1
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Sunda AP, Sharma AK. Molecular Insights into Cu/Zn Metal Response to the Amyloid β-Peptide (1-42). ACS PHYSICAL CHEMISTRY AU 2024; 4:57-66. [PMID: 38283784 PMCID: PMC10811771 DOI: 10.1021/acsphyschemau.3c00041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 10/03/2023] [Accepted: 10/04/2023] [Indexed: 01/30/2024]
Abstract
Aβ1-40 peptide and Aβ1-42 peptide are the building units of beta-amyloid plaques present in Alzheimer's disease (AD)-affected brain. The binding affinity of various divalent metal ions such as Cu and Zn present in AD-affected brain with different amino acids available in Aβ-peptide became the focus to explore their role in soluble neurotoxic oligomer formation. Cu2+ metal ions are known to enhance the neurotoxicity of the Aβ1-42 peptide by catalyzing the formation of soluble neurotoxic oligomers. The competitive preference of both Cu2+ and Zn2+ simultaneously to interact with the Aβ-peptide is unknown. The divalent Cu and Zn ions were inserted in explicit aqueous Aβ1-42 peptide configurations to get insights into the binding competence of these metal ions with peptides using classical molecular dynamics (MD) simulations. The metal-ion interactions reveal that competitive binding preferences of various peptide sites become metal-ion-specific and differ significantly. For Cu2+, interactions are found to be more significant with respect to those of Asp-7, His-6, Glu-11, and His-14. Asp-1, Glu-3, Asp-7, His-6, Glu-11, and His-13 amino acid residues show higher affinity toward Zn2+ ions. MD simulations show notable variation in the solvent-accessible surface area in the hydrophobic region of the peptide. Infinitesimal mobility was obtained for Zn2+ compared to Cu2+ in an aqueous solution and Cu2+ diffusivity deviated significantly at different time scales, proving its labile features in aqueous Aβ1-42 peptides.
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Affiliation(s)
- Anurag Prakash Sunda
- Department
of Chemistry, J. C. Bose University of Science
and Technology, YMCA, Faridabad 121006, India
| | - Anuj Kumar Sharma
- Department
of Chemistry, School of Chemical Sciences and Pharmacy, Central University of Rajasthan, Ajmer 305817, India
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2
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Borges-Araújo L, Patmanidis I, Singh AP, Santos LHS, Sieradzan AK, Vanni S, Czaplewski C, Pantano S, Shinoda W, Monticelli L, Liwo A, Marrink SJ, Souza PCT. Pragmatic Coarse-Graining of Proteins: Models and Applications. J Chem Theory Comput 2023; 19:7112-7135. [PMID: 37788237 DOI: 10.1021/acs.jctc.3c00733] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
The molecular details involved in the folding, dynamics, organization, and interaction of proteins with other molecules are often difficult to assess by experimental techniques. Consequently, computational models play an ever-increasing role in the field. However, biological processes involving large-scale protein assemblies or long time scale dynamics are still computationally expensive to study in atomistic detail. For these applications, employing coarse-grained (CG) modeling approaches has become a key strategy. In this Review, we provide an overview of what we call pragmatic CG protein models, which are strategies combining, at least in part, a physics-based implementation and a top-down experimental approach to their parametrization. In particular, we focus on CG models in which most protein residues are represented by at least two beads, allowing these models to retain some degree of chemical specificity. A description of the main modern pragmatic protein CG models is provided, including a review of the most recent applications and an outlook on future perspectives in the field.
