Статті в журналах: "Proteins Molecular Dynamics Computational Biophysics"

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Liang, Zhongjie, Gennady M. Verkhivker, and Guang Hu. "Integration of network models and evolutionary analysis into high-throughput modeling of protein dynamics and allosteric regulation: theory, tools and applications." Briefings in Bioinformatics 21, no. 3 (March 21, 2019): 815–35. http://dx.doi.org/10.1093/bib/bbz029.

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Abstract Proteins are dynamical entities that undergo a plethora of conformational changes, accomplishing their biological functions. Molecular dynamics simulation and normal mode analysis methods have become the gold standard for studying protein dynamics, analyzing molecular mechanism and allosteric regulation of biological systems. The enormous amount of the ensemble-based experimental and computational data on protein structure and dynamics has presented a major challenge for the high-throughput modeling of protein regulation and molecular mechanisms. In parallel, bioinformatics and systems biology approaches including genomic analysis, coevolution and network-based modeling have provided an array of powerful tools that complemented and enriched biophysical insights by enabling high-throughput analysis of biological data and dissection of global molecular signatures underlying mechanisms of protein function and interactions in the cellular environment. These developments have provided a powerful interdisciplinary framework for quantifying the relationships between protein dynamics and allosteric regulation, allowing for high-throughput modeling and engineering of molecular mechanisms. Here, we review fundamental advances in protein dynamics, network theory and coevolutionary analysis that have provided foundation for rapidly growing computational tools for modeling of allosteric regulation. We discuss recent developments in these interdisciplinary areas bridging computational biophysics and network biology, focusing on promising applications in allosteric regulations, including the investigation of allosteric communication pathways, protein–DNA/RNA interactions and disease mutations in genomic medicine. We conclude by formulating and discussing future directions and potential challenges facing quantitative computational investigations of allosteric regulatory mechanisms in protein systems.

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Yeggoni, Daniel Pushparaju, Aparna Rachamallu та Rajagopal Subramanyam. "A comparative binding mechanism between human serum albumin and α-1-acid glycoprotein with corilagin: biophysical and computational approach". RSC Advances 6, № 46 (2016): 40225–37. http://dx.doi.org/10.1039/c6ra06837e.

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The interaction between corilagin and serum proteins was studied by biophysical and molecular dynamics techniques which in turn provides valuable information about the interaction of phytochemical corilagin with serum proteins.

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Bardhan, Jaydeep P. "Gradient models in molecular biophysics: progress, challenges, opportunities." Journal of the Mechanical Behavior of Materials 22, no. 5-6 (December 1, 2013): 169–84. http://dx.doi.org/10.1515/jmbm-2013-0024.

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AbstractIn the interest of developing a bridge between researchers modeling materials and those modeling biological molecules, we survey recent progress in developing nonlocal-dielectric continuum models for studying the behavior of proteins and nucleic acids. As in other areas of science, continuum models are essential tools when atomistic simulations (e.g., molecular dynamics) are too expensive. Because biological molecules are essentially all nanoscale systems, the standard continuum model, involving local dielectric response, has basically always been dubious at best. The advanced continuum theories discussed here aim to remedy these shortcomings by adding nonlocal dielectric response. We begin by describing the central role of electrostatic interactions in biology at the molecular scale, and motivate the development of computationally tractable continuum models using applications in science and engineering. For context, we highlight some of the most important challenges that remain, and survey the diverse theoretical formalisms for their treatment, highlighting the rigorous statistical mechanics that support the use and improvement of continuum models. We then address the development and implementation of nonlocal dielectric models, an approach pioneered by Dogonadze, Kornyshev, and their collaborators almost 40 years ago. The simplest of these models is just a scalar form of gradient elasticity, and here we use ideas from gradient-based modeling to extend the electrostatic model to include additional length scales. The review concludes with a discussion of open questions for model development, highlighting the many opportunities for the materials community to leverage its physical, mathematical, and computational expertise to help solve one of the most challenging questions in molecular biology and biophysics.

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Ren, Pengyu, Jaehun Chun, Dennis G. Thomas, Michael J. Schnieders, Marcelo Marucho, Jiajing Zhang, and Nathan A. Baker. "Biomolecular electrostatics and solvation: a computational perspective." Quarterly Reviews of Biophysics 45, no. 4 (November 2012): 427–91. http://dx.doi.org/10.1017/s003358351200011x.

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AbstractAn understanding of molecular interactions is essential for insight into biological systems at the molecular scale. Among the various components of molecular interactions, electrostatics are of special importance because of their long-range nature and their influence on polar or charged molecules, including water, aqueous ions, proteins, nucleic acids, carbohydrates, and membrane lipids. In particular, robust models of electrostatic interactions are essential for understanding the solvation properties of biomolecules and the effects of solvation upon biomolecular folding, binding, enzyme catalysis, and dynamics. Electrostatics, therefore, are of central importance to understanding biomolecular structure and modeling interactions within and among biological molecules. This review discusses the solvation of biomolecules with a computational biophysics view toward describing the phenomenon. While our main focus lies on the computational aspect of the models, we provide an overview of the basic elements of biomolecular solvation (e.g. solvent structure, polarization, ion binding, and non-polar behavior) in order to provide a background to understand the different types of solvation models.

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Molinski, Steven V., Zoltán Bozóky, Surtaj H. Iram, and Saumel Ahmadi. "Biophysical Approaches Facilitate Computational Drug Discovery for ATP-Binding Cassette Proteins." International Journal of Medicinal Chemistry 2017 (March 19, 2017): 1–9. http://dx.doi.org/10.1155/2017/1529402.

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Although membrane proteins represent most therapeutically relevant drug targets, the availability of atomic resolution structures for this class of proteins has been limited. Structural characterization has been hampered by the biophysical nature of these polytopic transporters, receptors, and channels, and recent innovations to in vitro techniques aim to mitigate these challenges. One such class of membrane proteins, the ATP-binding cassette (ABC) superfamily, are broadly expressed throughout the human body, required for normal physiology and disease-causing when mutated, yet lacks sufficient structural representation in the Protein Data Bank. However, recent improvements to biophysical techniques (e.g., cryo-electron microscopy) have allowed for previously “hard-to-study” ABC proteins to be characterized at high resolution, providing insight into molecular mechanisms-of-action as well as revealing novel druggable sites for therapy design. These new advances provide ample opportunity for computational methods (e.g., virtual screening, molecular dynamics simulations, and structure-based drug design) to catalyze the discovery of novel small molecule therapeutics that can be easily translated from computer to bench and subsequently to the patient’s bedside. In this review, we explore the utility of recent advances in biophysical methods coupled with well-established in silico techniques towards drug development for diseases caused by dysfunctional ABC proteins.

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Moffett, Alexander S., and Diwakar Shukla. "Using molecular simulation to explore the nanoscale dynamics of the plant kinome." Biochemical Journal 475, no. 5 (March 9, 2018): 905–21. http://dx.doi.org/10.1042/bcj20170299.

