate characterization of the free-energy governing the formation of the protein-ligand complex is of fundamental importance to deeply understand each contribution to the establishment of the molecular complex.
Experimental biophysical techniques proved to be efficient in characterizing both thermodynamics and kinetics of protein-ligand binding. However, a detailed description of the whole binding process on a mechanistic level is not possible since only a quantitative estimation is allowed.
Conversely, from the computational point of view, plain molecular dynamics, which has been increasingly considered as the method of choice to investigate the entire dynamic process upon complex formation and to predict the associated thermodynamic and kinetic observables, cannot be applied in a routinely drug discovery pipeline because of the high computational cost.
In this context, this PhD thesis wants to address specific aspects of the protein-ligand binding process. In particular, it will deal with dynamic docking, thermodynamics and kinetics of protein-ligand binding by devising respectively three different computational protocols.
We developed a dynamic docking protocol based on potential-scaled (sMD) simulations, in which the protein and the ligand are let completely flexible in order to predict the protein-ligand binding pose within a reasonable computational time. Then, we investigated the applicability of sMD in describing the kinetic behavior of a series of drug-like molecules and we devised a fully automated method to analyze the unbinding trajectories. Finally, we develop a semi-automated protocol based on path collective variables combined with well-tempered metadynamics to estimate free-energies along a binding path.
10
Alsayed, Adnan. "A government and binding approach to restrictive relatives, with particular reference to restrictive relatives in standard Arabic." Thesis, University of Essex, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.243350.
11
Green, David Francis 1975. "Optimization of electrostatic binding free energy : applications to the analysis and design of ligand binding in protein complexes." Thesis, Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/16888.
Abstract:
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemistry, 2002.Vita.
Includes bibliographical references (p. 279-298).
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Electrostatic interactions play an important role in determining the energetics of association in biomolecular complexes. Previous work has shown that, within a continuum electrostatic model, for any given complex there exists a ligand charge distribution which optimizes the electrostatic binding free energy - the electrostatic complement of the target receptor. This electrostatic affinity optimization procedure was applied to several systems both in order to understand the role of electrostatic interactions in natural systems and as a tool in the design of ligands with improved affinity. Comparison of the natural and optimal charges of several ligands of glutaminyl-tRNA synthetase from E. coli, an enzyme with a strong natural requirement for specificity, shows remarkable similarity in many areas, suggesting that the optimization of electrostatic interactions played a role in the evolution of this system. The optimization procedure was also applied to the design of improvements to two inhibitors of HIV-1 viral-cell membrane fusion. Two tryptophan residues that are part of a D-peptide inhibitor were identified as contributing most significantly to binding, and a novel computational screening procedure based on the optimization methodology was developed to screen a library of tryptophan derivatives at both positions. Additionally, the optimization methodology was used to predict four mutations to standard amino acids at three positions on 5-Helix, a protein inhibitor of membrane fusion. All mutations were computed to improve the affinity of the inhibitor, with a five hundred-fold improvement calculated for one triple mutant.
(cont.) In the complex of b-lactamase inhibitor protein with TEM1 b-lactamase, a novel type of electrostatic interaction was identified, with surface exposed charged groups on the periphery of the binding interface projecting significant energetic effects through as much as 10 A of solvent. Finally, a large number of ab initio methods for determining partial atomic charges on small molecules were evaluated in terms of their ability to reproduce experimental values in continuum electrostatic calculations, with several preferred methods identified.
by David Francis Green.
Ph.D.
12
Keränen, Henrik. "Advances in Ligand Binding Predictions using Molecular Dynamics Simulations." Doctoral thesis, Uppsala universitet, Beräknings- och systembiologi, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-230777.
Abstract:
Biochemical processes all involve associations and dissociations of chemical entities. Understanding these is of substantial importance for many modern pharmaceutical applications. In this thesis, longstanding problems with regard to ligand binding are treated with computational methods, applied to proteins of key pharmaceutical importance. Homology modeling, docking, molecular dynamics simulations and free-energy calculations are used here for quantitative characterization of ligand binding to proteins. By combining computational tools, valuable contributions have been made for pharmaceutically relevant areas: a neglected tropical disease, an ion channel anti-drug-target, and GPCR drug-targets. We report three compounds inhibiting cruzain, the main cysteine protease of the protozoa causing Chagas’ disease. The compounds were found through an extensive virtual screening study and validated with experimental enzymatic assays. The compounds inhibit the enzyme in the μM-range and are therefore valuable in further lead optimization studies. A high-resolution crystal structure of the BRICHOS domain is reported, together with molecular dynamics simulations and hydrogen-deuterium exchange mass spectrometry studies. This work revealed a plausible mechanism for how the chaperone activity of the domain may operate. Rationalization of structure-activity relationships for a set of analogous blockers of the hERG potassium channel is given. A homology model of the ion channel was used for docking compounds and molecular dynamics simulations together with the linear interaction energy method employed for calculating the binding free-energies. The three-dimensional coordinates of two GPCRs, 5HT1B and 5HT2B, were derived from homology modeling and evaluated in the GPCR Dock 2013 assessment. Our models were in good correlation with the experimental structures and all of them placed among the top quarter of all models assessed. Finally, a computational method, based on molecular dynamics free-energy calculations, for performing alanine scanning was validated with the A2A adenosine receptor bound to either agonist or antagonist. The calculated binding free-energies were found to be in good agreement with experimental data and the method was subsequently extended to non-alanine mutations. With extensive experimental mutation data, this scheme is a valuable tool for quantitative understanding of ligand binding and can ultimately be used for structure-based drug design.
13
Nervall, Martin. "Binding Free Energy Calculations on Ligand-Receptor Complexes Applied to Malarial Protease Inhibitors." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-8338.
14
Mohamed, Noor Asidah Binti. "The evaluation of protein-ligand binding free energies using advanced potential energy function." Thesis, University of Southampton, 2018. https://eprints.soton.ac.uk/428049/.
Abstract:
Electronic polarisation is one of the components that plays an important role in many biomolecular systems. The effects of polarisation will act differently depending on the local environment of the system, such as in DNA, proteins and membranes. Traditionally, molecular mechanical force fields describe electrostatics as the interactions of fixed, atom-centred, point charges. Hence the past decade has seen many additions and improvements to existing force fields to better correlate dynamics with experimental observations. A better description of electrostatics by the inclusion of electronic polarisation is one such improvement. The AMOEBA polarisable force field is one of many possible models that is designed to be capable of capturing this effect. AMOEBA includes mutually polarising induced atomic dipoles at every atomic site, as well as a multipolar representation of fixed electrostatics. To investigate applications of AMOEBA and where its successes over existing fixed-charge methods may lie, we first evaluate features and performance of the AMOEBA polarisable force field in simple systems based on the evaluation of solvation free energies for small molecules in a range of common organic solvents. Here, we pointed out several challenges and limitations of AMOEBA in this study involving non-aqueous solvents. Then, we further our investigation on more complex systems including protein-ligand interactions. Initially, clear cases of failure in fixed-point-charge force fields were identified by exploring the sensitivity of the calculated free energies to parameter sets and simulation protocols of protein-ligand systems, focusing on binding free energy calculations of the cytochrome c peroxidase protein using the AMBER force field. Finally, we use these results to inform binding free energy calculations for testing of the AMOEBA force field. We discuss the implications of these results for better understanding and improving AMOEBA to aid its full implementation in other biological applications.
15
Gobbo, Dorothea <1989>. "Free energy and kinetics in protein-ligand binding: experimental measurements and computational estimates." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amsdottorato.unibo.it/8982/1/Gobbo_Dorothea_tesi.pdf.
Abstract:
Virtually all biochemical activities are mediated by the organization and recognition of biological macromolecules. An accurate characterization of the thermodynamics and kinetics governing the formation of supramolecular complexes is required to deeply understand the molecular principles driving all biological interactions. Thermodynamics provides the driving force of protein-ligand binding and is quantified by the binding free energies or the equilibrium dissociation constants. Since the interacting partners are out of equilibrium in vivo, the thermodynamic description of binding needs to be complemented by the knowledge of the kinetic rates. Nowadays, various biophysical experimental techniques can determine thermodynamic and kinetic properties, which are still difficult to be efficiently predicted by computational methods mainly because of the limited force field accuracy and the high computational cost.
During my Ph.D., I applied molecular dynamics (MD)-based methods to characterize the thermodynamics and kinetics of inter-molecular interactions. First, I worked on a new enhanced MD-based protocol to simulate protein-ligand dissociation events. This approach provides a realistic description of the evolution of the system to an external perturbation accounting for the natural forces driving the dissociation mechanisms. By applying this computational approach to two pharmaceutically relevant kinases, I was able to rank two series of compounds on unbinding kinetics and to get qualitative mechanistic and path information on the underlying unbinding events, providing additional valuable information to be used in the optimization of lead compounds. Then, I developed an innovative computational method to estimate free energies applicable to systems of arbitrary complexity. Despite the number of challenges to be overcome, the method is very promising being able to provide accurate free energy estimates. Therefore, computer simulations emerged as a valuable tool to obtain information on both the thermodynamic and kinetic aspects governing the formation of supramolecular complexes, which might be used in the rational optimization of lead compounds.
16
Nandigrami, Prithviraj. "Cooperative allosteric ligand binding in calmodulin." Kent State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=kent1507302866723977.
17
Carlsson, Jens. "Challenges in Computational Biochemistry: Solvation and Ligand Binding." Doctoral thesis, Uppsala University, Department of Cell and Molecular Biology, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-8738.