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Affiliation(s)
- Luís Borges-Araújo
- Molecular Microbiology and Structural Biochemistry (MMSB, UMR 5086), CNRS, University of Lyon, 7 Passage du Vercors, 69007 Lyon, France
| | - Ilias Patmanidis
- Department of Chemistry, Aarhus University, Langelandsgade 140, 8000 Aarhus C, Denmark
- Groningen Biomolecular Sciences and Biotechnology Institute and Zernike Institute for Advanced Materials, University of Groningen, Nijenborgh 7, 9747 AG Groningen, The Netherlands
| | - Akhil P Singh
- Department of Biology, University of Fribourg, Chemin du Musée 10, Fribourg CH-1700, Switzerland
| | - Lucianna H S Santos
- Biomolecular Simulations Group, Institut Pasteur de Montevideo, Montevideo 11400, Uruguay
| | - Adam K Sieradzan
- Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, 80-308 Gdansk, Poland
| | - Stefano Vanni
- Department of Biology, University of Fribourg, Chemin du Musée 10, Fribourg CH-1700, Switzerland
- Institut de Pharmacologie Moléculaire et Cellulaire, Université Côte d'Azur, Inserm, CNRS, 06560 Valbonne, France
| | - Cezary Czaplewski
- Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, 80-308 Gdansk, Poland
| | - Sergio Pantano
- Biomolecular Simulations Group, Institut Pasteur de Montevideo, Montevideo 11400, Uruguay
| | - Wataru Shinoda
- Research Institute for Interdisciplinary Science, Okayama University, 3-1-1 Tsushima-naka, Kita, Okayama 700-8530, Japan
| | - Luca Monticelli
- Molecular Microbiology and Structural Biochemistry (MMSB, UMR 5086), CNRS, University of Lyon, 7 Passage du Vercors, 69007 Lyon, France
| | - Adam Liwo
- Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, 80-308 Gdansk, Poland
| | - Siewert J Marrink
- Groningen Biomolecular Sciences and Biotechnology Institute and Zernike Institute for Advanced Materials, University of Groningen, Nijenborgh 7, 9747 AG Groningen, The Netherlands
| | - Paulo C T Souza
- Molecular Microbiology and Structural Biochemistry (MMSB, UMR 5086), CNRS, University of Lyon, 7 Passage du Vercors, 69007 Lyon, France
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3
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de Oliveira VM, Liu R, Shen J. Constant pH molecular dynamics simulations: Current status and recent applications. Curr Opin Struct Biol 2022; 77:102498. [PMID: 36410222 PMCID: PMC9933785 DOI: 10.1016/j.sbi.2022.102498] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Accepted: 10/10/2022] [Indexed: 11/19/2022]
Abstract
Many important protein functions are carried out through proton-coupled conformational dynamics. Thus, the ability to accurately model protonation states dynamically has wide-ranging implications. Over the past two decades, two main types of constant pH methods (discrete and continuous) have been developed to enable proton-coupled molecular dynamics (MD) simulations. In this short review, we discuss the current status of the development and highlight recent applications that have advanced our understanding of protein structure-function relationships. We conclude the review by outlining the remaining challenges in the method development and projecting important areas for future applications.
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Affiliation(s)
- Vinicius Martins de Oliveira
- Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, 20 Penn Street, Baltimore, 20201, Maryland, U.S.A
| | - Ruibin Liu
- Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, 20 Penn Street, Baltimore, 20201, Maryland, U.S.A
| | - Jana Shen
- Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, 20 Penn Street, Baltimore, 20201, MD, USA.
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4
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Silva TD, Vila-Viçosa D, Machuqueiro M. Increasing the Realism of in Silico pHLIP Peptide Models with a Novel pH Gradient CpHMD Method. J Chem Theory Comput 2022; 18:6472-6481. [PMID: 36257921 PMCID: PMC9775217 DOI: 10.1021/acs.jctc.2c00880] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
The pH-low insertion peptides (pHLIP) are pH-dependent membrane inserting peptides, whose function depends on the cell microenvironment acidity. Several peptide variants have been designed to improve upon the wt-sequence, particularly the state transition kinetics and the selectivity for tumor pH. The variant 3 (Var3) peptide is a 27 residue long peptide, with a key titrating residue (Asp-13) that, despite showing a modest performance in liposomes (pKins ∼ 5.0), excelled in tumor cell experiments. To help rationalize these results, we focused on the pH gradient in the cell membrane, which is one of the crucial properties that are not present in liposomes. We extended our CpHMD-L method and its pH replica-exchange (pHRE) implementation to include a pH gradient and mimic the pHLIP-membrane microenvironment in a cell where the internal pH is fixed (pH 7.2) and the external pH is allowed to change. We showed that, by properly modeling the pH-gradient, we can correctly predict the experimentally observed loss and gain of performance in tumor cells experiments by the wt and Var3 sequences, respectively. In sum, the pH gradient implementation allowed for more accurate and realistic pKa estimations and was a pivotal step in bridging the in silico data and the in vivo cell experiments.
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5
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Sequeira JN, Rodrigues FEP, Silva TGD, Reis PBPS, Machuqueiro M. Extending the Stochastic Titration CpHMD to CHARMM36m. J Phys Chem B 2022; 126:7870-7882. [PMID: 36190807 PMCID: PMC9776569 DOI: 10.1021/acs.jpcb.2c04529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
The impact of pH on proteins is significant but often neglected in molecular dynamics simulations. Constant-pH Molecular Dynamics (CpHMD) is the state-of-the-art methodology to deal with these effects. However, it still lacks widespread adoption by the scientific community. The stochastic titration CpHMD is one of such methods that, until now, only supported the GROMOS force field family. Here, we extend this method's implementation to include the CHARMM36m force field available in the GROMACS software package. We test this new implementation with a diverse group of proteins, namely, lysozyme, Staphylococcal nuclease, and human and E. coli thioredoxins. All proteins were conformationally stable in the simulations, even at extreme pH values. The RMSE values (pKa prediction vs experimental) obtained were very encouraging, in particular for lysozyme and human thioredoxin. We have also identified a few residues that challenged the CpHMD simulations, highlighting scenarios where the method still needs improvement independently of the force field. The CHARMM36m all-atom implementation was more computationally efficient when compared with the GROMOS 54A7, taking advantage of a shorter nonbonded interaction cutoff and a less frequent neighboring list update. The new extension will allow the study of pH effects in many systems for which this force field is particularly suited, i.e., proteins, membrane proteins, lipid bilayers, and nucleic acids.