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Eukaryotic protein kinases (PKs) are a large family of proteins critical for cellular response to external signals, acting as molecular switches. PKs propagate biochemical signals by catalyzing phosphorylation of other proteins, including other PKs, which can undergo conformational changes upon phosphorylation and catalyze further phosphorylations. Although PKs have been studied thoroughly across the domains of life, the structures of these proteins are sparsely understood in numerous groups of organisms, including plants. In addition to efforts towards determining crystal structures of PKs, research on human PKs has incorporated molecular dynamics (MD) simulations to study the conformational dynamics underlying the switching of PK function. This approach of experimental structural biology coupled with computational biophysics has led to improved understanding of how PKs become catalytically active and why mutations cause pathological PK behavior, at spatial and temporal resolutions inaccessible to current experimental methods alone. In this review, we argue for the value of applying MD simulation to plant PKs. We review the basics of MD simulation methodology, the successes achieved through MD simulation in animal PKs, and current work on plant PKs using MD simulation. We conclude with a discussion of the future of MD simulations and plant PKs, arguing for the importance of molecular simulation in the future of plant PK research.

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Ramos, Javier, Juan Francisco Vega, Victor Cruz, Eduardo Sanchez-Sanchez, Javier Cortes, and Javier Martinez-Salazar. "Hydrodynamic and Electrophoretic Properties of Trastuzumab/HER2 Extracellular Domain Complexes as Revealed by Experimental Techniques and Computational Simulations." International Journal of Molecular Sciences 20, no. 5 (March 1, 2019): 1076. http://dx.doi.org/10.3390/ijms20051076.

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The combination of hydrodynamic and electrophoretic experiments and computer simulations is a powerful approach to study the interaction between proteins. In this work, we present hydrodynamic and electrophoretic experiments in an aqueous solution along with molecular dynamics and hydrodynamic modeling to monitor and compute biophysical properties of the interactions between the extracellular domain of the HER2 protein (eHER2) and the monoclonal antibody trastuzumab (TZM). The importance of this system relies on the fact that the overexpression of HER2 protein is related with the poor prognosis breast cancers (HER2++ positives), while the TZM is a monoclonal antibody for the treatment of this cancer. We have found and characterized two different complexes between the TZM and eHER2 proteins (1:1 and 1:2 TZM:eHER2 complexes). The conformational features of these complexes regulate their hydrodynamic and electrostatic properties. Thus, the results indicate a high degree of molecular flexibility in the systems that ultimately leads to higher values of the intrinsic viscosity, as well as lower values of diffusion coefficient than those expected for simple globular proteins. A highly asymmetric charge distribution is detected for the monovalent complex (1:1 complex), which has strong implications in correlations between the experimental electrophoretic mobility and the modeled net charge. In order to understand the dynamics of these systems and the role of the specific domains involved, it is essential to find biophysical correlations between dynamics, macroscopic transport and electrostatic properties. The results should be of general interest for researchers working in this area.

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Oldham, William M., and Heidi E. Hamm. "Structural basis of function in heterotrimeric G proteins." Quarterly Reviews of Biophysics 39, no. 2 (May 2006): 117–66. http://dx.doi.org/10.1017/s0033583506004306.

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1. Introduction 22. Heterotrimeric G-protein structure 32.1. G-protein α subunit 32.2. G-protein βγ dimer 82.3. Unique role of Gβ5 in complexes with RGS proteins 92.4. Heterotrimer structure 102.5. Lipid modifications direct membrane association 113. Receptor–G protein complex 113.1. Low affinity interactions between inactive receptors (R) and G proteins 113.2. Receptor activation exposes the high-affinity G-protein binding site 123.3. Receptor–G protein interface 143.4. Structural determinants of receptor–G protein specificity 153.5. Models of the receptor–G protein complex 173.6. Sequential interactions may form the receptor–G protein complex 194. Molecular basis for G-protein activation 194.1. Potential mechanisms of receptor-catalyzed GDP release 204.2. GTP-mediated alteration of the receptor–G protein complex 235. Activation of downstream effector proteins 245.1. Gα interactions with effectors 245.2. Gβγ interactions with effectors and regulatory proteins 266. G-protein inactivation 286.1. Intrinsic GTPase-activity of Gα 286.2. GTPase-activating proteins 307. Novel regulation of G-protein signaling 318. New approaches to study G-protein dynamics 328.1. Nuclear magnetic resonance spectroscopy 328.2. Site-directed labeling techniques 338.3. Mapping allosteric connectivity with computational approaches 348.4. Studies of G-protein function in living cells 369. Conclusions 3710. References 38Heterotrimeric guanine-nucleotide-binding proteins (G proteins) act as molecular switches in signaling pathways by coupling the activation of heptahelical receptors at the cell surface to intracellular responses. In the resting state, the G-protein α subunit (Gα) binds GDP and Gβγ. Receptors activate G proteins by catalyzing GTP for GDP exchange on Gα, leading to a structural change in the Gα(GTP) and Gβγ subunits that allows the activation of a variety of downstream effector proteins. The G protein returns to the resting conformation following GTP hydrolysis and subunit re-association. As the G-protein cycle progresses, the Gα subunit traverses through a series of conformational changes. Crystallographic studies of G proteins in many of these conformations have provided substantial insight into the structures of these proteins, the GTP-induced structural changes in Gα, how these changes may lead to subunit dissociation and allow Gα and Gβγ to activate effector proteins, as well as the mechanism of GTP hydrolysis. However, relatively little is known about the receptor–G protein complex and how this interaction leads to GDP release from Gα. This article reviews the structural determinants of the function of heterotrimeric G proteins in mammalian systems at each point in the G-protein cycle with special emphasis on the mechanism of receptor-mediated G-protein activation. The receptor–G protein complex has proven to be a difficult target for crystallography, and several biophysical and computational approaches are discussed that complement the currently available structural information to improve models of this interaction. Additionally, these approaches enable the study of G-protein dynamics in solution, which is becoming an increasingly appreciated component of all aspects of G-protein signaling.

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Gauthier, Louis, Rémicia Di Franco, and Adrian W. R. Serohijos. "SodaPop: a forward simulation suite for the evolutionary dynamics of asexual populations on protein fitness landscapes." Bioinformatics 35, no. 20 (March 14, 2019): 4053–62. http://dx.doi.org/10.1093/bioinformatics/btz175.

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Abstract Motivation Protein evolution is determined by forces at multiple levels of biological organization. Random mutations have an immediate effect on the biophysical properties, structure and function of proteins. These same mutations also affect the fitness of the organism. However, the evolutionary fate of mutations, whether they succeed to fixation or are purged, also depends on population size and dynamics. There is an emerging interest, both theoretically and experimentally, to integrate these two factors in protein evolution. Although there are several tools available for simulating protein evolution, most of them focus on either the biophysical or the population-level determinants, but not both. Hence, there is a need for a publicly available computational tool to explore both the effects of protein biophysics and population dynamics on protein evolution. Results To address this need, we developed SodaPop, a computational suite to simulate protein evolution in the context of the population dynamics of asexual populations. SodaPop accepts as input several fitness landscapes based on protein biochemistry or other user-defined fitness functions. The user can also provide as input experimental fitness landscapes derived from deep mutational scanning approaches or theoretical landscapes derived from physical force field estimates. Here, we demonstrate the broad utility of SodaPop with different applications describing the interplay of selection for protein properties and population dynamics. SodaPop is designed such that population geneticists can explore the influence of protein biochemistry on patterns of genetic variation, and that biochemists and biophysicists can explore the role of population size and demography on protein evolution. Availability and implementation Source code and binaries are freely available at https://github.com/louisgt/SodaPop under the GNU GPLv3 license. The software is implemented in C++ and supported on Linux, Mac OS/X and Windows. Supplementary information Supplementary data are available at Bioinformatics online.