Abstract:
Accurate calculations of free energies for molecular association and solvation are important for the understanding of biochemical processes, and are useful in many pharmaceutical applications. In this thesis, molecular dynamics (MD) simulations are used to calculate thermodynamic properties for solvation and ligand binding.
The thermodynamic integration technique is used to calculate pKa values for three aspartic acid residues in two different proteins. MD simulations are carried out in explicit and Generalized-Born continuum solvent. The calculated pKa values are in qualitative agreement with experiment in both cases. A combination of MD simulations and a continuum electrostatics method is applied to examine pKa shifts in wild-type and mutant epoxide hydrolase. The calculated pKa values support a model that can explain some of the pH dependent properties of this enzyme.
Development of the linear interaction energy (LIE) method for calculating solvation and binding free energies is presented. A new model for estimating the electrostatic term in the LIE method is derived and is shown to reproduce experimental free energies of hydration. An LIE method based on a continuum solvent representation is also developed and it is shown to reproduce binding free energies for inhibitors of a malaria enzyme. The possibility of using a combination of docking, MD and the LIE method to predict binding affinities for large datasets of ligands is also investigated. Good agreement with experiment is found for a set of non-nucleoside inhibitors of HIV-1 reverse transcriptase.
Approaches for decomposing solvation and binding free energies into enthalpic and entropic components are also examined. Methods for calculating the translational and rotational binding entropies for a ligand are presented. The possibility to calculate ion hydration free energies and entropies for alkali metal ions by using rigorous free energy techniques is also investigated and the results agree well with experimental data.
18
Sund, Johan. "From Structure to Function with Binding Free Energy Calculations for Codon Reading, Riboswitches and Lectins." Doctoral thesis, Uppsala universitet, Beräknings- och systembiologi, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-207140.
Abstract:
Molecular association is part of many important processes in living cells. Computational methods for calculating binding free energies allows for a quantitative examination of biomolecular structures and hypotheses drawn from biochemical experiments. Here, binding free energy calculations for tRNAs and release factors binding to mRNA codons on the ribosome, sugars binding to lectins and purine analogs binding to the purine riboswitch are presented. The relative affinities between cognate and non-cognate tRNAs for different states involved in codon reading on the ribosome were determined. The calculations show that tRNA discrimination varies between different conformations of the 30S subunit, where the existence of both low and high selectivity states provides an efficient common mechanism for initial selection and proofreading. The simulations reveal a desolvation mechanism for the 30S conformational switch with which the accuracy of peptide bond formation can be amplified. When an mRNA stop codon (UAA, UAG or UGA) is located in the ribosomal A-site release factors bind to the ribosome and the synthesized protein is released. RF1 is specific for UAA and UAG whereas RF2 is specific for UAA and UGA. The free energy calculations and an analysis of the performed simulations show the mechanisms for how RF1 and RF2 are able to read the stop codons with different specificities. Also mitochondrial release factors were investigated. Vertebrate mitochondria have four stop codons, UAA, UAG, AGA and AGG and two release factors mtRF1 and mtRF1a. The calculations show how the specificities of both mtRF1 and mtRF1a agree with RF1 and that none of them are likely to read the non-standard stop codons AGA and AGG. The linear interaction energy method has also been examined for the RSL and PA-IIL lectins and for the purine riboswitch. The standard parameterization of the method works well for RSL, but fails for PA-IIL and the purine riboswitch due to compositions of the active sites in these systems. The development of new parameterizations to overcome these problems leads to a better understanding of both the method and the binding mechanisms in these systems.
19
Abdul, Rahim Nur Aida. "Investigating the mechanotransduction by two-photon fluorescence microscopy measurement of intracellular free energy of binding." Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/44746.
Abstract:
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2008.Includes bibliographical references (p. 99-108).
Force, due either to haemodynamic shear stress or relayed directly to the cell through adhesion complexes, is transmitted and translated into biological signals. This process is known as mechanotransduction. Extensive studies have been carried out on the signaling pathways involved in mechanotransduction. However, the mechanism(s) of mechanotransduction has yet to be fully understood. This thesis focuses on the measurement of the intracellular binding constant between focal adhesion proteins of interest, GFP-Paxillin and FAT-mCherry, using two-photon excitation fluorescence microscopy and the utility of it as a measure of protein conformational change. The hypothesis tested is that force-induced changes in protein conformation alter inter-protein binding affinity. A comprehensive toolkit that utilizes fluorescence microscopy techniques, Forster Resonance Energy Transfer (FRET) and its corollary, Fluorescence Lifetime Imaging (FLIM), as well as Fluorescence Correlation Spectroscopy (FCS), was developed. A procedure by which low photon counts cell data from FLIM could be included in global analysis fits and be corrected for was developed. This results in the recovery of maximum information from cellular data. Successful intracellular FCS measurements were combined with FLIM global analysis data to calculate the free energy of binding between GFP-Paxillin and FAT-mCherry. Results demonstrate that inter-cell heterogeneity exists and likely gives rise to differences in measured AIG. The application of these measurement techniques to cells experiencing 10% step strain shows that inter-protein binding is tighter upon stretch application. The source of this change is not clear, though Tyr phosphorylation has been ruled out by biochemical disruption of kinase activity.
by Nur Aida Abdul Rahim.
Ph.D.
20
Chen, Zhihong. "Modeling Ion Binding in the Chloride Transporter." University of Cincinnati / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1439310689.
21
Miao, Yi. "Shape-Dependent Molecular Recognition of Specific Sequences of DNA by Heterocyclic Cations." Digital Archive @ GSU, 2006. http://digitalarchive.gsu.edu/chemistry_diss/4.
Abstract:
SHAPE-DEPENDENT MOLECULAR RECOGNITION OF SPECIFIC SEQUENCES OF DNA BY HETEROCYCLIC CATIONS by YI MIAO Under the Direction of Dr. W. David Wilson ABSTRACT DB921 and DB911 are biphenyl-benzimidazole-diamidine isomers with a central para- and meta-substituted phenyl group, respectively. Unexpectedly, linear DB921 has much stronger binding affinity with DNA than its curved isomer, DB911. This is quite surprising and intriguing since DB911 has the classical curved shape generally required for strong minor groove binding while DB921 clearly does not match the groove shape. Several biophysical techniques including thermal melting (Tm), circular dichroism (CD), biosensor-surface plasmon resonance (SPR), and isothermal titration calorimetry (ITC) have been utilized to investigate the interactions between these compounds and DNA. The structure of the DB921-DNA complex reveals that DB921 binds to DNA with a reduced twist of the biphenyl for better fit of DB921 into the minor groove. A bound water molecule complements the curvature of DB921 and contributes for tight binding by forming H-bonds with both DNA and DB921. Structure-affinity relationship studies of a series of DB921 analogs show that the benzimidazole group is one of the key groups of DB921 for its strong binding to the minor groove. Thermodynamic studies show that the stronger binding of DB921 is due to a more favorable binding enthalpy compared to DB911 even though the complex formation with DNA for these compounds are all predominantly entropically driven. DB921 also has more negative heat capacity change than DB911. The initial studies of inhibition of the interaction between an AT hook peptide of HMGA proteins and its target DNA by a set of diamidine AT-minor groove binders using biosensor-SPR technique show that the inhibitory ranking order is consistent with that of binding affinity and linear-shaped DB921 still has excellent inhibitory effects. These heterocyclic cations rapidly inhibit the binding of DBD2 peptide to the DNA and may only block the specific AT binding of the peptide without hindering the non-specific binding interaction. The results of this project have shown that DB921 represents a new novel effective minor groove binder that does not fit the traditional model and is a potential inhibitor for DNA/protein complexes. INDEX WORDS: Molecular recognition, DNA binding, Minor groove binding, Linear shape, Compound curvature, Binding affinity, Binding kinetics, Thermodynamics, Surface plasmon resonance, Isothermal titration calorimetry, Inhibition
22
Gregor, Craig Robert. "Epitopes, aggregation and membrane binding : investigating the protein structure-function relationship." Thesis, University of Edinburgh, 2012. http://hdl.handle.net/1842/5833.
Abstract:
The three-dimensional structure of a protein, formed as a result of amino-acid sequences folding into compact domains, is regarded as a key factor in its biological function. How and why proteins fold into specific topologies, remain the key focus of scientific research in the field of biophysics. By stripping down complex reactions down to the most basic elements, biophysicists aim to develop simplified models for biological phenomena such as antibody discrimination, viral fusion or self-assembly. Focusing on small model peptide systems, rather than the full proteins from which they were derived, was hoped to result in accurate structural measurements and provide a more transparent comparison between simulation and experiment. The aim of this research was therefore to investigate how accurate these models were when compared against experiment. Furthermore, while breaking down the complex biological phenomena into simple models, there was also a conscious effort to ensure that the models were representative of real biological systems, and a major focus was therefore aimed at determining whether any meaningful biomedical insight may be extrapolated from such models. Peptides found in hormones (human chorionic gonadotropin, luteinizing hormone), viruses (HIV) and amyloid diseases (transthyretin) were selected in order to probe a variety of questions in relation to the aforementioned biological phenomena. Namely, how the primary sequence influenced the three-dimensional structure (and thus its biological function), how its environment could influence such a confirmation, and how these systems aggregated. This doctoral study has made use of a combination of computer simulations and experimental techniques to investigate a selection of biologically relevant peptides; utilising classical atomistic molecular dynamics (MD) simulations to characterise the free-energy landscapes of the chosen peptides, and compare these findings with the secondary structure content predicted by spectroscopic methods such as circular dichroism and infrared spectroscopy. The peptide systems studied within, were found to be characterised by rugged free-energy landscapes unlike their protein counterparts (defined by singular, deep minima). Furthermore, these landscapes were found to be highly plastic and sensitive to changes in the local environment.