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6
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Barroso da Silva FL, Giron CC, Laaksonen A. Electrostatic Features for the Receptor Binding Domain of SARS-COV-2 Wildtype and Its Variants. Compass to the Severity of the Future Variants with the Charge-Rule. J Phys Chem B 2022; 126:6835-6852. [PMID: 36066414 DOI: 10.1021/acs.jpcb.2c04225] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Electrostatic intermolecular interactions are important in many aspects of biology. We have studied the main electrostatic features involved in the interaction of the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein with the human receptor Angiotensin-converting enzyme 2 (ACE2). As the principal computational tool, we have used the FORTE approach, capable to model proton fluctuations and computing free energies for a very large number of protein-protein systems under different physical-chemical conditions, here focusing on the RBD-ACE2 interactions. Both the wild-type and all critical variants are included in this study. From our large ensemble of extensive simulations, we obtain, as a function of pH, the binding affinities, charges of the proteins, their charge regulation capacities, and their dipole moments. In addition, we have calculated the pKas for all ionizable residues and mapped the electrostatic coupling between them. We are able to present a simple predictor for the RBD-ACE2 binding based on the data obtained for Alpha, Beta, Gamma, Delta, and Omicron variants, as a linear correlation between the total charge of the RBD and the corresponding binding affinity. This "RBD charge rule" should work as a quick test of the degree of severity of the coming SARS-CoV-2 variants in the future.
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Affiliation(s)
- Fernando L Barroso da Silva
- Departamento de Ciências Biomoleculares, Faculdade de Ciências Farmacêuticas de Ribeirão Preto, Universidade de São Paulo, Av. café, s/no-campus da USP, BR-14040-903 Ribeirão Preto, SP, Brazil.,Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina 27695, United States
| | - Carolina Corrêa Giron
- Departamento de Ciências Biomoleculares, Faculdade de Ciências Farmacêuticas de Ribeirão Preto, Universidade de São Paulo, Av. café, s/no-campus da USP, BR-14040-903 Ribeirão Preto, SP, Brazil.,Hospital de Clínicas, Universidade Federal do Triângulo Mineiro, Av. Getúlio Guaritá, 38025-440 Uberaba, MG, Brazil
| | - Aatto Laaksonen
- Department of Materials and Environmental Chemistry, Arrhenius Laboratory, Stockholm University, SE-106 91 Stockholm, Sweden.,State Key Laboratory of Materials-Oriented and Chemical Engineering, Nanjing Tech University, Nanjing, 210009, P. R. China.,Centre of Advanced Research in Bionanoconjugates and Biopolymers, Petru Poni Institute of Macromolecular Chemistry, Aleea Grigore Ghica-Voda, 41A, 700487 Iasi, Romania.,Department of Engineering Sciences and Mathematics, Division of Energy Science, Luleå University of Technology, SE-97187 Luleå, Sweden.,Department of Chemical and Geological Sciences, Campus Monserrato, University of Cagliari, SS 554 bivio per Sestu, 09042 Monserrato, Italy
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7
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Kawamoto S, Liu H, Miyazaki Y, Seo S, Dixit M, DeVane R, MacDermaid C, Fiorin G, Klein ML, Shinoda W. SPICA Force Field for Proteins and Peptides. J Chem Theory Comput 2022; 18:3204-3217. [PMID: 35413197 DOI: 10.1021/acs.jctc.1c01207] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
A coarse-grained (CG) model for peptides and proteins was developed as an extension of the Surface Property fItting Coarse grAined (SPICA) force field (FF). The model was designed to examine membrane proteins that are fully compatible with the lipid membranes of the SPICA FF. A preliminary version of this protein model was created using thermodynamic properties, including the surface tension and density in the SPICA (formerly called SDK) FF. In this study, we improved the CG protein model to facilitate molecular dynamics (MD) simulations with a reproduction of multiple properties from both experiments and all-atom (AA) simulations. An elastic network model was adopted to maintain the secondary structure within a single chain. The side-chain analogues reproduced the transfer free energy profiles across the lipid membrane and demonstrated reasonable association free energy (potential of mean force) in water compared to those from AA MD. A series of peptides/proteins adsorbed onto or penetrated into the membrane simulated by the CG MD correctly predicted the penetration depths and tilt angles of peripheral and transmembrane peptides/proteins as comparable to those in the orientations of proteins in membranes (OPM) database. In addition, the dimerization free energies of several transmembrane helices within a lipid bilayer were comparable to those from experimental estimation. Application studies on a series of membrane protein assemblies, scramblases, and poliovirus capsids demonstrated the good performance of the SPICA FF.
