Relevant bibliographies by topics / Standard Binding Free Energy

Academic literature on the topic 'Standard Binding Free Energy'

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Published: 8 June 2024

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Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Journal articles on the topic "Standard Binding Free Energy":

1

Kötter, Alex, Henning D. Mootz, and Andreas Heuer. "Standard Binding Free Energy of a SIM–SUMO Complex." Journal of Chemical Theory and Computation 15, no. 11 (September 17, 2019): 6403–10. http://dx.doi.org/10.1021/acs.jctc.9b00428.

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General, Ignacio J. "A Note on the Standard State’s Binding Free Energy." Journal of Chemical Theory and Computation 6, no. 8 (July 15, 2010): 2520–24. http://dx.doi.org/10.1021/ct100255z.

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Zhang, Hong, Hugo Gattuso, Elise Dumont, Wensheng Cai, Antonio Monari, Christophe Chipot, and François Dehez. "Accurate Estimation of the Standard Binding Free Energy of Netropsin with DNA." Molecules 23, no. 2 (January 25, 2018): 228. http://dx.doi.org/10.3390/molecules23020228.

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4

Doudou, Slimane, Neil A. Burton, and Richard H. Henchman. "Standard Free Energy of Binding from a One-Dimensional Potential of Mean Force." Journal of Chemical Theory and Computation 5, no. 4 (March 10, 2009): 909–18. http://dx.doi.org/10.1021/ct8002354.

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Jandova, Zuzana, Willem Jespers, Eddy Sotelo, Hugo Gutiérrez-de-Terán, and Chris Oostenbrink. "Free-Energy Calculations for Bioisosteric Modifications of A3 Adenosine Receptor Antagonists." International Journal of Molecular Sciences 20, no. 14 (July 16, 2019): 3499. http://dx.doi.org/10.3390/ijms20143499.

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Adenosine receptors are a family of G protein-coupled receptors with increased attention as drug targets on different indications. We investigate the thermodynamics of ligand binding to the A3 adenosine receptor subtype, focusing on a recently reported series of diarylacetamidopyridine inhibitors via molecular dynamics simulations. With a combined approach of thermodynamic integration and one-step perturbation, we characterize the impact of the charge distribution in a central heteroaromatic ring on the binding affinity prediction. Standard charge distributions according to the GROMOS force field yield values in good agreement with the experimental data and previous free energy calculations. Subsequently, we examine the thermodynamics of inhibitor binding in terms of the energetic and entropic contributions. The highest entropy penalties are found for inhibitors with methoxy substituents in meta position of the aryl groups. This bulky group restricts rotation of aromatic rings attached to the pyrimidine core which leads to two distinct poses of the ligand. Our predictions support the previously proposed binding pose for the o-methoxy ligand, yielding in this case a very good correlation with the experimentally measured affinities with deviations below 4 kJ/mol.
6

Lanez, Touhami, and Meriem Henni. "Spectrophotometrical study of antioxidant standards interacting with 2,2-diphenyl-1-picrylhydrazyl radical." Chemistry & Chemical Technology 10, no. 3 (September 15, 2016): 255–58. http://dx.doi.org/10.23939/chcht10.03.255.

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This work aims to study the interaction of four well known antioxidant standards with 2,2-diphenyl-1-picrylhydrazyl radical (DPPH•) using spectrophotometric assays. The binding parameters like binding constant and binding free energy of the free and DPPH• bound forms were determined. The determination is based upon the decrease in absorbance of the electronic absorption spectrum of an acetonitrile solution of DPPH• in the presence of gradually increasing amount of antioxidant standards.
7

Kaur, Jasmeet, Harsh Kumar, and Pamita Awasthi. "An Investigation on Drug Binding Ability of Cationic Surfactant CTAB." ECS Transactions 107, no. 1 (April 24, 2022): 5293–303. http://dx.doi.org/10.1149/10701.5293ecst.