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Gilabert, Navarro Joan Francesc. "Estimation of binding free energies with Monte Carlo atomistic simulations and enhanced sampling." Doctoral thesis, Universitat Politècnica de Catalunya, 2020. http://hdl.handle.net/10803/669282.
Abstract:
The advances in computing power have motivated the hope that computational methods can accelerate the pace of drug discovery pipelines. For this, fast, reliable and user-friendly tools are required. One of the fields that has gotten more attentions is the prediction of binding affinities. Two main problems have been identified for such methods: insufficient sampling and inaccurate models.
This thesis is focused on tackling the first problem. To this end, we present the development of efficient methods for the estimation of protein-ligand binding free energies. We have developed a protocol that combines enhanced sampling with more standard simulations methods to achieve higher efficiency. First, we run an exploratory enhanced sampling simulation, starting from the bound conformation and partially biased towards unbound poses. The we leverage the information gained from this short simulation to run, longer unbiased simulations to collect statistics.
Thanks to the modularity and automation that the protocol offers we were able to test three different methods for the long simulations: PELE, molecular dynamics and AdaptivePELE. PELE and molecular dynamics showed similar results, although PELE used less computational resources. Both seemed to work well with small protein-fragment systems or proteins with not very flexible binding sites. Both failed to accurately reproduce the binding of a kinase, the Mitogen-activated protein kinase 1 (ERK2). On the other hand, AdaptivePELE did not show a great improvement over PELE, with positive results for the Urokinase-type plasminogen activator (URO) and a clear lack of sampling for the Progesterone receptor (PR).
We demonstrated the importance of well-designed suite of test systems for the development of new methods. Through the use of a diverse benchmark of protein systems we have established the cases in which the protocol is expected to give accurate results, and which areas require further development. This benchmark consisted of four proteins, and over 30 ligands, much larger than the test systems typically used in the development of pathway-based free energy methods.
In summary, the methodology developed in this work can contribute to the drug discovery process for a limited range of protein systems. For many other, we have observed that regular unbiased simulations are not efficient enough and more sophisticated, enhanced sampling methods are required.Els grans avenços en la capacitat de computació han motivat l'esperança que els mètodes de simulacions per ordinador puguin accelerar el ritme de descobriment de nous fàrmacs. Per a què això sigui possible, es necessiten eines ràpides, acurades i fàcils d'utilitzar. Un dels problemes que han rebut més atenció és el de la predicció d'energies lliures d'unió entre proteïna i lligand. Dos grans problemes han estat identificats per a aquests mètodes: la falta de mostreig i les aproximacions dels models. Aquesta tesi està enfocada a resoldre el primer problema. Per a això, presentem el desenvolupament de mètodes eficients per a l'estimació de d'energies lliures d'unió entre proteïna i lligand. Hem desenvolupat un protocol que combina mètodes anomenats enhanced sampling amb simulació clàssiques per a obtenir una major eficiència. Els mètodes d'enhanced sampling són una classe d'eines que apliquen algun tipus de pertorbació externa al sistema que s'està estudiant per tal d'accelerar-ne el mostreig. En el nostre protocol, primer correm una simulació exploratòria d'enhanced sampling, començant per una mostra de la unió de la proteïna i el lligand. Aquesta simulació esta parcialment esbiaixada cap a aquells estats del sistema on els dos components es troben més separats. Després utilitzem la informació obtinguda d'aquesta primera simulació més curta per a córrer una segona simulació més llarga, amb mètodes sense biaix per obtenir una estadística fidedigna del sistema. Gràcies a la modularitat i el grau d'automatització que la implementació del protocol ofereix, hem pogut provar tres mètodes diferents per les simulacions llargues: PELE, dinàmica molecular i AdaptivePELE. PELE i dinàmica molecular han mostrat resultats similars, tot i que PELE utilitza menys recursos. Els dos han mostrat bons resultats en l'estudi de sistemes de fragments o amb proteïnes amb llocs d'unió poc flexibles. Però, els dos han fallat a l'hora de reproduir els resultats experimentals per a una quinasa, la Mitogen-activated protein kinase 1 (ERK2). D'altra banda, AdaptivePELE no ha mostrat una gran millora respecte a PELE, amb resultats positius per a la proteïna Urokinase-type plasminogen activator (URO) i una clara falta de mostreig per al receptor de progesterona (PR). En aquest treball hem demostrat la importància d'establir un banc de proves equilibrat durant el desenvolupament de nous mètodes. Mitjançant l'ús d'un banc de proves divers hem pogut establir en quins casos es pot esperar que el protocol obtingui resultats acurats, i quines àrees necessiten més desenvolupament. El banc de proves ha consistit de quatre proteïnes i més de trenta lligands, molt més dels que comunament s'utilitzen en el desenvolupament de mètodes per a la predicció d'energies d'unió mitjançant mètodes basats en camins (pathway-based). En resum, la metodologia desenvolupada durant aquesta tesi pot contribuir al procés de recerca de nous fàrmacs per a certs tipus de sistemes de proteïnes. Per a la resta, hem observat que els mètodes de simulació no esbiaixats no són prou eficients i tècniques més sofisticades són necessàries.
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Almlöf, Martin. "Computational Methods for Calculation of Ligand-Receptor Binding Affinities Involving Protein and Nucleic Acid Complexes." Doctoral thesis, Uppsala University, Department of Cell and Molecular Biology, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-7421.
Abstract:
The ability to accurately predict binding free energies from computer simulations is an invaluable resource in understanding biochemical processes and drug action. Several methods based on microscopic molecular dynamics simulations exist, and in this thesis the validation, application, and development of the linear interaction energy (LIE) method is presented.
For a test case of several hydrophobic ligands binding to P450cam it is found that the LIE parameters do not change when simulations are performed with three different force fields. The nonpolar contribution to binding of these ligands is best reproduced with a constant offset and a previously determined scaling of the van der Waals interactions.
A new methodology for prediction of binding free energies of protein-protein complexes is investigated and found to give excellent agreement with experimental results. In order to reproduce the nonpolar contribution to binding, a different scaling of the van der Waals interactions is neccesary (compared to small ligand binding) and found to be, in part, due to an electrostatic preorganization effect not present when binding small ligands.
A new treatment of the electrostatic contribution to binding is also proposed. In this new scheme, the chemical makeup of the ligand determines the scaling of the electrostatic ligand interaction energies. These scaling factors are calibrated using the electrostatic contribution to hydration free energies and proposed to be applicable to ligand binding.
The issue of codon-anticodon recognition on the ribosome is adressed using LIE. The calculated binding free energies are in excellent agreement with experimental results, and further predict that the Leu2 anticodon stem loop is about 10 times more stable than the Ser stem loop in complex with a ribosome loaded with the Phe UUU codon. The simulations also support the previously suggested roles of A1492, A1493, and G530 in the codon-anticodon recognition process.
25
Orro, Graña Adolfo. "Examination of the role of binding site water molecules in molecular recognition." Thesis, SciLifeLab Stockholm, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-200164.
Abstract:
A set of algorithms were designed, implemented and evaluated in order to, first, identifyclusters of conserved waters in binding pockets, i.e. hydration sites. Then, their contributionto the free energy of binding in a ligand-protein association was quantified by calculatingtheir enthalpy and entropy. The information obtained by using these algorithms couldcontribute to the development of new drugs by generating new ligands that target specifichigh-energy, unfavorable waters. Evaluation tests show that our algorithms can indeedprovide relevant data about how hydration sites influence ligand-protein binding.
26
Uciechowska, Urszula Sylwia [Verfasser], Wolfgang [Akademischer Betreuer] Sippl, Gerhard [Akademischer Betreuer] Wolber, and Manfred [Akademischer Betreuer] Jung. "Virtual screening and binding free energy calculations of sirtuin inhibitors / Urszula Sylwia Uciechowska. Betreuer: Wolfgang Sippl ; Gerhard Wolber ; Manfred Jung." Halle, Saale : Universitäts- und Landesbibliothek Sachsen-Anhalt, 2010. http://d-nb.info/1025133943/34.
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Gibson, Meghan E. "Examining the Role of Magnesium Ions in the Structural Stability of Ribosomal Subunits and An Investigation of a Novel Anticancer Therapeutic: Analyzing the Binding Affinity of a Stapled p53 Peptide Analog for Regulator MDM2." Thesis, Boston College, 2011. http://hdl.handle.net/2345/bc-ir:104431.
Abstract:
Thesis advisor: Udayan MohantyComputational research can play a crucial component in the discovery of unique biochemical phenomena, from answering fundamental questions about molecular function and structure to the modeling of designed pharmaceuticals to cure many debilitating illnesses. Here computational methods are employed to examine the exquisite role that magnesium ions play in stabilizing ribosomal subunits responsible for protein translation and to analyze the potential of a proposed anticancer drug for a pathway that is impaired in the majority of human cancer cases
Thesis (BS) — Boston College, 2011
Submitted to: Boston College. College of Arts and Sciences
Discipline: College Honors Program
Discipline: Chemistry
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Lind, Christoffer. "Computational Studies of Protein Synthesis on the Ribosome and Ligand Binding to Riboswitches." Doctoral thesis, Uppsala universitet, Beräkningsbiologi och bioinformatik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-328583.