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Affiliation(s)
- Shuhei Kawamoto
- Department of Materials Chemistry, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan
| | - Huihui Liu
- Department of Materials Chemistry, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan
| | - Yusuke Miyazaki
- Department of Materials Chemistry, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan.,Research Institute for Interdisciplinary Science, Okayama University, 3-1-1 Tsushima-naka, Kita-ku, Okayama 700-8530, Japan
| | - Sangjae Seo
- Department of Materials Chemistry, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan.,Korea Institute of Science and Technology Information, 245 Daehak-ro, Daejeon 34141, Republic of Korea
| | - Mayank Dixit
- Department of Materials Chemistry, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan
| | - Russell DeVane
- Modeling & Simulation, Corporate Research & Development, The Procter and Gamble Company, West Chester, Ohio 45069, United States
| | - Christopher MacDermaid
- Institute for Computational Molecular Science, Temple University, 1925 North 12th Street, Philadelphia, Pennsylvania 19122, United States
| | - Giacomo Fiorin
- Institute for Computational Molecular Science, Temple University, 1925 North 12th Street, Philadelphia, Pennsylvania 19122, United States
| | - Michael L Klein
- Institute for Computational Molecular Science, Temple University, 1925 North 12th Street, Philadelphia, Pennsylvania 19122, United States
| | - Wataru Shinoda
- Department of Materials Chemistry, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan.,Research Institute for Interdisciplinary Science, Okayama University, 3-1-1 Tsushima-naka, Kita-ku, Okayama 700-8530, Japan.,Department of Chemistry, Faculty of Science, Okayama University, 3-1-1 Tsushima-naka, Kita-ku, Okayama 700-8530, Japan
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8
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Co NT, Li MS, Krupa P. Computational Models for the Study of Protein Aggregation. Methods Mol Biol 2022; 2340:51-78. [PMID: 35167070 DOI: 10.1007/978-1-0716-1546-1_4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Protein aggregation has been studied by many groups around the world for many years because it can be the cause of a number of neurodegenerative diseases that have no effective treatment. Obtaining the structure of related fibrils and toxic oligomers, as well as describing the pathways and main factors that govern the self-organization process, is of paramount importance, but it is also very difficult. To solve this problem, experimental and computational methods are often combined to get the most out of each method. The effectiveness of the computational approach largely depends on the construction of a reasonable molecular model. Here we discussed different versions of the four most popular all-atom force fields AMBER, CHARMM, GROMOS, and OPLS, which have been developed for folded and intrinsically disordered proteins, or both. Continuous and discrete coarse-grained models, which were mainly used to study the kinetics of aggregation, are also summarized.
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Affiliation(s)
- Nguyen Truong Co
- Institute of Physics, Polish Academy of Sciences, Warsaw, Poland
| | - Mai Suan Li
- Institute of Physics, Polish Academy of Sciences, Warsaw, Poland
- Institute for Computational Science and Technology, Ho Chi Minh City, Vietnam
| | - Pawel Krupa
- Institute of Physics, Polish Academy of Sciences, Warsaw, Poland.
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9
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Liwo A, Czaplewski C, Sieradzan AK, Lipska AG, Samsonov SA, Murarka RK. Theory and Practice of Coarse-Grained Molecular Dynamics of Biologically Important Systems. Biomolecules 2021; 11:1347. [PMID: 34572559 PMCID: PMC8465211 DOI: 10.3390/biom11091347] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Revised: 09/03/2021] [Accepted: 09/09/2021] [Indexed: 12/16/2022] Open
Abstract
Molecular dynamics with coarse-grained models is nowadays extensively used to simulate biomolecular systems at large time and size scales, compared to those accessible to all-atom molecular dynamics. In this review article, we describe the physical basis of coarse-grained molecular dynamics, the coarse-grained force fields, the equations of motion and the respective numerical integration algorithms, and selected practical applications of coarse-grained molecular dynamics. We demonstrate that the motion of coarse-grained sites is governed by the potential of mean force and the friction and stochastic forces, resulting from integrating out the secondary degrees of freedom. Consequently, Langevin dynamics is a natural means of describing the motion of a system at the coarse-grained level and the potential of mean force is the physical basis of the coarse-grained force fields. Moreover, the choice of coarse-grained variables and the fact that coarse-grained sites often do not have spherical symmetry implies a non-diagonal inertia tensor. We describe selected coarse-grained models used in molecular dynamics simulations, including the most popular MARTINI model developed by Marrink's group and the UNICORN model of biological macromolecules developed in our laboratory. We conclude by discussing examples of the application of coarse-grained molecular dynamics to study biologically important processes.