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Tang, Wai Shing, Gabriel Monteiro da Silva, Henry Kirveslahti, Erin Skeens, Bibo Feng, Timothy Sudijono, Kevin K. Yang, Sayan Mukherjee, Brenda Rubenstein, and Lorin Crawford. "A topological data analytic approach for discovering biophysical signatures in protein dynamics." PLOS Computational Biology 18, no. 5 (May 2, 2022): e1010045. http://dx.doi.org/10.1371/journal.pcbi.1010045.

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Identifying structural differences among proteins can be a non-trivial task. When contrasting ensembles of protein structures obtained from molecular dynamics simulations, biologically-relevant features can be easily overshadowed by spurious fluctuations. Here, we present SINATRA Pro, a computational pipeline designed to robustly identify topological differences between two sets of protein structures. Algorithmically, SINATRA Pro works by first taking in the 3D atomic coordinates for each protein snapshot and summarizing them according to their underlying topology. Statistically significant topological features are then projected back onto a user-selected representative protein structure, thus facilitating the visual identification of biophysical signatures of different protein ensembles. We assess the ability of SINATRA Pro to detect minute conformational changes in five independent protein systems of varying complexities. In all test cases, SINATRA Pro identifies known structural features that have been validated by previous experimental and computational studies, as well as novel features that are also likely to be biologically-relevant according to the literature. These results highlight SINATRA Pro as a promising method for facilitating the non-trivial task of pattern recognition in trajectories resulting from molecular dynamics simulations, with substantially increased resolution.

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Artali, Roberto, Antonio Del Pra, Elisabetta Foresti, Isidoro Giorgio Lesci, Norberto Roveri, and Piera Sabatino. "Adsorption of human serum albumin on the chrysotile surface: a molecular dynamics and spectroscopic investigation." Journal of The Royal Society Interface 5, no. 20 (July 11, 2007): 273–83. http://dx.doi.org/10.1098/rsif.2007.1137.

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The human serum albumin (HSA) secondary structure modifications induced by the chrysotile surface have been investigated via computational molecular dynamics (MD) and experimental infrared spectroscopy (FTIR) on synthetic chrysotile nanocrystals coated with different amount of HSA. MD simulations, conducted by placing various albumin subdomains close to the fixed chrysotile surface, show an initial adsorption phase, accompanied by local rearrangements of the albumin motifs in contact with the chrysotile layer. Next, large-scale rearrangements follow with consequent secondary structure modifications. Gaussian curve fitting of the FTIR spectra obtained for HSA-coated synthetic chrysotile nanocrystals has allowed the quantification of HSA structural modifications as a function of the amount of protein adsorbed. The experimental results support the atomistic computer simulations providing a realistic description of the adsorption of plasma proteins onto chrysotile and unravelling a key step in the understanding of asbestos toxicity.

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Miermans, Christiaan A., and Chase P. Broedersz. "Bacterial chromosome organization by collective dynamics of SMC condensins." Journal of The Royal Society Interface 15, no. 147 (October 2018): 20180495. http://dx.doi.org/10.1098/rsif.2018.0495.

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A prominent organizational feature of bacterial chromosomes was revealed by Hi-C experiments, indicating anomalously high contacts between the left and right chromosomal arms. These long-range contacts have been attributed to various nucleoid-associated proteins, including the ATPase Structural Maintenance of Chromosomes (SMC) condensin. Although the molecular structure of these ATPases has been mapped in detail, it still remains unclear by which physical mechanisms they collectively generate long-range chromosomal contacts. Here, we develop a computational model that captures the subtle interplay between molecular-scale activity of slip-links and large-scale chromosome organization. We first consider a scenario in which the ATPase activity of slip-links regulates their DNA-recruitment near the origin of replication, while the slip-link dynamics is assumed to be diffusive. We find that such diffusive slip-links can collectively organize the entire chromosome into a state with aligned arms, but not within physiological constraints. However, slip-links that include motor activity are far more effective at organizing the entire chromosome over all length-scales. The persistence of motor slip-links at physiological densities can generate large, nested loops and drive them into the bulk of the DNA. Finally, our model with motor slip-links can quantitatively account for the rapid arm–arm alignment of chromosomal arms observed in vivo .

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Soundarrajan, Dharsan K., Francisco J. Huizar, Ramezan Paravitorghabeh, Trent Robinett, and Jeremiah J. Zartman. "From spikes to intercellular waves: Tuning intercellular calcium signaling dynamics modulates organ size control." PLOS Computational Biology 17, no. 11 (November 1, 2021): e1009543. http://dx.doi.org/10.1371/journal.pcbi.1009543.

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Information flow within and between cells depends significantly on calcium (Ca2+) signaling dynamics. However, the biophysical mechanisms that govern emergent patterns of Ca2+ signaling dynamics at the organ level remain elusive. Recent experimental studies in developing Drosophila wing imaginal discs demonstrate the emergence of four distinct patterns of Ca2+ activity: Ca2+ spikes, intercellular Ca2+ transients, tissue-level Ca2+ waves, and a global “fluttering” state. Here, we used a combination of computational modeling and experimental approaches to identify two different populations of cells within tissues that are connected by gap junction proteins. We term these two subpopulations “initiator cells,” defined by elevated levels of Phospholipase C (PLC) activity, and “standby cells,” which exhibit baseline activity. We found that the type and strength of hormonal stimulation and extent of gap junctional communication jointly determine the predominate class of Ca2+ signaling activity. Further, single-cell Ca2+ spikes are stimulated by insulin, while intercellular Ca2+ waves depend on Gαq activity. Our computational model successfully reproduces how the dynamics of Ca2+ transients varies during organ growth. Phenotypic analysis of perturbations to Gαq and insulin signaling support an integrated model of cytoplasmic Ca2+ as a dynamic reporter of overall tissue growth. Further, we show that perturbations to Ca2+ signaling tune the final size of organs. This work provides a platform to further study how organ size regulation emerges from the crosstalk between biochemical growth signals and heterogeneous cell signaling states.

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Róg, Tomasz, Mykhailo Girych, and Alex Bunker. "Mechanistic Understanding from Molecular Dynamics in Pharmaceutical Research 2: Lipid Membrane in Drug Design." Pharmaceuticals 14, no. 10 (October 19, 2021): 1062. http://dx.doi.org/10.3390/ph14101062.

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We review the use of molecular dynamics (MD) simulation as a drug design tool in the context of the role that the lipid membrane can play in drug action, i.e., the interaction between candidate drug molecules and lipid membranes. In the standard “lock and key” paradigm, only the interaction between the drug and a specific active site of a specific protein is considered; the environment in which the drug acts is, from a biophysical perspective, far more complex than this. The possible mechanisms though which a drug can be designed to tinker with physiological processes are significantly broader than merely fitting to a single active site of a single protein. In this paper, we focus on the role of the lipid membrane, arguably the most important element outside the proteins themselves, as a case study. We discuss work that has been carried out, using MD simulation, concerning the transfection of drugs through membranes that act as biological barriers in the path of the drugs, the behavior of drug molecules within membranes, how their collective behavior can affect the structure and properties of the membrane and, finally, the role lipid membranes, to which the vast majority of drug target proteins are associated, can play in mediating the interaction between drug and target protein. This review paper is the second in a two-part series covering MD simulation as a tool in pharmaceutical research; both are designed as pedagogical review papers aimed at both pharmaceutical scientists interested in exploring how the tool of MD simulation can be applied to their research and computational scientists interested in exploring the possibility of a pharmaceutical context for their research.