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Taking in consideration the application of surfactants in drug delivery, the interactions of cationic surfactant cetyltrimethylammonium bromide (CTAB) with drug Betaine Hydrochloride have been scrutinized. The micellization behaviour of surfactant is investigated at three different temperatures (298.15, 308.15, and 318.15)K in presence of various concentrations (0.10, 0.25, and 0.50) mmolkg-1 of drug Betaine hydrochloride via conductivity measurements The critical micelle concentration (CMC) attained though conductometric measurements has been utilized to obtain different thermodynamic parameters of micellization i.e. standard free energy of micellization (ΔG0 m), standard enthalpy of micellization (ΔH0 m), and standard entropy of micellization (ΔS0 m).
8

La, Van N. T., and David D. L. Minh. "Bayesian Regression Quantifies Uncertainty of Binding Parameters from Isothermal Titration Calorimetry More Accurately Than Error Propagation." International Journal of Molecular Sciences 24, no. 20 (October 11, 2023): 15074. http://dx.doi.org/10.3390/ijms242015074.

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We compare several different methods to quantify the uncertainty of binding parameters estimated from isothermal titration calorimetry data: the asymptotic standard error from maximum likelihood estimation, error propagation based on a first-order Taylor series expansion, and the Bayesian credible interval. When the methods are applied to simulated experiments and to measurements of Mg(II) binding to EDTA, the asymptotic standard error underestimates the uncertainty in the free energy and enthalpy of binding. Error propagation overestimates the uncertainty for both quantities, except in the simulations, where it underestimates the uncertainty of enthalpy for confidence intervals less than 70%. In both datasets, Bayesian credible intervals are much closer to observed confidence intervals.
9

udhe, Prashik B. D., and Hardik G. Bhatt. "Molecular docking studies of some novel 2 & 3-(4-aminobenzamido) benzoic acid derivatives as DHFR inhibitors for treatment of tuberculosis." International Journal of PharmTech Research 13, no. 3 (2020): 262–71. http://dx.doi.org/10.20902/ijptr.2019.130317.

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A Novel series 2 & 3-(4-aminobenzamido) benzoic acid derivatives were designed virtually considering the basic pharmacophore N-(3,5-bis (trifluoromethyl) phenyl)- 5-chloro-2-hydroxybenzamide.The energy minimized conformers of each molecule was generated and docked with M. tuberculosis DHFR enzyme with PDB id: 1DF7 using Autodock 4.2.5.1. Most of the molecules have shown significant binding interaction with the receptor. Among the test compounds, DX-35, DY-24, DX-18, DX-31 & DY-23 have shown highest free energy of binding -9.51 to -8.92 kcal/mol and also the very good estimated inhibitory constant in a range of 0.11 to 0.29 Ki μM, which is comparable to that of the reference standard methotrexate and the standard Anti-Tb drug Ciprofloxacin.
10

Bertazzo, Martina, Dorothea Gobbo, Sergio Decherchi, and Andrea Cavalli. "Machine Learning and Enhanced Sampling Simulations for Computing the Potential of Mean Force and Standard Binding Free Energy." Journal of Chemical Theory and Computation 17, no. 8 (July 14, 2021): 5287–300. http://dx.doi.org/10.1021/acs.jctc.1c00177.

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Journal articles Dissertations / Theses Books

Dissertations / Theses on the topic "Standard Binding Free Energy":

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.

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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 liaison
During 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.

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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.

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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/.

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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.

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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.

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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.

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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.

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Chemistry
Ph.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&gt. "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.

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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.

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Books on the topic "Standard Binding Free Energy":

1

Canada. The Canada-U.S. free trade agreement. Ottawa, Ont: International Trade Communications Group, 1988.

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Canada. The Canada-U.S. Free Trade Agreement. Ottawa: Department of ExternalAffairs, 1988.

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Canada. The Canada-U.S. free trade agreement : [text, explanatory notes]. Ottawa: External Affairs Canada, 1987.

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Blaha, Stephen. The origin of the standard model: The genesis of four quark and lepton species, parity violation, the electro weak sector, color SU(3), three visible generations of fermions, and one generation of dark matter with dark energy ; Quantum theory of the third kind : a new type of divergence-free quantum field theory supporting a unified standard model of elementary particles and quantum gravity based on a new method in the calculus of variations. Auburn, NH: Pingree-Hill Publishing, 2006.

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Canada. North American Free Trade Agreement between the government of the United States of America, the government of Canada, and the government of the United Mexican States. [Washington, D.C: U.S. G.P.O.], 1992.

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Canada. North American Free Trade Agreement between the government of the United States of America, the government of Canada, and the government of the United Mexican States. Washington, DC: [Executive Office of the President], 1993.