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Affiliation(s)
- Adam Liwo
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland; (C.C.); (A.K.S.); (A.G.L.); (S.A.S.)
| | - Cezary Czaplewski
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland; (C.C.); (A.K.S.); (A.G.L.); (S.A.S.)
| | - Adam K. Sieradzan
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland; (C.C.); (A.K.S.); (A.G.L.); (S.A.S.)
| | - Agnieszka G. Lipska
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland; (C.C.); (A.K.S.); (A.G.L.); (S.A.S.)
| | - Sergey A. Samsonov
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland; (C.C.); (A.K.S.); (A.G.L.); (S.A.S.)
| | - Rajesh K. Murarka
- Department of Chemistry, Indian Institute of Science Education and Research Bhopal, Bhopal Bypass Road, Bhopal 462066, MP, India;
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10
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Reilley DJ, Wang J, Dokholyan NV, Alexandrova AN. Titr-DMD-A Rapid, Coarse-Grained Quasi-All-Atom Constant pH Molecular Dynamics Framework. J Chem Theory Comput 2021; 17:4538-4549. [PMID: 34165292 PMCID: PMC10662685 DOI: 10.1021/acs.jctc.1c00338] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
The pH-dependence of enzyme fold stability and catalytic activity is a fundamentally dynamic, structural property which is difficult to study. The challenges and expense of investigating dynamic, atomic scale behavior experimentally means that computational methods, particularly constant pH molecular dynamics (CpHMD), are well situated tools for this. However, these methods often struggle with affordable sampling of sufficiently long time scales while also obtaining accurate pKa prediction and verifying the structures they generate. We introduce Titr-DMD, an affordable CpHMD method that combines the quasi-all-atom coarse-grained discrete molecular dynamics (DMD) method for conformational sampling with Propka for pKa prediction, to circumvent these issues. The combination enables rapid sampling on limited computational resources, while simulations are still performed on the atomic scale. We benchmark the method on a set of proteins with experimentally attested pKa and on the pH triggered conformational change in a staphylococcal nuclease mutant, a rare experimental study of such behavior. Our results show Titr-DMD to be an effective and inexpensive method to study pH-coupled protein dynamics.
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Affiliation(s)
- David J Reilley
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, California 90095-1569, United States
| | - Jian Wang
- Department of Pharmacology, Department of Biochemistry and Molecular Biology, Penn State University College of Medicine, Hershey, Pennsylvania 17033, United States
| | - Nikolay V Dokholyan
- Department of Pharmacology, Department of Biochemistry and Molecular Biology, Penn State University College of Medicine, Hershey, Pennsylvania 17033, United States
- Departments of Chemistry and Biomedical Engineering, Pennsylvania State University, University Park, Pennsylvania 16802, United States
| | - Anastassia N Alexandrova
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, California 90095-1569, United States
- California NanoSystems Institute, Los Angeles, California 90095-1569, United States
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11
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Giron CC, Laaksonen A, Barroso da Silva FL. Up State of the SARS-COV-2 Spike Homotrimer Favors an Increased Virulence for New Variants. FRONTIERS IN MEDICAL TECHNOLOGY 2021; 3:694347. [PMID: 35047936 PMCID: PMC8757851 DOI: 10.3389/fmedt.2021.694347] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Accepted: 05/31/2021] [Indexed: 12/23/2022] Open
Abstract
The COVID-19 pandemic has spread worldwide. However, as soon as the first vaccines-the only scientifically verified and efficient therapeutic option thus far-were released, mutations combined into variants of SARS-CoV-2 that are more transmissible and virulent emerged, raising doubts about their efficiency. This study aims to explain possible molecular mechanisms responsible for the increased transmissibility and the increased rate of hospitalizations related to the new variants. A combination of theoretical methods was employed. Constant-pH Monte Carlo simulations were carried out to quantify the stability of several spike trimeric structures at different conformational states and the free energy of interactions between the receptor-binding domain (RBD) and angiotensin-converting enzyme II (ACE2) for the most worrying variants. Electrostatic epitopes were mapped using the PROCEEDpKa method. These analyses showed that the increased virulence is more likely to be due to the improved stability to the S trimer in the opened state, in which the virus can interact with the cellular receptor, ACE2, rather than due to alterations in the complexation RBD-ACE2, since the difference observed in the free energy values was small (although more attractive in general). Conversely, the South African/Beta variant (B.1.351), compared with the SARS-CoV-2 wild type (wt), is much more stable in the opened state with one or two RBDs in the up position than in the closed state with three RBDs in the down position favoring the infection. Such results contribute to understanding the natural history of disease and indicate possible strategies for developing new therapeutic molecules and adjusting the vaccine doses for higher B-cell antibody production.