Abstract:
The ribosome is a macromolecular machine that produces proteins in all kingdoms of life. The proteins, in turn, control the biochemical processes within the cell. It is thus of extreme importance that the machine that makes the proteins works with high precision. By using three dimensional structures of the ribosome and homology modelling, we have applied molecular dynamics simulations and free-energy calculations to study the codon specificity of protein synthesis in initiation and termination on an atomistic level. In addition, we have examined the binding of small molecules to riboswitches, which can change the expression of an mRNA. The relative affinities on the ribosome between the eukaryotic initiator tRNA to the AUG start codon and six near-cognate codons were determined. The free-energy calculations show that the initiator tRNA has a strong preference for the start codon, but requires assistance from initiation factors 1 and 1A to uphold discrimination against near-cognate codons. When instead a stop codon (UAA, UGA or UAG) is positioned in the ribosomal A-site, a release factor binds and terminates protein synthesis by hydrolyzing the nascent peptide chain. However, vertebrate mitochondria have been thought to have four stop codons, namely AGA and AGG in addition to the standard UAA and UAG codons. Furthermore, two release factors have been identified, mtRF1 and mtRF1a. Free-energy calculations were used to determine if any of these two factors could bind to the two non-standard stop codons, and thereby terminate protein synthesis. Our calculations showed that the mtRF’s have similar stop codon specificity as bacterial RF1 and that it is highly unlikely that the mtRF’s are responsible for terminating at the AGA and AGG stop codons. The eukaryotic release factor 1, eRF1, on the other hand, can read all three stop codons singlehandedly. We show that eRF1 exerts a high discrimination against near-cognate codons, while having little preference for the different cognate stop codons. We also found an energetic mechanism for avoiding misreading of the UGG codon and could identify a conserved cluster of hydrophobic amino acids which prevents excessive solvent molecules to enter the codon binding site. The linear interaction energy method was used to examine binding of small molecules to the purine riboswitch and the FEP method was employed to explicitly calculate the LIE b-parameters. We show that the purine riboswitches have a remarkably high degree of electrostatic preorganization for their cognate ligands which is fundamental for discriminating against different purine analogs.
29
Shamsudin, Khan Yasmin. "Non-Steroidal Anti-Inflammatory Drugs in Cyclooxygenases 1 and 2 : Binding modes and mechanisms from computational methods and free energy calculations." Doctoral thesis, Uppsala universitet, Beräkningsbiologi och bioinformatik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-328478.
Abstract:
Non-steroidal anti-inflammatory drugs (NSAIDs) are one of the most commonly used classes of drugs. They target the cyclooxygenases (COX) 1 and 2 to reduce the physiological responses of pain, fever, and inflammation. Due to their role in inducing angiogenesis, COX proteins have also been identified as targets in cancer therapies. In this thesis, I describe computational protocols of molecular docking, molecular dynamics simulations and free energy calculations. These methods were used in this thesis to determine structure-activity relationships of a diverse set of NSAIDs in binding to their target proteins COX-1 and 2. Binding affinities were calculated and used to predict the binding modes. Based on combinations of molecular dynamics simulations and free energy calculations, binding mechanisms of sub-classes of NSAIDs were also proposed. Two stable conformations of COX were probed to understand how they affect inhibitor affinities. Finally, a brief discussion on selectivity towards either COX isoform is discussed. These results will be useful in future de novo design and testing of third-generation NSAIDs.
30
Cook, Monica Mion. "Endocrine-Disrupting Compounds: Measurement in Tampa Bay, Removal from Sewage and Development of an Estrogen Receptor Model." Scholar Commons, 2015. http://scholarcommons.usf.edu/etd/5861.
Abstract:
The significance of endocrine-disrupting compounds (EDCs) in the environment has only recently come to the forefront of scientific research, policy debates, water utilities management and public awareness. EDCs have the ability to interfere with the normal functioning of the endocrine system of humans and other animals. Numerous chemicals are included in the class of compounds known as EDCs, and exposure is widespread. These compounds are found in a variety of environmental matrices (e.g., marine and freshwater systems, sediment, soil), transported there primarily through sewage effluent discharge and recycling of sewage sludge for topical fertilizer use. This transport to the environment serves as the primary route of exposure for aquatic and terrestrial organisms living there. Furthermore, these compounds are also found in consumer products, food and drinking water--which serve as the exposure source for human beings. Multiple examples of endocrine disruption have been documented in humans and animals, and certain EDCs have been implicated in each case. The future of public and environmental health will depend upon mitigating the effects of these chemicals.
This purpose of this dissertation is to provide an initial understanding of EDC occurrence in the Tampa Bay region of south Florida, and to complement the existing body of EDC research with regards to marine systems. It focuses on estrogenic EDCs, specific compounds which target the estrogen axis of the endocrine system. Six estrogenic EDCs were chosen based on their documented prevalence in the environment, prevalence in sewage, and for their suspected endocrine-disrupting effects: estrone, 17β-estradiol, estriol, 17α-ethinylestradiol, bisphenol-A and nonylphenol. These compounds were verified to be amenable to and detectable by gas chromatography-mass spectrometry analysis.
Since the occurrence of EDCs in aquatic environments of the Tampa Bay region had not been previously characterized, the initial phase of the research focused on quantification of the six estrogenic EDCs in Tampa Bay area water, sediment, and sewage influent and effluent. All targeted EDCs were present in 89% of sewage samples, while 100% of the samples contained at least one or more EDCs. The concentrations of EDCs in marine aqueous and sediment samples tended to decrease with increasing distance from the wastewater treatment plant discharge site. The ubiquitous presence of these estrogenic EDCs in the Tampa Bay area is cause for concern with respect to endocrine disruption in local terrestrial and aquatic wildlife. Since the Tampa Bay region is home to a wide variety of marine organisms, constant exposure to EDCs could result in ecosystem-level effects, as these compounds can impair reproductive fitness and lead to other adverse health effects. This research also served to enlarge the existing scientific literature on EDC occurrence, as many marine and freshwater systems continue to be characterized globally.
The very basis for expecting to find EDCs in the Tampa Bay area had come from the fact that the main source of environmental contamination is typically the effluent discharge from area wastewater treatment plants. Conventional wastewater treatment plant processes are designed to reduce the amount of organic matter, pathogens and nutrients from the incoming influent. However, the processes are not as effective in removing micropollutants, including EDCs. These compounds notoriously evade traditional wastewater treatment technologies and are found even in tertiary-treated effluent. For this reason, the second phase of the research assessed an electro-chemical technique for the removal of the same six EDCs. The removal technique was tested on a laboratory scale and has a commercial-sized counterpart which can be integrated at the level of the wastewater treatment plant. In order to test the removal efficiency, samples of influent and tertiary-treated effluent were spiked with the six EDCs. The mean concentration of each EDC component was statistically lower after treatment (removal range = 42% - 98.2%), demonstrating the effectiveness of this electro-chemical process for EDC removal from both raw and treated sewage. The significance of the results lies in the fact that if this method is implemented, then future wastewater treatment plant effluent discharge (similar to that of the Tampa Bay region) could be less impacted by EDCs and therefore cleaner for the environment into which it is being discharged.
For the final phase of the research, the use of computational techniques to simulate human endogenous estrogen binding to its receptor was started as a foundation for future models to eventually predict endocrine-disrupting potential of different chemical compounds. We built an estradiol-human estrogen receptor model, and used molecular dynamic simulations to determine the binding free energy. The calculated total binding free energy of estradiol bound to the ligand binding domain of the human estrogen receptor was found to be -16.85 kcal/mol, which is in range of the experimental value of -12.40 kcal/mol. Humans are chronically exposed to low doses of EDCs every day, which makes endocrine disruption a considerable public health issue. Human exposure to EDCs is completely different from marine organism exposure, but the adverse effects are no less significant. The successful completion of this model serves as a platform for 1. Testing the human model against endocrine-disrupting compounds, 2. Subsequent models that will be developed for different species, including marine species important to Tampa Bay.
Substantial data exist regarding the exposures and health risks associated with EDCs in humans and wildlife on a global scale. As the pressing issues of climate change and carbon emissions are at the top of the list of environmental concerns, it is important to note that mitigating the effects of EDCs should not be overlooked and will be an important responsibility of regulatory agencies in the near future.
31
Montalvo, Acosta Joel José. "Computational approaches to molecular recognition : from host-guest to protein-ligand binding." Thesis, Strasbourg, 2018. http://www.theses.fr/2018STRAF051/document.
Abstract:
La reconnaissance moléculaire est un problème très intéressant et surtout un défi actuel pour la chimie biophysique. Avoir des prévisions fiables sur la reconnaissance spécifique entre les molécules est hautement prioritaire, car il fournira un aperçu des problèmes fondamentaux et suscitera des applications technologiques pertinentes. La thèse présentée ici est centrée sur une analyse quantitatif de la reconnaissance moléculaire en solution pour la liaison l'hôte-invité, la liaison protéine-ligand et la catalyse. Le cadre de la mécanique statistique utilisé pour décrire l'état de la technique de liaison récepteur-ligand est un point d'inflexion pour le développement de nouvelles méthodes améliorées. En fait, un modèle très performant et précis a été obtenu pour l'analyse de la liaison hôte-invité. Enfin, les modèles présentés ont été utilisés comme outils prédictifs fiables pour la découverte de nouvelles entités chimiques destinées à améliorer la catalyse en solutionMolecular recognition is a very interesting problem, and foremost, a current challenge for biophysical chemistry. Having reliable predictions on the specific recognition between molecules is highly priority as it will provide an insight of fundamental problems and will raise relevant technological applications. The dissertation presented here is centered on a quantitative analysis of molecular recognition in solution for host-guest, protein-ligand binding and catalysis. The statistical mechanics framework used to describe the state-of-the-art for receptor-ligand binding is an inflection point for the developing of new improved and methods. In fact, a highly performanced and accurate model was obtained for the analysis of host-guest binding. Finally, the presented models were used as a reliable predictive tools for discovering new chemical entities for enhance catalysis in solution
32
Berg, Emily Katherine. "Thermodynamics of λ-PCR Primer Design and Effective Ribosome Binding Sites." Thesis, Virginia Tech, 2019. http://hdl.handle.net/10919/89900.