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Gubieda, Alicia G., John R. Packer, Iolo Squires, Jack Martin, and Josana Rodriguez. "Going with the flow: insights from Caenorhabditis elegans zygote polarization." Philosophical Transactions of the Royal Society B: Biological Sciences 375, no. 1809 (August 24, 2020): 20190555. http://dx.doi.org/10.1098/rstb.2019.0555.

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Cell polarity is the asymmetric distribution of cellular components along a defined axis. Polarity relies on complex signalling networks between conserved patterning proteins, including the PAR ( par titioning defective) proteins, which become segregated in response to upstream symmetry breaking cues. Although the mechanisms that drive the asymmetric localization of these proteins are dependent upon cell type and context, in many cases the regulation of actomyosin cytoskeleton dynamics is central to the transport, recruitment and/or stabilization of these polarity effectors into defined subcellular domains. The transport or advection of PAR proteins by an actomyosin flow was first observed in the Caenorhabditis elegan s zygote more than a decade ago. Since then a multifaceted approach, using molecular methods, high-throughput screens, and biophysical and computational models, has revealed further aspects of this flow and how polarity regulators respond to and modulate it. Here, we review recent findings on the interplay between actomyosin flow and the PAR patterning networks in the polarization of the C. elegans zygote. We also discuss how these discoveries and developed methods are shaping our understanding of other flow-dependent polarizing systems. This article is part of a discussion meeting issue ‘Contemporary morphogenesis’.

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Li, Haiyan, Zanxia Cao, Guodong Hu, Liling Zhao, Chunling Wang, and Jihua Wang. "Ligand-induced structural changes analysis of ribose-binding protein as studied by molecular dynamics simulations." Technology and Health Care 29 (March 25, 2021): 103–14. http://dx.doi.org/10.3233/thc-218011.

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BACKGROUND: The ribose-binding protein (RBP) from Escherichia coli is one of the representative structures of periplasmic binding proteins. Binding of ribose at the cleft between two domains causes a conformational change corresponding to a closure of two domains around the ligand. The RBP has been crystallized in the open and closed conformations. OBJECTIVE: With the complex trajectory as a control, our goal was to study the conformation changes induced by the detachment of the ligand, and the results have been revealed from two computational tools, MD simulations and elastic network models. METHODS: Molecular dynamics (MD) simulations were performed to study the conformation changes of RBP starting from the open-apo, closed-holo and closed-apo conformations. RESULTS: The evolution of the domain opening angle θ clearly indicates large structural changes. The simulations indicate that the closed states in the absence of ribose are inclined to transition to the open states and that ribose-free RBP exists in a wide range of conformations. The first three dominant principal motions derived from the closed-apo trajectories, consisting of rotating, bending and twisting motions, account for the major rearrangement of the domains from the closed to the open conformation. CONCLUSIONS: The motions showed a strong one-to-one correspondence with the slowest modes from our previous study of RBP with the anisotropic network model (ANM). The results obtained for RBP contribute to the generalization of robustness for protein domain motion studies using either the ANM or PCA for trajectories obtained from MD.

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Verkhivker, Gennady. "Structural and Computational Studies of the SARS-CoV-2 Spike Protein Binding Mechanisms with Nanobodies: From Structure and Dynamics to Avidity-Driven Nanobody Engineering." International Journal of Molecular Sciences 23, no. 6 (March 8, 2022): 2928. http://dx.doi.org/10.3390/ijms23062928.

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Nanobodies provide important advantages over traditional antibodies, including their smaller size and robust biochemical properties such as high thermal stability, high solubility, and the ability to be bioengineered into novel multivalent, multi-specific, and high-affinity molecules, making them a class of emerging powerful therapies against SARS-CoV-2. Recent research efforts on the design, protein engineering, and structure-functional characterization of nanobodies and their binding with SARS-CoV-2 S proteins reflected a growing realization that nanobody combinations can exploit distinct binding epitopes and leverage the intrinsic plasticity of the conformational landscape for the SARS-CoV-2 S protein to produce efficient neutralizing and mutation resistant characteristics. Structural and computational studies have also been instrumental in quantifying the structure, dynamics, and energetics of the SARS-CoV-2 spike protein binding with nanobodies. In this review, a comprehensive analysis of the current structural, biophysical, and computational biology investigations of SARS-CoV-2 S proteins and their complexes with distinct classes of nanobodies targeting different binding sites is presented. The analysis of computational studies is supplemented by an in-depth examination of mutational scanning simulations and identification of binding energy hotspots for distinct nanobody classes. The review is focused on the analysis of mechanisms underlying synergistic binding of multivalent nanobodies that can be superior to single nanobodies and conventional nanobody cocktails in combating escape mutations by effectively leveraging binding avidity and allosteric cooperativity. We discuss how structural insights and protein engineering approaches together with computational biology tools can aid in the rational design of synergistic combinations that exhibit superior binding and neutralization characteristics owing to avidity-mediated mechanisms.

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Ose, Nicholas J., Brandon M. Butler, Avishek Kumar, I. Can Kazan, Maxwell Sanderford, Sudhir Kumar, and S. Banu Ozkan. "Dynamic coupling of residues within proteins as a mechanistic foundation of many enigmatic pathogenic missense variants." PLOS Computational Biology 18, no. 4 (April 7, 2022): e1010006. http://dx.doi.org/10.1371/journal.pcbi.1010006.

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Many pathogenic missense mutations are found in protein positions that are neither well-conserved nor fall in any known functional domains. Consequently, we lack any mechanistic underpinning of dysfunction caused by such mutations. We explored the disruption of allosteric dynamic coupling between these positions and the known functional sites as a possible mechanism for pathogenesis. In this study, we present an analysis of 591 pathogenic missense variants in 144 human enzymes that suggests that allosteric dynamic coupling of mutated positions with known active sites is a plausible biophysical mechanism and evidence of their functional importance. We illustrate this mechanism in a case study of β-Glucocerebrosidase (GCase) in which a vast majority of 94 sites harboring Gaucher disease-associated missense variants are located some distance away from the active site. An analysis of the conformational dynamics of GCase suggests that mutations on these distal sites cause changes in the flexibility of active site residues despite their distance, indicating a dynamic communication network throughout the protein. The disruption of the long-distance dynamic coupling caused by missense mutations may provide a plausible general mechanistic explanation for biological dysfunction and disease.

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Hossain, Sheikh I., Neha S. Gandhi, Zak E. Hughes, and Suvash C. Saha. "Computational Modelling of the Interaction of Gold Nanoparticle with Lung Surfactant Monolayer." MRS Advances 4, no. 20 (2019): 1177–85. http://dx.doi.org/10.1557/adv.2019.93.