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Affiliation(s)
- Carolina Corrêa Giron
- Departamento de Ciências Biomoleculares, Faculdade de Ciências Farmacêuticas de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, Brazil
- Hospital de Clínicas, Universidade Federal do Triângulo Mineiro, Uberaba, Brazil
| | - Aatto Laaksonen
- Arrhenius Laboratory, Department of Materials and Environmental Chemistry, Stockholm University, Stockholm, Sweden
- State Key Laboratory of Materials-Oriented and Chemical Engineering, Nanjing Tech University, Nanjing, China
- Centre of Advanced Research in Bionanoconjugates and Biopolymers, Petru Poni Institute of Macromolecular Chemistry, Iasi, Romania
- Division of Energy Science, Department of Engineering Sciences and Mathematics, Luleå University of Technology, Luleå, Sweden
| | - Fernando Luís Barroso da Silva
- Departamento de Ciências Biomoleculares, Faculdade de Ciências Farmacêuticas de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, Brazil
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC, United States
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12
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Mugnai ML, Thirumalai D. Molecular Transfer Model for pH Effects on Intrinsically Disordered Proteins: Theory and Applications. J Chem Theory Comput 2021; 17:1944-1954. [PMID: 33566618 DOI: 10.1021/acs.jctc.0c01316] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
We present a theoretical method to study how changes in pH shape the heterogeneous conformational ensemble explored by intrinsically disordered proteins (IDPs). The theory is developed in the context of coarse-grained models, which enable a fast, accurate, and extensive exploration of conformational space at a given protonation state. In order to account for pH effects, we generalize the molecular transfer model (MTM), in which conformations are re-weighted using the transfer free energy, which is the free energy necessary for bringing to equilibrium in a new environment a "frozen" conformation of the system. Using the semi-grand ensemble, we derive an exact expression of the transfer free energy, which amounts to the appropriate summation over all the protonation states. Because the exact result is computationally too demanding to be useful for large polyelectrolytes or IDPs, we introduce a mean-field (MF) approximation of the transfer free energy. Using a lattice model, we compare the exact and MF results for the transfer free energy and a variety of observables associated with the model IDP. We find that the precise location of the charged groups (the sequence), and not merely the net charge, determines the structural properties. We demonstrate that some of the limitations previously noted for MF theory in the context of globular proteins are mitigated when disordered polymers are studied. The excellent agreement between the exact and MF results poises us to use the method presented here as a computational tool to study the properties of IDPs and other biological systems as a function of pH.
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Affiliation(s)
- Mauro Lorenzo Mugnai
- Department of Chemistry, The University of Texas at Austin, Austin, Texas 78712, United States
| | - D Thirumalai
- Department of Chemistry, The University of Texas at Austin, Austin, Texas 78712, United States
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13
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Poveda-Cuevas SA, Barroso da Silva FL, Etchebest C. How the Strain Origin of Zika Virus NS1 Protein Impacts Its Dynamics and Implications to Their Differential Virulence. J Chem Inf Model 2021; 61:1516-1530. [PMID: 33651942 DOI: 10.1021/acs.jcim.0c01377] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Viruses can impact and affect human populations in a severe way. The appropriate differentiation among several species or strains of viruses is one of the biggest challenges for virology and infectiology studies. The detection of measurables-quantified discrepancies allows for more accurate clinical diagnoses and treatments for viral diseases. In the present study, we have used a computational approach to explore the dynamical properties of the nonstructural protein 1 from two strains of Zika virus. Our results show that despite a high sequence similarity, the two viral proteins from different origins can exhibit significant dissimilar structural dynamics, which complement their reported differential virulence. The present study opens up new ways in the understanding of the infectivity for these biological entities.