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E, Vance Dennis, and Vance Jean E, eds. Biochemistry of lipids, lipoproteins, and membranes. Amsterdam: Elsevier, 1991.

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Canada. Pacific Salmon Treaty: Including: Yukon River agreement, revisions to December, 2002, memorandum of understanding (1985), exchange of notes--1985, 1999 & 2002. [Vancouver, B.C.?]: Pacific Salmon Commission, 2004.

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Canada. Agreement amending treaty with Canada concerning Pacific Coast albacore tuna vessels and port privileges: Message from the President of the United States transmitting agreement amending treaty between the government of the United States of America and the government of Canada on Pacific Coast albacore tuna vessels and port privileges done at Washington, D.C., May 26, 1981 (The "Treaty"), effected by an exchange of diplomatic notes at Washington on July 17, 2002, and August 13, 2002 (The "Agreement"). Washington: U.S. G.P.O., 2003.

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Canada. St. Lawrence Seaway: Tariff of tolls : agreement between the United States of America and Canada, amending the agreement of March 9, 1959, as amended and supplemented, effected by exchange of notes, signed at Washington June 10 and July 12, 1994, and exchange of notes, signed at Washington August 9 and October 18, 1995. Washington, D.C: Dept. of State, 2000.

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Book chapters on the topic "Standard Binding Free Energy":

1

McCammon, J. Andrew. "Free Energy and Binding Selectivity." In Computational Approaches in Supramolecular Chemistry, 515–17. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-1058-7_33.

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Chattoraj, D. K., L. N. Ghosh, and P. K. Mahapatra. "Standard Free Energy of Adsorption at Liquid Interfaces." In Surfactants in Solution, 277–92. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4615-3836-3_19.

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Wang, Lingle, Jennifer Chambers, and Robert Abel. "Protein–Ligand Binding Free Energy Calculations with FEP+." In Methods in Molecular Biology, 201–32. New York, NY: Springer New York, 2019. http://dx.doi.org/10.1007/978-1-4939-9608-7_9.

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Reif, Maria M., and Martin Zacharias. "Computational Tools for Accurate Binding Free-Energy Prediction." In Methods in Molecular Biology, 255–92. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1767-0_12.

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Jespers, Willem, Johan Åqvist, and Hugo Gutiérrez-de-Terán. "Free Energy Calculations for Protein–Ligand Binding Prediction." In Methods in Molecular Biology, 203–26. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1209-5_12.

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Eisenman, George, Osvaldo Alvarez, and Johan Aqvist. "Free Energy Perturbation Simulations of Cation Binding to Valinomycin." In The Pedersen Memorial Issue, 23–53. Dordrecht: Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-011-2532-1_3.

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Wong, Thomas K. F., and S. M. Yiu. "Prediction of Minimum Free Energy Structure for Simple Non-standard Pseudoknot." In Biomedical Engineering Systems and Technologies, 345–55. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-18472-7_27.

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Aldeghi, Matteo, Joseph P. Bluck, and Philip C. Biggin. "Absolute Alchemical Free Energy Calculations for Ligand Binding: A Beginner’s Guide." In Methods in Molecular Biology, 199–232. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4939-7756-7_11.

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Reddy, M. Rami, Mark D. Erion, and Atul Agarwal. "Free Energy Calculations: Use and Limitations in Predicting Ligand Binding Affinities." In Reviews in Computational Chemistry, 217–304. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2007. http://dx.doi.org/10.1002/9780470125939.ch4.

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Mandal, Tanumoy, Andreas Ekstedt, Rikard Enberg, Gunnar Ingelman, and Johan Löfgren. "Exclusion Limits on Minimal Anomaly Free $$\mathrm {U}(1)$$ Extensions of the Standard Model." In XXII DAE High Energy Physics Symposium, 243–46. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73171-1_55.

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Conference papers on the topic "Standard Binding Free Energy":

1

Chen, Kok Hao, and Jong Hyun Choi. "DNA Oligonucleotide-Templated Nanocrystals: Synthesis and Novel Label-Free Protein Detection." In ASME 2009 International Mechanical Engineering Congress and Exposition. ASMEDC, 2009. http://dx.doi.org/10.1115/imece2009-11958.