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ABSTRACTLung surfactant (LS), a thin layer of phospholipids and proteins inside the alveolus of the lung is the first biological barrier to inhaled nanoparticles (NPs). LS stabilizes and protects the alveolus during its continuous compression and expansion by fine-tuning the surface tension at the air-water interface. Previous modelling studies have reported the biophysical function of LS monolayer and its role, but many open questions regarding the consequences and interactions of airborne nano-sized particles with LS monolayer remain. In spite of gold nanoparticles (AuNPs) having a paramount role in biomedical applications, the understanding of the interactions between bare AuNPs (as pollutants) and LS monolayer components still unresolved. Continuous inhalation of NPs increases the possibility of lung ageing, reducing the normal lung functioning and promoting lung malfunction, and may induce serious lung diseases such as asthma, lung cancer, acute respiratory distress syndrome, and more. Different medical studies have shown that AuNPs can disrupt the routine lung functions of gold miners and promote respiratory diseases. In this work, coarse-grained molecular dynamics simulations are performed to gain an understanding of the interactions between bare AuNPs and LS monolayer components at the nanoscale. Different surface tensions of the monolayer are used to mimic the biological process of breathing (inhalation and exhalation). It is found that the NP affects the structure and packing of the lipids by disordering lipid tails. Overall, the analysed results suggest that bare AuNPs impede the normal biophysical function of the lung, a finding that has beneficial consequences to the potential development of treatments of various respiratory diseases.

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Kuwahara, Hiroyuki, and Russell Schwartz. "Stochastic steady state gain in a gene expression process with mRNA degradation control." Journal of The Royal Society Interface 9, no. 72 (January 11, 2012): 1589–98. http://dx.doi.org/10.1098/rsif.2011.0757.

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Recent analyses with high-resolution single-molecule experimental methods have shown highly irregular and variable bursting of mRNA in a wide range of organisms. Noise in gene expression is thought to be beneficial in cell fate specifications, as it can lay a foundation for phenotypic diversification of isogenetic cells in the homogeneous environment. However, because the stability of proteins is, in many cases, higher than that of mRNAs, noise from transcriptional bursting can be considerably buffered at the protein level, limiting the effect of noisy mRNAs at a more global regulation level. This raises a question as to what constructive role noisy mRNAs can play in the system-level dynamics. In this study, we have addressed this question using the computational models that extend the conventional transcriptional bursting model with a post-transcriptional regulation step. Surprisingly, by comparing this stochastic model with the corresponding deterministic model, we find that intrinsic fluctuations can substantially increase the expected mRNA level. Because effects of a higher mRNA level can be transmitted to the protein level even with slow protein degradation rates, this finding suggests that an increase in the protein level is another potential effect of transcriptional bursting. Here, we show that this striking steady state increase is caused by the asynchronous nature of molecular reactions, which allows the transcriptional regulation model to create additional modes of qualitatively distinct dynamics. Our results illustrate non-intuitive effects of reaction asynchronicity on system dynamics that cannot be captured by the traditional deterministic framework. Because molecular reactions are intrinsically stochastic and asynchronous, these findings may have broad implications in modelling and understanding complex biological systems.

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Lu, Wei, Carlos Bueno, Nicholas P. Schafer, Joshua Moller, Shikai Jin, Xun Chen, Mingchen Chen, et al. "OpenAWSEM with Open3SPN2: A fast, flexible, and accessible framework for large-scale coarse-grained biomolecular simulations." PLOS Computational Biology 17, no. 2 (February 12, 2021): e1008308. http://dx.doi.org/10.1371/journal.pcbi.1008308.

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We present OpenAWSEM and Open3SPN2, new cross-compatible implementations of coarse-grained models for protein (AWSEM) and DNA (3SPN2) molecular dynamics simulations within the OpenMM framework. These new implementations retain the chemical accuracy and intrinsic efficiency of the original models while adding GPU acceleration and the ease of forcefield modification provided by OpenMM’s Custom Forces software framework. By utilizing GPUs, we achieve around a 30-fold speedup in protein and protein-DNA simulations over the existing LAMMPS-based implementations running on a single CPU core. We showcase the benefits of OpenMM’s Custom Forces framework by devising and implementing two new potentials that allow us to address important aspects of protein folding and structure prediction and by testing the ability of the combined OpenAWSEM and Open3SPN2 to model protein-DNA binding. The first potential is used to describe the changes in effective interactions that occur as a protein becomes partially buried in a membrane. We also introduced an interaction to describe proteins with multiple disulfide bonds. Using simple pairwise disulfide bonding terms results in unphysical clustering of cysteine residues, posing a problem when simulating the folding of proteins with many cysteines. We now can computationally reproduce Anfinsen’s early Nobel prize winning experiments by using OpenMM’s Custom Forces framework to introduce a multi-body disulfide bonding term that prevents unphysical clustering. Our protein-DNA simulations show that the binding landscape is funneled towards structures that are quite similar to those found using experiments. In summary, this paper provides a simulation tool for the molecular biophysics community that is both easy to use and sufficiently efficient to simulate large proteins and large protein-DNA systems that are central to many cellular processes. These codes should facilitate the interplay between molecular simulations and cellular studies, which have been hampered by the large mismatch between the time and length scales accessible to molecular simulations and those relevant to cell biology.

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22

Wan, Shunzhou, Agastya P. Bhati, Stefan J. Zasada, and Peter V. Coveney. "Rapid, accurate, precise and reproducible ligand–protein binding free energy prediction." Interface Focus 10, no. 6 (October 16, 2020): 20200007. http://dx.doi.org/10.1098/rsfs.2020.0007.

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Анотація:

A central quantity of interest in molecular biology and medicine is the free energy of binding of a molecule to a target biomacromolecule. Until recently, the accurate prediction of binding affinity had been widely regarded as out of reach of theoretical methods owing to the lack of reproducibility of the available methods, not to mention their complexity, computational cost and time-consuming procedures. The lack of reproducibility stems primarily from the chaotic nature of classical molecular dynamics (MD) and the associated extreme sensitivity of trajectories to their initial conditions. Here, we review computational approaches for both relative and absolute binding free energy calculations, and illustrate their application to a diverse set of ligands bound to a range of proteins with immediate relevance in a number of medical domains. We focus on ensemble-based methods which are essential in order to compute statistically robust results, including two we have recently developed, namely thermodynamic integration with enhanced sampling and enhanced sampling of MD with an approximation of continuum solvent. Together, these form a set of rapid, accurate, precise and reproducible free energy methods. They can be used in real-world problems such as hit-to-lead and lead optimization stages in drug discovery, and in personalized medicine. These applications show that individual binding affinities equipped with uncertainty quantification may be computed in a few hours on a massive scale given access to suitable high-end computing resources and workflow automation. A high level of accuracy can be achieved using these approaches.

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23

Paulino, Joana, Myunggi Yi, Ivan Hung, Zhehong Gan, Xiaoling Wang, Eduard Y. Chekmenev, Huan-Xiang Zhou, and Timothy A. Cross. "Functional stability of water wire–carbonyl interactions in an ion channel." Proceedings of the National Academy of Sciences 117, no. 22 (May 15, 2020): 11908–15. http://dx.doi.org/10.1073/pnas.2001083117.

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Water wires are critical for the functioning of many membrane proteins, as in channels that conduct water, protons, and other ions. Here, in liquid crystalline lipid bilayers under symmetric environmental conditions, the selective hydrogen bonding interactions between eight waters comprising a water wire and a subset of 26 carbonyl oxygens lining the antiparallel dimeric gramicidin A channel are characterized by17O NMR spectroscopy at 35.2 T (or 1,500 MHz for1H) and computational studies. While backbone15N spectra clearly indicate structural symmetry between the two subunits, single site17O labels of the pore-lining carbonyls report two resonances, implying a break in dimer symmetry caused by the selective interactions with the water wire. The17O shifts document selective water hydrogen bonding with carbonyl oxygens that are stable on the millisecond timescale. Such interactions are supported by density functional theory calculations on snapshots taken from molecular dynamics simulations. Water hydrogen bonding in the pore is restricted to just three simultaneous interactions, unlike bulk water environs. The stability of the water wire orientation and its electric dipole leads to opposite charge-dipole interactions for K+ions bound at the two ends of the pore, thereby providing a simple explanation for an ∼20-fold difference in K+affinity between two binding sites that are ∼24 Å apart. The17O NMR spectroscopy reported here represents a breakthrough in high field NMR technology that will have applications throughout molecular biophysics, because of the acute sensitivity of the17O nucleus to its chemical environment.