Abstract:
Recombinant DNA technology has been commonly used in a number of fields to synthesize new products or generate products with a new pathway. Conventional cloning methods are expensive and require significant time and labor; λ-PCR, a new cloning method developed in the Senger lab, has a number of advantages compared to other cloning processes due to its employment of relatively inexpensive and widely available materials and time-efficiency. While the amount of lab work required for the cloning process is minimal, the importance of accurate primer design cannot be overstated. The target of this study was to create an effective procedure for λ-PCR primer design that ensures accurate cloning reactions. Additionally, synthetic ribosome binding sites (RBS) were included in the primer designs to test heterologous protein expression of the cyan fluorescent reporter with different RBS strengths. These RBS sequences were designed with an online tool, the RBS Calculator.
A chimeric primer design procedure for λ-PCR was developed and shown to effectively create primers used for accurate cloning with λ-PCR; this method was used to design primers for CFP cloning in addition to two enzymes cloned in the Senger lab. A total of five strains of BL21(DE3) with pET28a + CFP were constructed, each with the same cyan fluorescent protein (CFP) reporter but different RBS sequences located directly upstream of the start codon of the CFP gene. Expression of the protein was measured using both whole-cell and cell-free systems to determine which system yields higher protein concentrations. A number of other factors were tested to optimize conditions for high protein expression, including: induction time, IPTG concentration, temperature, and media (for the cell-free experiments only). Additionally, expression for each synthetic RBS sequence was investigated to determine an accurate method for predicting protein translation. NUPACK and the Salis Lab RBS Calculator were both used to evaluate the effects of these different synthetic RBS sequences. The results of the plate reader experiments with the 5 CFP strains revealed a number of factors to be statistically significant when predicting protein expression, including: IPTG concentration, induction time, and in the cell-free experiments, type of media. The whole-cell system consistently produced higher amounts of protein than the cell-free system. Lastly, contrasts between the CFP strains showed each strain's performance did not match the predictions from the RBS Calculator. Consequently, a new method for improving protein expression with synthetic RBS sequences was developed using relationships between Gibbs free energy of the RBS-rRNA complex and expression levels obtained through experimentation. Additionally, secondary structure present at the RBS in the mRNA transcript was modeled with strain expression since these structures cause deviations in the relationship between Gibbs free energy of the mRNA-rRNA complex and CFP expression.Master of Science
Recombinant DNA technology has been used to genetically enhance organisms to produce greater amounts of a product already made by the organism or to make an organism synthesize a new product. Genes are commonly modified in organisms using cloning practices which typically involves inserting a target gene into a plasmid and transforming the plasmid into the organism of interest. A new cloning process developed in the Senger lab, λ-PCR, improves the cloning process compared to other methods due to its use of relatively inexpensive materials and high efficiency. A primary goal of this study was to develop a procedure for λ-PCR primer design that allows for accurate use of the cloning method. Additionally, this study investigated the use of synthetic ribosome binding sites to control and improve expression of proteins cloned into an organism. Ribosome binding sites are sequences located upstream of the gene that increase the molecule’s affinity for the rRNA sequence on the ribosome, bind to the ribosome just upstream of the beginning of the gene, and initiate expression of the gene. Tools have been developed that create synthetic ribosome binding sites designed to produce specific amounts of protein. For example, the tools can increase or decrease expression of a gene depending on the application. These tools, the Salis Lab RBS Calculator and NUPACK, were used to design and evaluate the effects of the synthetic ribosome binding sites. Additionally, a new method was created to design synthetic ribosome binding sites since the methods used during the design process yielded inaccuracies. Each strain of E. coli contained the same gene, a cyan fluorescent protein (CFP), but had different RBS sequences located upstream of the gene. Expression of CFP was controlled via induction, meaning the addition of a particular molecule, IPTG in this system, triggered expression of CFP. Each of the CFP strains were tested with a variety of v conditions in order to find the conditions most suitable for protein expression; the variables tested include: induction time, IPTG (inducer) concentration, and temperature. Media was also tested for the cell-free systems, meaning the strains were grown overnight for 18 hours and lysed, a process where the cell membrane is broken in order to utilize the cell’s components for protein expression; the cell lysate was resuspended in new media for the experiments. ANOVA and multiple linear regression revealed IPTG concentration, induction time, and media to be significant factors impacting protein expression. This analysis also showed each CFP strain did not perform as the RBS Calculator predicted. Modeling each strain’s CFP expression using the RBS-rRNA binding strengths and secondary structures present in the RBS allowed for the creation of a new model for predicting and designing RBS sequences.
33
Becker, Caroline [Verfasser], and Rainer [Akademischer Betreuer] Böckmann. "Development of computational methods for the prediction of protein structure, protein binding, and mutational effects using free energy calculations / Caroline Becker. Gutachter: Rainer Böckmann." Erlangen : Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 2014. http://d-nb.info/1054331456/34.
34
Boukharta, Lars. "Computational Modelling of Ligand Complexes with G-Protein Coupled Receptors, Ion Channels and Enzymes." Doctoral thesis, Uppsala universitet, Beräknings- och systembiologi, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-212103.
Abstract:
Accurate predictions of binding free energies from computer simulations are an invaluable resource for understanding biochemical processes and drug action. The primary aim of the work described in the thesis was to predict and understand ligand binding to several proteins of major pharmaceutical importance using computational methods. We report a computational strategy to quantitatively predict the effects of alanine scanning and ligand modifications based on molecular dynamics free energy simulations. A smooth stepwise scheme for free energy perturbation calculations is derived and applied to a series of thirteen alanine mutations of the human neuropeptide Y1 G-protein coupled receptor and a series of eight analogous antagonists. The robustness and accuracy of the method enables univocal interpretation of existing mutagenesis and binding data. We show how these calculations can be used to validate structural models and demonstrate their ability to discriminate against suboptimal ones. Site-directed mutagenesis, homology modelling and docking were further used to characterize agonist binding to the human neuropeptide Y2 receptor, which is important in feeding behavior and an obesity drug target. In a separate project, homology modelling was also used for rationalization of mutagenesis data for an integron integrase involved in antibiotic resistance. Blockade of the hERG potassium channel by various drug-like compounds, potentially causing serious cardiac side effects, is a major problem in drug development. We have used a homology model of hERG to conduct molecular docking experiments with a series of channel blockers, followed by molecular dynamics simulations of the complexes and evaluation of binding free energies with the linear interaction energy method. The calculations are in good agreement with experimental binding affinities and allow for a rationalization of three-dimensional structure-activity relationships with implications for design of new compounds. Docking, scoring, molecular dynamics, and the linear interaction energy method were also used to predict binding modes and affinities for a large set of inhibitors to HIV-1 reverse transcriptase. Good agreement with experiment was found and the work provides a validation of the methodology as a powerful tool in structure-based drug design. It is also easily scalable for higher throughput of compounds.
35
Donnini, S. (Serena). "Computing free energies of protein-ligand association." Doctoral thesis, University of Oulu, 2007. http://urn.fi/urn:isbn:9789514285745.
Abstract:
Abstract
Spontaneous changes in protein systems, such as the binding of a ligand to an enzyme or receptor, are characterized by a decrease of free energy. Despite the recent developments in computing power and methodology, it remains challenging to accurately estimate free energy changes. Major issues are still concerned with the accuracy of the underlying model to describe the protein system and how well the calculation in fact emulates the behaviour of the system.
This thesis is largely concerned with the quality of current free energy calculation methods as applied to protein-ligand systems. Several methodologies were employed to calculate Gibbs standard free energies of binding for a collection of protein-ligand complexes, for which experimental affinities were available. Calculations were performed using system description with different levels of accuracy and included a continuum approach, which considers the protein and the ligand at the atomic level but includes solvent as a polarizable continuum, and an all-atom approach that relies on molecular dynamics simulations.
In most such applications, the effects of ionic strength are neglected. However, the severity of this approximation, in particular when calculating free energies of charged ligands, is not very clear. The issue of incorporating ionic strength in free energy calculations by means of explicit ions was investigated in greater detail and considerable attention was given to the affinities of charged peptides in the presence of explicit counter-ions. A second common approximation is concerned with the description of ligands that exhibit multiple protonation states. Because most of current methods do not model changes in the acid dissociation constants of titrating groups upon binding, protonation equilibria of such ligands are not taken into account in free energy calculations. The implications of this approximation when predicting affinities were analysed.
Finally, when calculating free energies of binding, a correct description of the interactions between the protein and the ligand is of fundamental importance. However, active sites of enzymes, where strained conformations may hold a functional role, are not always accurately modelled by molecular mechanics force fields. The case of a strained planar proline in the active site of triosephosphate isomerase was investigated using an hybrid quantum mechanics/molecular mechanics method, which implies a higher level of accuracy.
36
Mackness, Brian C. "The Identification and Targeting of Partially-Folded Conformations on the Folding Free-Energy Landscapes of ALS-Linked Proteins for Therapeutic Intervention: A Dissertation." eScholarship@UMMS, 2016. https://escholarship.umassmed.edu/gsbs_diss/826.