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Abstract:
Semiconductor and magnetic nanoparticles hold unique optical and magnetic properties, and great promise for bio-imaging and therapeutic applications. As part of their stable synthesis, the nanocrystal surfaces are usually capped by long chain organic moieties such as trioctylphosphine oxide. This capping serves two purposes: it saturates dangling bonds at the exposed crystalline lattice, and it prevents irreversible aggregation by stabilizing the colloid through entropic repulsion. These nanocrystals can be rendered water-soluble by either ligand exchange or overcoating, which hampers their widespread use in biological imaging and biomedical therapeutics. Here, we report a novel scheme of synthesizing fluorescent PbS and magnetic Fe3O4 nanoparticles using DNA oligonucleotides. Our method of PbS synthesis includes addition of Na2S to the mixture solution of DNA sequence and Pb acetate (at a fixed molar ratio of DNA/S2−/Pb2+ of 1:2:4) in a standard TAE buffer at room temperature in the open air. In the case of Fe3O4 particle synthesis, ferric and ferrous chloride were mixed with DNA in DI water at a molar ratio of DNA/Fe2+/Fe3+ = 1:4:8 and the particles were formed via reductive precipitation, induced by increasing pH to ∼11 with addition of ammonium hydroxide. These nanocrystals are highly stable and water-soluble immediately after the synthesis, due to DNA termination. We examined the surface chemistry between oligonucleotides and nanocrystals using FTIR spectroscopy, and found that the different chemical moieties of nucleobases passivate the particle surface. Strong coordination of primary amine and carbonyl groups provides the chemical and colloidal stabilities, leading to high particle yields (Figure 1). The resulting PbS nanocrystals have a distribution of 3–6 nm in diameter, while a broader size distribution is observed with Fe3O4 nanoparticles as shown in Figure 1b and c, respectively. A similar observation was reported with the pH change-induced Fe3O4 particles of a bimodal size distribution where superparamagnetic and ferrimagnetic magnetites co-exist. In spite of the differences, FTIR measurements suggest that the chemical nature of the oligonucleotide stabilization in this case is identical to the PbS system. As a particular application, we demonstrate that aptamer-capped PbS QD can detect a target protein based on selective charge transfer, since the oligonucleotide-templated synthesis can also serve the additional purpose of providing selective binding to a molecular target. Here, we use thrombin and a thrombin-binding aptamer as a model system. These QD have diameters of 3∼6 nm and fluoresce around 1050 nm. We find that a DNA aptamer can passivate near IR fluorescent PbS nanocrystals, rendering them water-soluble and stable against aggregation, and retain the secondary conformation needed to selectively bind to its target, thrombin, as shown in Figure 2. Importantly, we find that when the aptamer-functionalized nanoparticles binds to its target (only the target), there is a highly systematic and selective quenching of the PL, even in high concentrations of interfering proteins as shown in Figure 3a and b. Thrombin is detected within one minute with a detection limit of ∼1 nM. This PL quenching is attributed to charge transfer from functional groups on the protein to the nanocrystals. A charge transfer can suppress optical transition mechanisms as we observe a significant decrease in QD absorption with target addition (Figure 3c). Here, we rule out other possibilities including Forster resonance energy transfer (FRET) and particle aggregation, because thrombin absorb only in the UV, and we did not observe any significant change in the diffusion coefficient of the particles with the target analyte, respectively. The charge transfer-induced photobleaching of QD and carbon nanotubes was observed with amine groups, Ru-based complexes, and azobenzene compounds. This selective detection of an unlabeled protein is distinct from previously reported schemes utilizing electrochemistry, absorption, and FRET. In this scheme, the target detection by a unique, direct PL transduction is observed even in the presence of high background concentrations of interfering negatively or positively charged proteins. This mechanism is the first to selectively modulate the QD PL directly, enabling new types of label free assays and detection schemes. This direct optical transduction is possible due to oligonucleotidetemplated surface passivation and molecular recognition. This chemistry may lead to more nanoparticle-based optical and magnetic probes that can be activated in a highly chemoselective manner.
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Wall, Michael E. "Ligand Binding, Protein Fluctuations, And Allosteric Free Energy." In FROM PHYSICS TO BIOLOGY: The Interface between Experiment and Computation - BIFI 2006 II International Congress. AIP, 2006. http://dx.doi.org/10.1063/1.2345620.