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24

Westerlund, Annie M., Akshay Sridhar, Leo Dahl, Alma Andersson, Anna-Yaroslava Bodnar, and Lucie Delemotte. "Markov state modelling reveals heterogeneous drug-inhibition mechanism of Calmodulin." PLOS Computational Biology 18, no. 10 (October 7, 2022): e1010583. http://dx.doi.org/10.1371/journal.pcbi.1010583.

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Calmodulin (CaM) is a calcium sensor which binds and regulates a wide range of target-proteins. This implicitly enables the concentration of calcium to influence many downstream physiological responses, including muscle contraction, learning and depression. The antipsychotic drug trifluoperazine (TFP) is a known CaM inhibitor. By binding to various sites, TFP prevents CaM from associating to target-proteins. However, the molecular and state-dependent mechanisms behind CaM inhibition by drugs such as TFP are largely unknown. Here, we build a Markov state model (MSM) from adaptively sampled molecular dynamics simulations and reveal the structural and dynamical features behind the inhibitory mechanism of TFP-binding to the C-terminal domain of CaM. We specifically identify three major TFP binding-modes from the MSM macrostates, and distinguish their effect on CaM conformation by using a systematic analysis protocol based on biophysical descriptors and tools from machine learning. The results show that depending on the binding orientation, TFP effectively stabilizes features of the calcium-unbound CaM, either affecting the CaM hydrophobic binding pocket, the calcium binding sites or the secondary structure content in the bound domain. The conclusions drawn from this work may in the future serve to formulate a complete model of pharmacological modulation of CaM, which furthers our understanding of how these drugs affect signaling pathways as well as associated diseases.

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25

Wu, Yinghao, Kalyani Dhusia та Zhaoqian Su. "Mechanistic dissection of spatial organization in NF-κB signaling pathways by hybrid simulations". Integrative Biology 13, № 5 (24 квітня 2021): 109–20. http://dx.doi.org/10.1093/intbio/zyab006.

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Abstract The nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) is one of the most important transcription factors involved in the regulation of inflammatory signaling pathways. Inappropriate activation of these pathways has been linked to autoimmunity and cancers. Emerging experimental evidences have been showing the existence of elaborate spatial organizations for various molecular components in the pathways. One example is the scaffold protein tumor necrosis factor receptor associated factor (TRAF). While most TRAF proteins form trimeric quaternary structure through their coiled-coil regions, the N-terminal region of some members in the family can further be dimerized. This dimerization of TRAF trimers can drive them into higher-order clusters as a response to receptor stimulation, which functions as a spatial platform to mediate the downstream poly-ubiquitination. However, the molecular mechanism underlying the TRAF protein clustering and its functional impacts are not well-understood. In this article, we developed a hybrid simulation method to tackle this problem. The assembly of TRAF-based signaling platform at the membrane-proximal region is modeled with spatial resolution, while the dynamics of downstream signaling network, including the negative feedbacks through various signaling inhibitors, is simulated as stochastic chemical reactions. These two algorithms are further synchronized under a multiscale simulation framework. Using this computational model, we illustrated that the formation of TRAF signaling platform can trigger an oscillatory NF-κB response. We further demonstrated that the temporal patterns of downstream signal oscillations are closely regulated by the spatial factors of TRAF clustering, such as the geometry and energy of dimerization between TRAF trimers. In general, our study sheds light on the basic mechanism of NF-κB signaling pathway and highlights the functional importance of spatial regulation within the pathway. The simulation framework also showcases its potential of application to other signaling pathways in cells.

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Heerwig, Andreas, Alfred Kick, Paul Sommerfeld, Sophia Eimermacher, Frederick Hartung, Markus Laube, Dietmar Fischer та ін. "The Impact of Nε-Acryloyllysine Piperazides on the Conformational Dynamics of Transglutaminase 2". International Journal of Molecular Sciences 24, № 2 (13 січня 2023): 1650. http://dx.doi.org/10.3390/ijms24021650.

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Анотація:

In addition to the classic functions of proteins, such as acting as a biocatalyst or binding partner, the conformational states of proteins and their remodeling upon stimulation need to be considered. A prominent example of a protein that undergoes comprehensive conformational remodeling is transglutaminase 2 (TGase 2), the distinct conformational states of which are closely related to particular functions. Its involvement in various pathophysiological processes, including fibrosis and cancer, motivates the development of theranostic agents, particularly based on inhibitors that are directed toward the transamidase activity. In this context, the ability of such inhibitors to control the conformational dynamics of TGase 2 emerges as an important parameter, and methods to assess this property are in great demand. Herein, we describe the application of the switchSENSE® principle to detect conformational changes caused by three irreversibly binding Nε-acryloyllysine piperazides, which are suitable radiotracer candidates of TGase 2. The switchSENSE® technique is based on DNA levers actuated by alternating electric fields. These levers are immobilized on gold electrodes with one end, and at the other end of the lever, the TGase 2 is covalently bound. A novel computational method is introduced for describing the resulting lever motion to quantify the extent of stimulated conformational TGase 2 changes. Moreover, as a complementary biophysical method, native polyacrylamide gel electrophoresis was performed under similar conditions to validate the results. Both methods prove the occurrence of an irreversible shift in the conformational equilibrium of TGase 2, caused by the binding of the three studied Nε-acryloyllysine piperazides.

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27

Silva, Andriele, and Shaneen Singh. "Abstract 5029: A computational analysis of NEK10 and its novel protein-protein interaction with HspB1." Cancer Research 82, no. 12_Supplement (June 15, 2022): 5029. http://dx.doi.org/10.1158/1538-7445.am2022-5029.