Abstract:
The hallmark feature of many neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS), is the accumulation of cytoplasmic inclusions of key disease-linked proteins. Two of these proteins, TDP-43 and SOD1, represent a significant proportion of sporadic and familial ALS cases, respectively. The population of potentially aggregation-prone partially-folded states on the folding free-energy landscape may serve as a common mechanism for ALS pathogenesis. A detailed biophysical understanding of the folding and misfolding energy landscapes of TDP-43 and SOD1 can provide critical insights into the design of novel therapeutics to delay onset and progression in ALS.
Equilibrium unfolding studies on the RNA recognition motif (RRM) domains of TDP-43 revealed the population of a stable RRM intermediate in RRM2, with residual structure localized to the N-terminal half of the domain. Other RRM domains from FUS/TLS and hnRNP A1 similarly populate RRM intermediates, suggesting a possible connection with disease. Mutations, which enhance the population of the RRM2 intermediate, could serve as tools for deciphering the functional and misfolding roles of this partially-folded state in disease models, leading to the development of new biomarkers to track ALS progression.
ALS mutations in SOD1 have been shown to destabilize the stable homodimer to result in increased populations of the monomeric and unfolded forms of SOD1. Mechanistic insights into the misfolding of SOD1 demonstrated that the unfolded state is a key species in the initiation and propagation of aggregation, suggesting that limiting these populations may provide therapeutic benefit to ALS patients. An in vitro time-resolved Förster Resonance Energy Transfer assay to screen small molecules that stabilize the native state of SOD1 has identified several lead compounds, providing a pathway to new therapeutics to treat ALS.
37
Mackness, Brian C. "The Identification and Targeting of Partially-Folded Conformations on the Folding Free-Energy Landscapes of ALS-Linked Proteins for Therapeutic Intervention: A Dissertation." eScholarship@UMMS, 2004. http://escholarship.umassmed.edu/gsbs_diss/826.
Abstract:
The hallmark feature of many neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS), is the accumulation of cytoplasmic inclusions of key disease-linked proteins. Two of these proteins, TDP-43 and SOD1, represent a significant proportion of sporadic and familial ALS cases, respectively. The population of potentially aggregation-prone partially-folded states on the folding free-energy landscape may serve as a common mechanism for ALS pathogenesis. A detailed biophysical understanding of the folding and misfolding energy landscapes of TDP-43 and SOD1 can provide critical insights into the design of novel therapeutics to delay onset and progression in ALS.
Equilibrium unfolding studies on the RNA recognition motif (RRM) domains of TDP-43 revealed the population of a stable RRM intermediate in RRM2, with residual structure localized to the N-terminal half of the domain. Other RRM domains from FUS/TLS and hnRNP A1 similarly populate RRM intermediates, suggesting a possible connection with disease. Mutations, which enhance the population of the RRM2 intermediate, could serve as tools for deciphering the functional and misfolding roles of this partially-folded state in disease models, leading to the development of new biomarkers to track ALS progression.
ALS mutations in SOD1 have been shown to destabilize the stable homodimer to result in increased populations of the monomeric and unfolded forms of SOD1. Mechanistic insights into the misfolding of SOD1 demonstrated that the unfolded state is a key species in the initiation and propagation of aggregation, suggesting that limiting these populations may provide therapeutic benefit to ALS patients. An in vitro time-resolved Förster Resonance Energy Transfer assay to screen small molecules that stabilize the native state of SOD1 has identified several lead compounds, providing a pathway to new therapeutics to treat ALS.
38
Buch, Mundó Ignasi 1984. "Investigation of protein-ligand interactions using high-throughput all-atom molecular dynamics simulations." Doctoral thesis, Universitat Pompeu Fabra, 2012. http://hdl.handle.net/10803/101407.
Abstract:
Investigation of protein-ligand interactions has been a long-standing application for molecular dynamics (MD) simulations given its importance to drug design. However, relevant timescales for biomolecular motions are orders of magnitude longer than the commonly accessed simulation times. Adequate sampling of biomolecular phase-space has therefore been a major challenge in computational modeling that has limited its applicability. The primary objective for this thesis has been the brute-force simulation of costly protein-ligand binding modeling experiments on a large computing infrastructure. We have built and developed GPUGRID: a peta-scale distributed computing infrastructure for high-throughput MD simulations. We have used GPUGRID for the calculation of protein-ligand binding free energies as well as for the reconstruction of binding processes through unguided ligand binding simulations. The promising results presented herein, may have set the grounds for future applications of high-throughput MD simulations to drug discovery programs.
39
Suciu, Ioana. "Energy aware optimization for low power radio technologies." Doctoral thesis, Universitat Politècnica de Catalunya, 2020. http://hdl.handle.net/10803/668889.
Abstract:
The explosive growth of IoT is pushing the market towards cheap, very low power devices with a strong focus on miniaturization, for applications such as in-body sensors, personal health monitoring and microrobots. Proposing procedures for energy efficiency in IoT is a difficult task, as it is a rapidly growing market comprised of many and very diverse product categories using technologies that are not stable, evolving at a high pace. The research in this field proposes solutions that go from physical layer optimization up to the network layer, and the sensor network designer has to select the techniques that are best for its application specific architecture and radio technology used. This work is focused on exploring new techniques for enhancing the energy efficiency and user experience of IoT networks. We divide the proposed techniques in frame and chip level optimization techniques, respectively. While the frame level techniques are meant to improve the performance of existing radio technologies, the chip level techniques aim at replacing them with crystal-free architectures.
The identified frame level techniques are the use of preamble authentication and packet fragmentation, advisable for Low Power Wide Area Networks (LPWANs), a technology that offers the lowest energy consumption per provided service, but is vulnerable in front of energy exhaustion attacks and does not perform well in dense networks. The use of authenticated preambles between the sensors and gateways becomes a defence mechanism against the battery draining intended by attackers. We show experimentally that this approach is able to reduce with 91% the effect of an exhaustion attack, increasing the device's lifetime from less than 0.24 years to 2.6 years. The experiments were conducted using Loadsensing sensor nodes, commercially used for critical infrastructure control and monitoring. Even if exemplified on LoRaWAN, the use of preamble authentication is extensible to any wireless protocol. The use of packet fragmentation despite the packet fits the frame, is shown to reduce the probability of collisions while the number of users in the duty-cycle restricted network increases. Using custom-made Matlab simulations, important goodput improvement was obtained with fragmentation, with higher impact in slower and denser networks. Using NS3 simulations, we showed that combining packet fragmentation with group NACK can increase the network reliability, while reducing the energy consumed for retransmissions, at the cost of adding small headers to each fragment. It is a strategy that proves to be effective in dense duty-cycle restricted networks only, where the headers overhead is negligible compared to the network traffic.
As a chip level technique, we consider using radios for communication that do not use external frequency references such as crystal oscillators. This would enable having all sensor's elements on a single piece of silicon, rendering it even ten times more energy efficient due to the compactness of the chip. The immediate consequence is the loss of communication accuracy and ability to easily switch communication channels. In this sense, we propose a sequence of frequency synchronization algorithms and phases that have to be respected by a crystal-free device so that it can be able to join a network by finding the beacon channel, synthesize all communication channels and then maintain their accuracy against temperature change. The proposed algorithms need no additional network overhead, as they are using the existing network signaling. The evaluation is made in simulations and experimentally on a prototype implementation of an IEEE802.15.4 crystal-free radio. While in simulations we are able to change to another communication channel with very good frequency accuracy, the results obtained experimentally show an initial accuracy slightly above 40ppm, which will be later corrected by the chip to be below 40 ppm.El crecimiento significativo de la IoT está empujando al mercado hacia el desarrollo de dispositivos de bajo coste, de muy bajo consumo energético y con un fuerte enfoque en la miniaturización, para aplicaciones que requieran sensores corporales, monitoreo de salud personal y micro-robots. La investigación en el campo de la eficiencia energética en la IoT propone soluciones que van desde la optimización de la capa física hasta la capa de red. Este trabajo se centra en explorar nuevas técnicas para mejorar la eficiencia energética y la experiencia del usuario de las redes IoT. Dividimos las técnicas propuestas en técnicas de optimización de nivel de trama de red y chip, respectivamente. Si bien las técnicas de nivel de trama están destinadas a mejorar el rendimiento de las tecnologías de radio existentes, las técnicas de nivel de chip tienen como objetivo reemplazarlas por arquitecturas que no requieren de cristales. Las técnicas de nivel de trama desarrolladas en este trabajo son el uso de autenticación de preámbulos y fragmentación de paquetes, aconsejables para redes LPWAN, una tecnología que ofrece un menor consumo de energía por servicio prestado, pero es vulnerable frente a los ataques de agotamiento de energía y no escalan frente la densificación. El uso de preámbulos autenticados entre los sensores y las pasarelas de enlace se convierte en un mecanismo de defensa contra el agotamiento del batería previsto por los atacantes. Demostramos experimentalmente que este enfoque puede reducir con un 91% el efecto de un ataque de agotamiento, aumentando la vida útil del dispositivo de menos de 0.24 años a 2.6 años. Los experimentos se llevaron a cabo utilizando nodos sensores de detección de carga, utilizados comercialmente para el control y monitoreo de infrastructura crítica. Aunque la técnica se ejemplifica en el estándar LoRaWAN, el uso de autenticación de preámbulo es extensible a cualquier protocolo inalámbrico. En esta tesis se muestra también que el uso de la fragmentación de paquetes a pesar de que el paquete se ajuste a la trama, reduce la probabilidad de colisiones mientras aumenta el número de usuarios en una red con restricciones de ciclos de transmisión. Mediante el uso de simulaciones en Matlab, se obtiene una mejora importante en el rendimiento de la red con la fragmentación, con un mayor impacto en redes más lentas y densas. Usando simulaciones NS3, demostramos que combinar la fragmentación de paquetes con el NACK en grupo se puede aumentar la confiabilidad de la red, al tiempo que se reduce la energía consumida para las retransmisiones, a costa de agregar pequeños encabezados a cada fragmento. Como técnica de nivel de chip, consideramos el uso de radios para la comunicación que no usan referencias de frecuencia externas como los osciladores basados en un cristal. Esto permitiría tener todos los elementos del sensor en una sola pieza de silicio, lo que lo hace incluso diez veces más eficiente energéticamente debido a la integración del chip. La consecuencia inmediata, en el uso de osciladores digitales en vez de cristales, es la pérdida de precisión de la comunicación y la capacidad de cambiar fácilmente los canales de comunicación. En este sentido, proponemos una secuencia de algoritmos y fases de sincronización de frecuencia que deben ser respetados por un dispositivo sin cristales para que pueda unirse a una red al encontrar el canal de baliza, sintetizar todos los canales de comunicación y luego mantener su precisión contra el cambio de temperatura. Los algoritmos propuestos no necesitan una sobrecarga de red adicional, ya que están utilizando la señalización de red existente. La evaluación se realiza en simulaciones y experimentalmente en una implementación prototipo de una radio sin cristal IEEE802.15.4. Los resultados obtenidos experimentalmente muestran una precisión inicial ligeramente superior a 40 ppm, que luego será corregida por el chip para que sea inferior a 40 ppm.