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Yue Shi, Dian Jiao, M. J. Schnieders, and Pengyu Ren. "Trypsin-ligand binding free energy calculation with AMOEBA." In 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2009. http://dx.doi.org/10.1109/iembs.2009.5335108.

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Dakka, Jumana, Kristof Farkas-Pall, Matteo Turilli, David W. Wright, Peter V. Coveney, and Shantenu Jha. "Concurrent and Adaptive Extreme Scale Binding Free Energy Calculations." In 2018 IEEE 14th International Conference on e-Science (e-Science). IEEE, 2018. http://dx.doi.org/10.1109/escience.2018.00034.

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Kudrawiec, R. "The Free Exciton Binding Energy in a Strained GaN0.02As0.98 Layer." In PHYSICS OF SEMICONDUCTORS: 27th International Conference on the Physics of Semiconductors - ICPS-27. AIP, 2005. http://dx.doi.org/10.1063/1.1994105.

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Takamatsu, Yuichiro. "Binding Free Energy Calculation and Structural Analysis for Antigen-Antibody Complex." In FLOW DYNAMICS: The Second International Conference on Flow Dynamics. AIP, 2006. http://dx.doi.org/10.1063/1.2204566.

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Yang, Kun, Xicheng Wang, Jane W. Z. Lu, Andrew Y. T. Leung, Vai Pan Iu, and Kai Meng Mok. "A Prediction Method of Binding Free Energy of Protein and Ligand." In PROCEEDINGS OF THE 2ND INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL MECHANICS AND THE 12TH INTERNATIONAL CONFERENCE ON THE ENHANCEMENT AND PROMOTION OF COMPUTATIONAL METHODS IN ENGINEERING AND SCIENCE. AIP, 2010. http://dx.doi.org/10.1063/1.3452207.

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"BINDING FREE ENERGY CALCULATION VIA MOLECULAR DYNAMICS SIMULATIONS FOR A miRNA:mRNA INTERACTION." In International Conference on Bioinformatics Models, Methods and Algorithms. SciTePress - Science and and Technology Publications, 2011. http://dx.doi.org/10.5220/0003167703180321.

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Cain, Sahar, Ali Risheh, and Negin Forouzesh. "Calculation of Protein-Ligand Binding Free Energy Using a Physics-Guided Neural Network." In 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2021. http://dx.doi.org/10.1109/bibm52615.2021.9669867.

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Forouzesh, Negin. "Binding Free Energy of the Novel Coronavirus Spike Protein and the Human ACE2 Receptor." In BCB '20: 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3388440.3414712.

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Reports on the topic "Standard Binding Free Energy":

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Midak, Lilia Ya, Ivan V. Kravets, Olga V. Kuzyshyn, Jurij D. Pahomov, Victor M. Lutsyshyn, and Aleksandr D. Uchitel. Augmented reality technology within studying natural subjects in primary school. [б. в.], February 2020. http://dx.doi.org/10.31812/123456789/3746.

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The purpose of the research is creation of mobile app (supported by Android) for visualization of chemical structure of water and to display video- data of laboratory experiments that can be used by the teacher and pupils for an effective background for learning natural cycle subjects and performance of laboratory experiments in the elementary school using lapbook. As a result of work, aimed at visualizing the education material, a free mobile app LiCo.STEM was developed; it can be downloaded from the overall-available resource Google Play Market. Representation of the developed video materials on the mobile gadgets is conducted by “binding” them to individual images- “markers” for every laboratory experiment. Applying such technologies gives an opportunity to establish educational activity, based on interference of adults with children, oriented on interests and abilities of each kid, development of curiosity, cognitive motivation and educational energy; development of imagination, creative initiative, including the speech, ability to chose the materials, types of work, participants of the common activity, promotion of conditions for parents participate in the common study activity.
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Oliynyk, Kateryna, and Matteo Ciantia. Application of a finite deformation multiplicative plasticity model with non-local hardening to the simulation of CPTu tests in a structured soil. University of Dundee, December 2021. http://dx.doi.org/10.20933/100001230.