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Abstract The NEK kinase family of proteins consists of 11 serine/threonine kinases that participate in the disjunction of the centrosome, mitotic spindle assembly, and primary cilium formation. NEK10 is the most divergent member of the NEK family. It is unique in having a catalytic domain that is centrally positioned and flanked by two coiled-coil domains, while all the other NEKs have their catalytic domain near the N-terminus. Instead, NEK10 has four armadillo repeats of unexplored function in its N-terminus. NEK10 seems to play a key role in carcinogenesis and has been linked in melanoma, breast cancer, and a variety of ciliopathies. As part of our long-term goal to build interactomes of all the NEK members, we have previously reported data for known and predicted NEK10 interacting proteins, including novel protein-protein interactions such as HspB1 and MAP3K1, which have not been previously reported in the literature. In this study, we focused on understanding the molecular mechanism underlying NEK10’s interaction with HspB1 and its functional consequences. HspB1 is involved in various cellular functions such as maintaining cytoskeletal integrity and cell death. It is also a well-studied cancer protein and contains a highly conserved α-crystallin domain flanked by disordered N- and C-terminal domains. Many proteins are targeted by HspB1 to promote resistance to cell death, and malignant phenotypes; high levels of HspB1 have been identified in many cancer stem cells, such as those from lung and breast cancers. We used state-of-the-art computational approaches to model and characterize the full-length NEK10 as well as HspB1 protein. Our results offer robust full-length three-dimensional models of NEK10 and HspB1 and their biophysical characterization. In addition, we delineate the role of the armadillo repeats that are unique to NEK10 in the NEK family, in its interaction with HspB1. Our docking analysis shows that GLU178 of NEK10 located within its Armadillo Repeats forms a salt bridge with ARG953 of HspB1’s β4/β8 groove, which is a known protein-protein interaction hot spot for both interactions with other proteins as well as for self-interactions. Our results, therefore, suggest a scenario of Nek10 interaction with HspB1 using its ARM motif, which frees the catalytic domain for auto-phosphorylation and/or phosphorylation of other targets. Since HspB1 regulates the architecture of the cellular microtubular network (MT) by facilitating the formation of non-centrosomal MT, we speculate that the interaction of NEK10 with HspB1 plays a role in centrosome dynamics. Overall, this study shows novel and intriguing information about NEK10’s structure-function relationships, especially in the context of its interaction with HspB1. Furthermore, it establishes the framework for elucidating the detailed molecular mechanisms of NEK10 interactions with other proteins to further explore its potential as a therapeutic target. Citation Format: Andriele Silva, Shaneen Singh. A computational analysis of NEK10 and its novel protein-protein interaction with HspB1 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5029.

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S., Udhaya Kumar, Srivarshini Sankar, Salma Younes, Thirumal Kumar D., Muneera Naseer Ahmad, Sarah Samer Okashah, Balu Kamaraj, Abeer Mohammed Al-Subaie, George Priya Doss C., and Hatem Zayed. "Deciphering the Role of Filamin B Calponin-Homology Domain in Causing the Larsen Syndrome, Boomerang Dysplasia, and Atelosteogenesis Type I Spectrum Disorders via a Computational Approach." Molecules 25, no. 23 (November 26, 2020): 5543. http://dx.doi.org/10.3390/molecules25235543.

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Filamins (FLN) are a family of actin-binding proteins involved in regulating the cytoskeleton and signaling phenomenon by developing a network with F-actin and FLN-binding partners. The FLN family comprises three conserved isoforms in mammals: FLNA, FLNB, and FLNC. FLNB is a multidomain monomer protein with domains containing an actin-binding N-terminal domain (ABD 1–242), encompassing two calponin-homology domains (assigned CH1 and CH2). Primary variants in FLNB mostly occur in the domain (CH2) and surrounding the hinge-1 region. The four autosomal dominant disorders that are associated with FLNB variants are Larsen syndrome, atelosteogenesis type I (AOI), atelosteogenesis type III (AOIII), and boomerang dysplasia (BD). Despite the intense clustering of FLNB variants contributing to the LS-AO-BD disorders, the genotype-phenotype correlation is still enigmatic. In silico prediction tools and molecular dynamics simulation (MDS) approaches have offered the potential for variant classification and pathogenicity predictions. We retrieved 285 FLNB missense variants from the UniProt, ClinVar, and HGMD databases in the current study. Of these, five and 39 variants were located in the CH1 and CH2 domains, respectively. These variants were subjected to various pathogenicity and stability prediction tools, evolutionary and conservation analyses, and biophysical and physicochemical properties analyses. Molecular dynamics simulation (MDS) was performed on the three candidate variants in the CH2 domain (W148R, F161C, and L171R) that were predicted to be the most pathogenic. The MDS analysis results showed that these three variants are highly compact compared to the native protein, suggesting that they could affect the protein on the structural and functional levels. The computational approach demonstrates the differences between the FLNB mutants and the wild type in a structural and functional context. Our findings expand our knowledge on the genotype-phenotype correlation in FLNB-related LS-AO-BD disorders on the molecular level, which may pave the way for optimizing drug therapy by integrating precision medicine.

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Schaaf, Gabriel, Marek Dynowski, Carl J. Mousley, Sweety D. Shah, Peihua Yuan, Eva M. Winklbauer, Marília K. F. de Campos, et al. "Resurrection of a functional phosphatidylinositol transfer protein from a pseudo-Sec14 scaffold by directed evolution." Molecular Biology of the Cell 22, no. 6 (March 15, 2011): 892–905. http://dx.doi.org/10.1091/mbc.e10-11-0903.

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Анотація:

Sec14-superfamily proteins integrate the lipid metabolome with phosphoinositide synthesis and signaling via primed presentation of phosphatidylinositol (PtdIns) to PtdIns kinases. Sec14 action as a PtdIns-presentation scaffold requires heterotypic exchange of phosphatidylcholine (PtdCho) for PtdIns, or vice versa, in a poorly understood progression of regulated conformational transitions. We identify mutations that confer Sec14-like activities to a functionally inert pseudo-Sec14 (Sfh1), which seemingly conserves all of the structural requirements for Sec14 function. Unexpectedly, the “activation” phenotype results from alteration of residues conserved between Sfh1 and Sec14. Using biochemical and biophysical, structural, and computational approaches, we find the activation mechanism reconfigures atomic interactions between amino acid side chains and internal water in an unusual hydrophilic microenvironment within the hydrophobic Sfh1 ligand-binding cavity. These altered dynamics reconstitute a functional “gating module” that propagates conformational energy from within the hydrophobic pocket to the helical unit that gates pocket access. The net effect is enhanced rates of phospholipid-cycling into and out of the Sfh1* hydrophobic pocket. Taken together, the directed evolution approach reveals an unexpectedly flexible functional engineering of a Sec14-like PtdIns transfer protein—an engineering invisible to standard bioinformatic, crystallographic, and rational mutagenesis approaches.

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30

Elk, Jackson Chief, J. B. Alexander Ross, and Stephen R. Sprang. "Molecular Dynamics Investigation on Conformational Dynamics of G Proteins." Biophysical Journal 100, no. 3 (February 2011): 533a. http://dx.doi.org/10.1016/j.bpj.2010.12.3109.

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Vaidehi, Nagarajan, Gouthaman Balaraman, In-Hee Park, Jeff Wagner, and Abhinandan Jain. "Heirarchical Constrained Molecular Dynamics Simulations for Proteins." Biophysical Journal 100, no. 3 (February 2011): 533a. http://dx.doi.org/10.1016/j.bpj.2010.12.3113.

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32

Dobson, Christopher M. "Biophysical Techniques in Structural Biology." Annual Review of Biochemistry 88, no. 1 (June 20, 2019): 25–33. http://dx.doi.org/10.1146/annurev-biochem-013118-111947.

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Анотація:

Over the past six decades, steadily increasing progress in the application of the principles and techniques of the physical sciences to the study of biological systems has led to remarkable insights into the molecular basis of life. Of particular significance has been the way in which the determination of the structures and dynamical properties of proteins and nucleic acids has so often led directly to a profound understanding of the nature and mechanism of their functional roles. The increasing number and power of experimental and theoretical techniques that can be applied successfully to living systems is now ushering in a new era of structural biology that is leading to fundamentally new information about the maintenance of health, the origins of disease, and the development of effective strategies for therapeutic intervention. This article provides a brief overview of some of the most powerful biophysical methods in use today, along with references that provide more detailed information about recent applications of each of them. In addition, this article acts as an introduction to four authoritative reviews in this volume. The first shows the ways that a multiplicity of biophysical methods can be combined with computational techniques to define the architectures of complex biological systems, such as those involving weak interactions within ensembles of molecular components. The second illustrates one aspect of this general approach by describing how recent advances in mass spectrometry, particularly in combination with other techniques, can generate fundamentally new insights into the properties of membrane proteins and their functional interactions with lipid molecules. The third reviewdemonstrates the increasing power of rapidly evolving diffraction techniques, employing the very short bursts of X-rays of extremely high intensity that are now accessible as a result of the construction of free-electron lasers, in particular to carry out time-resolved studies of biochemical reactions. The fourth describes in detail the application of such approaches to probe the mechanism of the light-induced changes associated with bacteriorhodopsin's ability to convert light energy into chemical energy.