40
Andér, Martin. "Computational Analysis of Molecular Recognition Involving the Ribosome and a Voltage Gated K+ Channel." Doctoral thesis, Uppsala universitet, Institutionen för cell- och molekylärbiologi, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-101413.
Abstract:
Over the last few decades, computer simulation techniques have been established as an essential tool for understanding biochemical processes. This thesis deals mainly with the application of free energy calculations to ribosomal complexes and a cardiac ion channel. The linear interaction energy (LIE) method is used to explore the energetic properties of the essential process of codon–anticodon recognition on the ribosome. The calculations show the structural and energetic consequences and effects of first, second, and third position mismatches in the ribosomal decoding center. Recognition of stop codons by ribosomal termination complexes is fundamentally different from sense codon recognition. Free energy perturbation simulations are used to study the detailed energetics of stop codon recognition by the bacterial ribosomal release factors RF1 and RF2. The calculations explain the vastly different responses to third codon position A to G substitutions by RF1 and RF2. Also, previously unknown highly specific water interactions are identified. The GGQ loop of ribosomal RFs is essential for its hydrolytic activity and contains a universally methylated glutamine residue. The structural effect of this methylation is investigated. The results strongly suggest that the methylation has no effect on the intrinsic conformation of the GGQ loop, and, thus, that its sole purpose is to enhance interactions in the ribosomal termination complex. A first microscopic, atomic level, analysis of blocker binding to the pharmaceutically interesting potassium ion channel Kv1.5 is presented. A previously unknown uniform binding mode is identified, and experimental binding data is accurately reproduced. Furthermore, problems associated with pharmacophore models based on minimized gas phase ligand conformations are highlighted. Generalized Born and Poisson–Boltzmann continuum models are incorporated into the LIE method to enable implicit treatment of solvent, in an effort to improve speed and convergence. The methods are evaluated and validated using a set of plasmepsin II inhibitors.
41
Kamble, Sharad R. "Molecular interactions in pharmaceutical preformulation and supramolecular complexes. Structural properties governing drug-plasma protein binding and investigation of amino acids co-crystals." Thesis, University of Bradford, 2018. http://hdl.handle.net/10454/16882.
Abstract:
The study of pharmaceutical preformulation includes the evaluation of
pharmacokinetic, pharmacodynamic and physicochemical properties of the drug
molecules that aid the formulation. However, it has a limited role in determining
drug dosage optimisation in the formulation. The study of drug-Plasma Protein
Binding (PPB), and the lipophilicity, solubility, and ionic behaviours of the
desired drug molecules addresses the gap and enhances our undertraining
related to the behaviour of the drug molecules in the body.
The High-Performance Liquid Chromatography (HPLC) technique was used in
the current study to assess drug-PPB interaction. Using Michael Abraham’s
‘Linear Free Energy Relationship’ (LFER) method, two major plasma proteins
namely, Human Serum Albumin as HSA and α-1-Acid Glycoprotein as AGP,
were used and the structural properties governing drug-plasma protein binding
was determined. This is the first time that the effect of ionised species on PPB
has been quantitatively evaluated. In addition, the molecular interactions also play a key role in the supramolecular complexes of co-crystals.
The project also evaluated the co-crystallisation process and its effect on physicochemical properties of the drug. In the current study, amino acids (AAs) have been observed to be a prominent source of
coformers. The AAs showed co-crystals formation with carboxylic acids, nonsteroidal
anti-inflammatory drug (NSAID) and citric acid which overcome the hygroscopicity problems and improved the physical stability issues during storage. This study has also identified a new formulation which is helpful for improvement in the stability of effervescent tablets at various relative humidity
(RH) conditions which will reduce the manufacturing cost associated with the
production of effervescent tablets.
42
Alonso, Hernan, and hernan alonso@anu edu au. "Computer Modelling and Simulations of Enzymes and their Mechanisms." The Australian National University. The John Curtin School of Medical Research, 2006. http://thesis.anu.edu.au./public/adt-ANU20061212.161155.
Abstract:
Although the tremendous catalytic power of enzymes is widely recognized, their exact mechanisms of action are still a source of debate. In order to elucidate the origin of their power, it is necessary to look at individual residues and atoms, and establish their contribution to ligand binding, activation, and reaction. Given the present limitations of experimental techniques, only computational tools allow for such detailed analysis. During my PhD studies I have applied a variety of computational methods, reviewed in Chapter 2, to the study of two enzymes: DfrB dihydrofolate reductase (DHFR) and methyltetrahydrofolate: corrinoid/iron-sulfur protein methyltransferase (MeTr).
¶
The DfrB enzyme has intrigued microbiologists since it was discovered thirty years ago, because of its simple structure, enzymatic inefficiency, and its insensitivity to trimethoprim. This bacterial enzyme shows neither structural nor sequence similarity with its chromosomal counterpart, despite both catalysing the reduction of dihydrofolate (DHF) using NADPH as a cofactor. As numerous attempts to obtain experimental structures of an enzyme ternary complex have been unsuccessful, I combined docking studies and molecular dynamics simulations to produce a reliable model of the reactive DfrBDHFNADPH complex. These results, combined with published empirical data, showed that multiple binding modes of the ligands are possible within DfrB.
¶
Comprehensive sequence and structural analysis provided further insight into the DfrB family. The presence of the dfrB genes within integrons and their level of sequence conservation suggest that they are old structures that had been diverging well before the introduction of trimethoprim. Each monomer of the tetrameric active enzyme presents an SH3-fold domain; this is a eukaryotic auxiliary domain never found before as the sole domain of a protein, let alone as the catalytic one. Overall, DfrB DHFR seems to be a poorly adapted catalyst, a minimalistic enzyme that promotes the reaction by facilitating the approach of the ligands rather than by using specific catalytic residues.
¶
MeTr initiates the Wood-Ljungdahl pathway of anaerobic CO2 fixation. It catalyses the transfer of the N5-methyl group from N5-methyltetrahydrofolate (CH3THF) to the cobalt centre of a corrinoid/iron-sulfur protein. For the reaction to occur, the N5 position of CH3THF is expected to be activated by protonation. As experimental studies have led to conflicting suggestions, computational approaches were used to address the activation mechanism.
¶
Initially, I tested the accuracy of quantum mechanical (QM) methods to predict protonation positions and pKas of pterin, folate, and their analogues. Then, different protonation states of CH3THF and active-site aspartic residues were analysed. Fragment QM calculations suggested that the pKa of N5 in CH3THF is likely to increase upon protein binding. Further, ONIOM calculations which accounted for the complete protein structure indicated that active-site aspartic residues are likely to be protonated before the ligand. Finally, solvation and binding free energies of several protonated forms of CH3THF were compared using the thermodynamic integration approach. Taken together, these preliminary results suggest that further work with particular emphasis on the protonation state of active-site aspartic residues is needed in order to elucidate the protonation and activation mechanism of CH3THF within MeTr.
43
Shekfeh, Suhaib [Verfasser], Wolfgang [Akademischer Betreuer] Sippl, Gerhard [Akademischer Betreuer] Wolber, and Maciej [Akademischer Betreuer] Baginski. "Virtual screening and end-point binding free energy methods for developing targeted cancer therapies : applications on acetyltransferases and protein kinases as case studies / Suhaib Shekfeh. Betreuer: Wolfgang Sippl ; Gerhard Wolber ; Maciej Baginski." Halle, Saale : Universitäts- und Landesbibliothek Sachsen-Anhalt, 2015. http://d-nb.info/1070585947/34.
44
Chen, Wei. "Molecular dynamics simulations of binding, unfolding, and global conformational changes of signaling and adhesion molecules." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/28118.