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In this paper an isotropic hardening elastoplastic constitutive model for structured soils is applied to the simulation of a standard CPTu test in a saturated soft structured clay. To allow for the extreme deformations experienced by the soil during the penetration process, the model is formulated in a fully geometric non-linear setting, based on: i) the multiplicative decomposition of the deformation gradient into an elastic and a plastic part; and, ii) on the existence of a free energy function to define the elastic behaviour of the soil. The model is equipped with two bonding-related internal variables which provide a macroscopic description of the effects of clay structure. Suitable hardening laws are employed to describe the structure degradation associated to plastic deformations. The strain-softening associated to bond degradation usually leads to strain localization and consequent formation of shear bands, whose thickness is dependent on the characteristics of the microstructure (e.g, the average grain size). Standard local constitutive models are incapable of correctly capturing this phenomenon due to the lack of an internal length scale. To overcome this limitation, the model is framed using a non-local approach by adopting volume averaged values for the internal state variables. The size of the neighbourhood over which the averaging is performed (characteristic length) is a material constant related to the microstructure which controls the shear band thickness. This extension of the model has proven effective in regularizing the pathological mesh dependence of classical finite element solutions in the post-localization regime. The results of numerical simulations, conducted for different soil permeabilities and bond strengths, show that the model captures the development of plastic deformations induced by the advancement of the cone tip; the destructuration of the clay associated with such plastic deformations; the space and time evolution of pore water pressure as the cone tip advances. The possibility of modelling the CPTu tests in a rational and computationally efficient way opens a promising new perspective for their interpretation in geotechnical site investigations.
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Lokke, Arnkjell, and Anil Chopra. Direct-Finite-Element Method for Nonlinear Earthquake Analysis of Concrete Dams Including Dam–Water–Foundation Rock Interaction. Pacific Earthquake Engineering Research Center, University of California, Berkeley, CA, March 2019. http://dx.doi.org/10.55461/crjy2161.

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Evaluating the seismic performance of concrete dams requires nonlinear dynamic analysis of two- or three-dimensional dam–water–foundation rock systems that include all the factors known to be significant in the earthquake response of dams. Such analyses are greatly complicated by interaction between the structure, the impounded reservoir and the deformable foundation rock that supports it, and the fact that the fluid and foundation domains extend to large distances. Presented in this report is the development of a direct finite-element (FE) method for nonlinear earthquake analysis of two- and three-dimensional dam–water–foundation rock systems. The analysis procedure applies standard viscous-damper absorbing boundaries to model the semi-unbounded fluid and foundation domains, and specifies at these boundaries effective earthquake forces determined from a ground motion defined at a control point on the ground surface. This report is organized in three parts, with a common notation list, references, and appendices at the end of the report. Part I develops the direct FE method for 2D dam–water–foundation rock systems. The underlying analytical framework of treating dam–water–foundation rock interaction as a scattering problem, wherein the dam perturbs an assumed "free-field" state of the system, is presented, and by applying these concepts to a bounded FE model with viscous-damper boundaries to truncate the semi-unbounded domains, the analysis procedure is derived. Step-by-step procedures for computing effective earthquake forces from analysis of two 1D free-field systems are presented, and the procedure is validated by computing frequency response functions and transient response of an idealized dam–water–foundation rock system and comparing against independent benchmark results. This direct FE method is generalized to 3D systems in Part II of this report. While the fundamental concepts of treating interaction as a scattering problem are similar for 2D and 3D systems, the derivation and implementation of the method for 3D systems is much more involved. Effective earthquake forces must now be computed by analyzing a set of 1D and 2D systems derived from the boundaries of the free-field systems, which requires extensive book-keeping and data transfer for large 3D models. To reduce these requirements and facilitate implementation of the direct FE method for 3D systems, convenient simplifications of the procedure are proposed and their effectiveness demonstrated. Part III of the report proposes to use the direct FE method for conducting the large number of nonlinear response history analyses (RHAs) required for performance-based earthquake engineering (PBEE) of concrete dams, and discusses practical modeling considerations for two of the most influential aspects of these analyses: nonlinear mechanisms and energy dissipation (damping). The findings have broad implications for modeling of energy dissipation and calibration of damping values for concrete dam analyses. At the end of Part III, the direct FE method is implemented with a commercial FE program and used to compute the nonlinear response of an actual arch dam. These nonlinear results, although limited in their scope, demonstrate the capabilities and effectiveness of the direct FE method to compute the types of nonlinear engineering response quantities required for PBEE of concrete dams.

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