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Affiliation(s)
- Sergio A Poveda-Cuevas
- Programa Interunidades em Bioinformática, Universidade de São Paulo, Rua do Matão, 1010, BR, 05508-090 São Paulo, São Paulo, Brazil.,Departamento de Ciências Biomoleculares, Faculdade de Ciências Farmacêuticas de Ribeirão Preto, Universidade de São Paulo, Av. do Café, s/no-Campus da USP, BR, 14040-903 Ribeirão Preto, São Paulo, Brazil.,University of São Paulo and Université de Paris International Laboratory in Structural Bioinformatics, Av. do Café, s/no-Campus da USP, Bloco B, BR, 14040-903 Ribeirão Preto, São Paulo, Brazil
| | - Fernando Luís Barroso da Silva
- Programa Interunidades em Bioinformática, Universidade de São Paulo, Rua do Matão, 1010, BR, 05508-090 São Paulo, São Paulo, Brazil.,Departamento de Ciências Biomoleculares, Faculdade de Ciências Farmacêuticas de Ribeirão Preto, Universidade de São Paulo, Av. do Café, s/no-Campus da USP, BR, 14040-903 Ribeirão Preto, São Paulo, Brazil.,Department of Chemical and Biomolecular Engineering, North Carolina State University, 27695 Raleigh, North Carolina, United States.,University of São Paulo and Université de Paris International Laboratory in Structural Bioinformatics, Av. do Café, s/no-Campus da USP, Bloco B, BR, 14040-903 Ribeirão Preto, São Paulo, Brazil
| | - Catherine Etchebest
- Institut National de la Transfusion Sanguine, 6 Rue Alexandre Cabanel, 75015 Paris, France.,Institut National de la Santé et de la Recherche Médicale, UMR_S 1134, Biologie Intégrée du Globule Rouge, Equipe 2, INSERM, Dynamique des Structures et des Interactions Moléculaires, F-75015 Paris, France.,Université de Paris, 5 Rue Thomas Mann, 75013 Paris, France.,University of São Paulo and Université de Paris International Laboratory in Structural Bioinformatics, Av. do Café, s/no-Campus da USP, Bloco B, BR, 14040-903 Ribeirão Preto, São Paulo, Brazil
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14
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Marchetto A, Si Chaib Z, Rossi CA, Ribeiro R, Pantano S, Rossetti G, Giorgetti A. CGMD Platform: Integrated Web Servers for the Preparation, Running, and Analysis of Coarse-Grained Molecular Dynamics Simulations. Molecules 2020; 25:E5934. [PMID: 33333836 PMCID: PMC7765266 DOI: 10.3390/molecules25245934] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Revised: 11/21/2020] [Accepted: 11/28/2020] [Indexed: 12/17/2022] Open
Abstract
Advances in coarse-grained molecular dynamics (CGMD) simulations have extended the use of computational studies on biological macromolecules and their complexes, as well as the interactions of membrane protein and lipid complexes at a reduced level of representation, allowing longer and larger molecular dynamics simulations. Here, we present a computational platform dedicated to the preparation, running, and analysis of CGMD simulations. The platform is built on a completely revisited version of our Martini coarsE gRained MembrAne proteIn Dynamics (MERMAID) web server, and it integrates this with other three dedicated services. In its current version, the platform expands the existing implementation of the Martini force field for membrane proteins to also allow the simulation of soluble proteins using the Martini and the SIRAH force fields. Moreover, it offers an automated protocol for carrying out the backmapping of the coarse-grained description of the system into an atomistic one.
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Affiliation(s)
- Alessandro Marchetto
- Department of Biotechnology, University of Verona, 37134 Verona, Italy; (A.M.); (C.A.R.); (R.R.)
- Computational Biomedicine, Institute for Neuroscience and Medicine (INM-9) and Institute for Advanced Simulations (IAS-5), Forschungszentrum Jülich, 52425 Jülich, Germany;
- Faculty of Mathematics, Computer Science and Natural Sciences, RWTH Aachen University, 52062 Aachen, Germany
| | - Zeineb Si Chaib
- Computational Biomedicine, Institute for Neuroscience and Medicine (INM-9) and Institute for Advanced Simulations (IAS-5), Forschungszentrum Jülich, 52425 Jülich, Germany;
- Faculty of Mathematics, Computer Science and Natural Sciences, RWTH Aachen University, 52062 Aachen, Germany
| | - Carlo Alberto Rossi
- Department of Biotechnology, University of Verona, 37134 Verona, Italy; (A.M.); (C.A.R.); (R.R.)
| | - Rui Ribeiro
- Department of Biotechnology, University of Verona, 37134 Verona, Italy; (A.M.); (C.A.R.); (R.R.)
| | - Sergio Pantano
- Institut Pasteur de Montevideo, Mataojo 2020, 11400 Montevideo, Uruguay;
| | - Giulia Rossetti
- Computational Biomedicine, Institute for Neuroscience and Medicine (INM-9) and Institute for Advanced Simulations (IAS-5), Forschungszentrum Jülich, 52425 Jülich, Germany;
- Jülich Supercomputing Center (JSC), Forschungszentrum Jülich, 52428 Jülich, Germany
- Department of Hematology, Oncology, Hemostaseology, and Stem Cell Transplantation, RWTH Aachen University, 52062 Aachen, Germany
| | - Alejandro Giorgetti
- Department of Biotechnology, University of Verona, 37134 Verona, Italy; (A.M.); (C.A.R.); (R.R.)