Abstract:
Thesis (M. S.)--Mechanical Engineering, Georgia Institute of Technology, 2009.Committee Chair: Zhu, Cheng; Committee Member: Harvey, Stephen; Committee Member: Hud, Nicholas; Committee Member: Zamir, Evan; Committee Member: Zhu, Ting.
45
Hernández, Alvarez Lilian [UNESP]. "Identification and characterization of cruzain allosteric inhibitors: a computer-aided approach." Universidade Estadual Paulista (UNESP), 2017. http://hdl.handle.net/11449/151919.
Abstract:
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
Trypanosoma cruzi é o agente causal da doença de Chagas, uma infecção negligenciada que afeta milhões de pessoas nas regiões tropicais. A maioria dos fármacos empregados no tratamento desta doença são altamente tóxicos e geram resistência. Na atualidade, o descobrimento de inibidores alostéricos é um tópico emergente dentro da área de desenho computacional de fármacos, pois promove a acessibilidade a medicamentos mais seletivos e menos tóxicos. Neste trabalho foi desenvolvida uma estratégia para a descoberta computacional de inibidores alostéricos a qual foi aplicada à cruzaína, a principal cisteíno protease do T. cruzi. A caracterização molecular da forma livre e ligada da cruzaína foi investigada através do ancoramento molecular, simulações de dinâmica molecular, cálculos de energia livre de ligação e construção de redes de interações entre resíduos. A partir da análise baseada na geometria das estruturas geradas na dinâmica molecular, foram detectados dois potenciais sítios alostéricos na cruzaína. Os resultados sugerem a existência de diferentes mecanismos de regulação exercidos pela ligação de inibidores diferentes no mesmo sítio alostérico. Além disso, foram identificados os resíduos que estabelecem os caminhos de transmissão de informação entre um dos sítios alostéricos identificado e o sítio ativo da enzima. O presente estudo é a primeira aproximação de desenho de inibidores alostéricos da cruzaína e serve para futuras intervenções farmacológicas. Esses resultados constituem uma base para o desenho de inibidores específicos de cisteíno proteases homólogas da papaína.
Trypanosoma cruzi is the causative agent of Chagas disease, a neglected infection affecting millions of people in tropical regions. There are several chemotherapeutic agents for the treatment of this disease, but most of them are highly toxic and generate resistance. Currently, the development of allosteric inhibitors constitutes a promising research field, since it may improve the accessibility to more selective and less toxic medicines. To date, the allosteric drugs prediction is a state-of-the-art topic in rational structure-based computational design. In this work a simulation strategy was developed for computational discovery of allosteric inhibitors, and it was applied for or cruzain, a promising target and the major cysteine protease of T. cruzi. Molecular dynamics simulations, binding free energy calculations and network-based modelling of residue interactions were combined to characterize and compare molecular distinctive features of the apo form and the cruzain-allosteric inhibitor complexes. By using geometry-based detection on trajectory snapshots we determined the existence of two main allosteric sites suitable for drug targeting. The results suggest dissimilar mechanism exerted by the same allosteric site when binding different potential allosteric inhibitors. Finally, we identified the residues involved in suboptimal paths linking the identified site and the orthosteric site. The present study constitutes the first approximation for designing cruzain allosteric inhibitors and may serve for future pharmacological intervention. These findings are particularly relevant for the design of allosteric modulators of papain-like cysteine proteases.
CAPES: 031/2013
46
Domin, Gesine, Sven Findeiß, Manja Wachsmuth, Sebastian Will, Peter F. Stadler, and Mario Mörl. "Applicability of a computational design approach for synthetic riboswitches." Universitätsbibliothek Leipzig, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-218007.
Abstract:
Riboswitches have gained attention as tools for synthetic biology, since they enable researchers to reprogram cells to sense and respond to exogenous molecules. In vitro evolutionary approaches produced numerous RNA aptamers that bind such small ligands, but their conversion into functional riboswitches remains difficult. We previously developed a computational approach for the design of synthetic theophylline riboswitches based on secondary structure prediction. These riboswitches have been constructed to regulate ligand dependent transcription termination in Escherichia coli. Here, we test the usability of this design strategy by applying the approach to tetracycline and streptomycin aptamers. The resulting tetracycline riboswitches exhibit robust regulatory properties in vivo. Tandem fusions of these riboswitches with theophylline riboswitches represent logic gates responding to two different input signals. In contrast, the conversion of the streptomycin aptamer into functional riboswitches appears to be difficult. Investigations of the underlying aptamer secondary structure revealed differences between in silico prediction and structure probing. We conclude that only aptamers adopting the minimal free energy (MFE) structure are suitable targets for construction of synthetic riboswitches with design approaches based on equilibrium thermodynamics of RNA structures. Further improvements in the design strategy are required to implement aptamer
structures not corresponding to the calculated MFE state.
47
Domin, Gesine, Sven Findeiß, Manja Wachsmuth, Sebastian Will, Peter F. Stadler, and Mario Mörl. "Applicability of a computational design approach for synthetic riboswitches." Oxford University Press, 2016. https://ul.qucosa.de/id/qucosa%3A15259.
Abstract:
Riboswitches have gained attention as tools for synthetic biology, since they enable researchers to reprogram cells to sense and respond to exogenous molecules. In vitro evolutionary approaches produced numerous RNA aptamers that bind such small ligands, but their conversion into functional riboswitches remains difficult. We previously developed a computational approach for the design of synthetic theophylline riboswitches based on secondary structure prediction. These riboswitches have been constructed to regulate ligand dependent transcription termination in Escherichia coli. Here, we test the usability of this design strategy by applying the approach to tetracycline and streptomycin aptamers. The resulting tetracycline riboswitches exhibit robust regulatory properties in vivo. Tandem fusions of these riboswitches with theophylline riboswitches represent logic gates responding to two different input signals. In contrast, the conversion of the streptomycin aptamer into functional riboswitches appears to be difficult. Investigations of the underlying aptamer secondary structure revealed differences between in silico prediction and structure probing. We conclude that only aptamers adopting the minimal free energy (MFE) structure are suitable targets for construction of synthetic riboswitches with design approaches based on equilibrium thermodynamics of RNA structures. Further improvements in the design strategy are required to implement aptamer
structures not corresponding to the calculated MFE state.
48
Bessoud, Agnès. "Analyse des interactions dans des alliages à base de métaux de transition." Grenoble INPG, 1989. http://www.theses.fr/1989INPG0091.
Abstract:
Calcul, a partir d'un hamiltonien de liaisons fortes et de la methode de l'amas-reseau de bethe, de la structure electronique et l'energie de formation d'alliages binaires de structure cubique centree ou cubique a faces centrees. En utilisant l'entropie de configuration traitee par la methode variationnelle des amas, l'energie libre de formation a ete obtenue par minimisation par rapport au parametre d'ordre a courte distance
49
Chen, Po-Chin, and 陳博晉. "Computation of Binding Free Energy of Inhibitor-Erk Kinase Complexs Using Thermodynamic Integration Molecular Dynamics Simulation." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/31597834109755377411.
Abstract:
碩士國立臺灣師範大學
化學系
100
Erk is the downstream protein in the Ras/Raf/MEK/ERK signal transduction pathway which is deregulated in many cancers. In the present study, we select this kinase to design new inhibitors for this kinase using MD simulation. Previous computations have shown that thermodynamic integration (TI) MD simulation method is able to give relative binding free energy for a pair of inhibitors for this kinase in good agreement with experimental results. In the present study, we carried out TI-MD computations for new analogous compounds in searching for better inhibitors. An analog with –OH functional group on the benzene ring was found to have better affinity than the 82A ligand by 1.1 kcal/mol. In addition, we investigate how single mutational step performs compared with the triple mutational steps in the TI-MD method. Furthermore, effect of number of lambda points in the computed relative binding free energy was investigated as well. These results should be useful for further TI-MD simulation and inhibitor design of this kind.
50
Chang, Jeng-Yih, and 張正義. "Study of the Aggregation of β-amyloid Peptide (Aβ) : Monte Carlo Simulations and Binding Free Energy Calculations." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/71038099971134684738.
Abstract:
碩士國立陽明大學
生物醫學資訊研究所
96
Alzheimer's disease (AD) is the most common form of dementia in aged population. It gradually impairs patients' memory, cognition, and behavior. One of the molecular pathology of this disease is defined by the presence within the brain of senile plaques. The senile plaques are made of deposits of the β-amyloid peptide (Aβ). Generally, Aβ can be dissolved in water and exists as a random coil conformation. However, under certain conditions, Aβ will form aggregates of β-sheets. Then, these aggregates are arranged as insoluble fibrils which cause neurotoxicity. Previous studies indicate that mutations will affect the aggregation ability of Aβ. When Leu17 and Phe19 are mutated to Ala, the aggregation rate of Aβ will be decreased in water. But another mutation of Glu22 to Gly (Dutch mutant) forms protofibrils more rapidly than wild type. Here we use Monte Carlo simulation and binding free energy calculation to investigate the differences between the Aβ (L17A/F19A) mutant, Aβ (E22G) mutant and Aβ wild type. Aβ (L17A/F19A) mutant shows a lower probability to form β-sheet stacking in Monte Carlo simulation. In addition, the binding free energy of Aβ (L17A/F19A) mutant is also higher than that of Aβ wild type. These results mean that the Aβ (L17A/F19A) mutant is more difficult to form aggregates of β-sheets. But Aβ (E22G) mutant is different with Aβ (L17A/F19A) mutant. The binding free energy of Aβ (E22G) mutant is lower than that of Aβ wild type. So Aβ (E22G) mutant is easier to aggregate. The results of this study are in good agreement with previous experimental studies.