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33

Haddad, Yazan, Vojtech Adam, and Zbynek Heger. "Rotamer Dynamics: Analysis of Rotamers in Molecular Dynamics Simulations of Proteins." Biophysical Journal 116, no. 11 (June 2019): 2062–72. http://dx.doi.org/10.1016/j.bpj.2019.04.017.

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34

Seshan, Shiv S. "The rigidization of water dynamics around proteins: A molecular dynamics study." Biophysical Journal 122, no. 3 (February 2023): 138a. http://dx.doi.org/10.1016/j.bpj.2022.11.909.

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35

Stacklies, Wolfram, and Frauke Graeter. "Force Propagation in Proteins From Molecular Dynamics Simulations." Biophysical Journal 96, no. 3 (February 2009): 589a. http://dx.doi.org/10.1016/j.bpj.2008.12.3087.

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36

Toofanny, Rudesh D., Aitziber L. Cortajarena, Lynne Regan, and Valerie Daggett. "Molecular Dynamics Simulations of Consensus Tetratricopeptide Repeat Proteins." Biophysical Journal 98, no. 3 (January 2010): 636a—637a. http://dx.doi.org/10.1016/j.bpj.2009.12.3486.

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37

Truelsen, Sigurd F. "Accelerated Molecular Dynamics Simulations of Phosphate Binding Proteins." Biophysical Journal 110, no. 3 (February 2016): 540a. http://dx.doi.org/10.1016/j.bpj.2015.11.2893.

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38

Kandel, Saugat, Adrien B. Larsen, Abhinandan Jain, and Nagarajan Vaidehi. "Gneimosim: Multiscale Internal Coordinates Molecular Dynamics for Proteins." Biophysical Journal 110, no. 3 (February 2016): 641a. http://dx.doi.org/10.1016/j.bpj.2015.11.3429.

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39

Haas-Neill, Liam I., and Sarah Rauscher. "Molecular Dynamics Simulations of Phosphorylated Intrinsically Disordered Proteins." Biophysical Journal 116, no. 3 (February 2019): 432a—433a. http://dx.doi.org/10.1016/j.bpj.2018.11.2329.

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40

Sridhar Dwadasi, Balarama, Hristina R. Zhekova, Sergei Y. Noskov, Dennis R. Salahub, and Peter D. Tieleman. "Constant pH molecular dynamics simulations of membrane proteins." Biophysical Journal 122, no. 3 (February 2023): 424a. http://dx.doi.org/10.1016/j.bpj.2022.11.2297.

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41

Belato, Helen B., Carmelissa Norbrun, Jinping Luo, Chinmai Pindi, Souvik Sinha, Alexandra M. D’Ordine, Gerwald Jogl, Giulia Palermo, and George P. Lisi. "Disruption of electrostatic contacts in the HNH nuclease from a thermophilic Cas9 rewires allosteric motions and enhances high-temperature DNA cleavage." Journal of Chemical Physics 157, no. 22 (December 14, 2022): 225103. http://dx.doi.org/10.1063/5.0128815.

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Allosteric signaling within multidomain proteins is a driver of communication between spatially distant functional sites. Understanding the mechanism of allosteric coupling in large multidomain proteins is the most promising route to achieving spatial and temporal control of the system. The recent explosion of CRISPR-Cas9 applications in molecular biology and medicine has created a need to understand how the atomic level protein dynamics of Cas9, which are the driving force of its allosteric crosstalk, influence its biophysical characteristics. In this study, we used a synergistic approach of nuclear magnetic resonance (NMR) and computation to pinpoint an allosteric hotspot in the HNH domain of the thermostable GeoCas9. We show that mutation of K597 to alanine disrupts a salt-bridge network, which in turn alters the structure, the timescale of allosteric motions, and the thermostability of the GeoHNH domain. This homologous lysine-to-alanine mutation in the extensively studied mesophilic S. pyogenes Cas9 similarly alters the dynamics of the SpHNH domain. We have previously demonstrated that the alteration of allostery via mutations is a source for the specificity enhancement of SpCas9 (e SpCas9). Hence, this may also be true in GeoCas9.

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42

Huang, Jing. "Computational dissection of the structure-dynamics-function relationship of human solute carrier proteins." Biophysical Journal 122, no. 3 (February 2023): 507a. http://dx.doi.org/10.1016/j.bpj.2022.11.2700.

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43

Durrieu, Marie-Pierre, Richard Lavery, and Marc Baaden. "Interactions between Neuronal Fusion Proteins Explored by Molecular Dynamics." Biophysical Journal 94, no. 9 (May 2008): 3436–46. http://dx.doi.org/10.1529/biophysj.107.123117.

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Fogolari, Federico, Alessandro Brigo, and Henriette Molinari. "Protocol for MM/PBSA Molecular Dynamics Simulations of Proteins." Biophysical Journal 85, no. 1 (July 2003): 159–66. http://dx.doi.org/10.1016/s0006-3495(03)74462-2.

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45

Childers, Matthew Carter, and Valerie Daggett. "Insights from molecular dynamics simulations for computational protein design." Molecular Systems Design & Engineering 2, no. 1 (2017): 9–33. http://dx.doi.org/10.1039/c6me00083e.

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46

Dutta, Mandira, and Gregory A. Voth. "Computational studies of the dynamics of SARS-CoV-2 spike, membrane, and nucleocapsid proteins." Biophysical Journal 121, no. 3 (February 2022): 455a. http://dx.doi.org/10.1016/j.bpj.2021.11.482.

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47

Bock, Lars, Brian Hutchings, Helmut Grubmüller, and Dixon J. Woodbury. "Chemomechanical Regulation of Snare Proteins Studied with Molecular Dynamics Simulations." Biophysical Journal 98, no. 3 (January 2010): 677a. http://dx.doi.org/10.1016/j.bpj.2009.12.3723.

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Bock, Lars V., Brian Hutchings, Helmut Grubmüller, and Dixon J. Woodbury. "Chemomechanical Regulation of SNARE Proteins Studied with Molecular Dynamics Simulations." Biophysical Journal 99, no. 4 (August 2010): 1221–30. http://dx.doi.org/10.1016/j.bpj.2010.06.019.

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Chen, Wei, Jason A. Wallace, Zhi Yue, and Jana K. Shen. "Application of Explicit-Solvent Constant ph Molecular Dynamics to Proteins." Biophysical Journal 104, no. 2 (January 2013): 508a. http://dx.doi.org/10.1016/j.bpj.2012.11.2803.

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Hawkins, Russell, and Daniel Cox. "Elastic Moduli of Fibrous Proteins from Equilibrium Molecular Dynamics Simulation." Biophysical Journal 114, no. 3 (February 2018): 676a. http://dx.doi.org/10.1016/j.bpj.2017.11.3647.

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