- Computational Biomedicine, Institute for Neuroscience and Medicine (INM-9) and Institute for Advanced Simulations (IAS-5), Forschungszentrum Jülich, 52425 Jülich, Germany;
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15
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Corrêa Giron C, Laaksonen A, Barroso da Silva FL. On the interactions of the receptor-binding domain of SARS-CoV-1 and SARS-CoV-2 spike proteins with monoclonal antibodies and the receptor ACE2. Virus Res 2020; 285:198021. [PMID: 32416259 PMCID: PMC7228703 DOI: 10.1016/j.virusres.2020.198021] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Revised: 05/01/2020] [Accepted: 05/11/2020] [Indexed: 01/12/2023]
Abstract
A new betacoronavirus named SARS-CoV-2 has emerged as a new threat to global health and economy. A promising target for both diagnosis and therapeutics treatments of the new disease named COVID-19 is the coronavirus (CoV) spike (S) glycoprotein. By constant-pH Monte Carlo simulations and the PROCEEDpKa method, we have mapped the electrostatic epitopes for four monoclonal antibodies and the angiotensin-converting enzyme 2 (ACE2) on both SARS-CoV-1 and the new SARS-CoV-2 S receptor binding domain (RBD) proteins. We also calculated free energy of interactions and shown that the S RBD proteins from both SARS viruses binds to ACE2 with similar affinities. However, the affinity between the S RBD protein from the new SARS-CoV-2 and ACE2 is higher than for any studied antibody previously found complexed with SARS-CoV-1. Based on physical chemical analysis and free energies estimates, we can shed some light on the involved molecular recognition processes, their clinical aspects, the implications for drug developments, and suggest structural modifications on the CR3022 antibody that would improve its binding affinities for SARS-CoV-2 and contribute to address the ongoing international health crisis.
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MESH Headings
- Angiotensin-Converting Enzyme 2
- Antibodies, Monoclonal/immunology
- Antibodies, Monoclonal/metabolism
- Antibodies, Viral/immunology
- Antibodies, Viral/metabolism
- Betacoronavirus/chemistry
- Betacoronavirus/immunology
- Computer Simulation
- Epitope Mapping
- Humans
- Models, Molecular
- Monte Carlo Method
- Peptidyl-Dipeptidase A/chemistry
- Peptidyl-Dipeptidase A/metabolism
- Protein Binding
- Protein Conformation
- Protein Interaction Domains and Motifs
- Protein Interaction Mapping
- Receptors, Virus/chemistry
- Receptors, Virus/metabolism
- Severe acute respiratory syndrome-related coronavirus/chemistry
- Severe acute respiratory syndrome-related coronavirus/immunology
- SARS-CoV-2
- Spike Glycoprotein, Coronavirus/chemistry
- Spike Glycoprotein, Coronavirus/immunology
- Spike Glycoprotein, Coronavirus/metabolism
- Thermodynamics
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Affiliation(s)
- Carolina Corrêa Giron
- Universidade Federal do Triângulo Mineiro, Departamento de Saúde Coletiva, Rua Vigário Carlos, 38025-350 Uberaba, MG, Brazil; Universidade de São Paulo, Departamento de Ciências Biomoleculares, Faculdade de Ciências Farmacêuticas de Ribeirão Preto, Av. café, s/no - campus da USP, BR-14040-903 Ribeirão Preto SP, Brazil
| | - Aatto Laaksonen
- Department of Materials and Environmental Chemistry, Arrhenius Laboratory, Stockholm University, SE-106 91 Stockholm, Sweden; State Key Laboratory of Materials-Oriented and Chemical Engineering, Nanjing Tech University, Nanjing, 210009, PR China; Centre of Advanced Research in Bionanoconjugates and Biopolymers, Petru Poni Institute of Macromolecular Chemistry, Aleea Grigore Ghica-Voda, 41A, 700487 Iasi, Romania; Department of Engineering Sciences and Mathematics, Division of Energy Science, Luleå University of Technology, SE-97187 Luleå, Sweden
| | - Fernando L Barroso da Silva
- Universidade de São Paulo, Departamento de Ciências Biomoleculares, Faculdade de Ciências Farmacêuticas de Ribeirão Preto, Av. café, s/no - campus da USP, BR-14040-903 Ribeirão Preto SP, Brazil; Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC 27695, United States.
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Barroso da Silva FL, Carloni P, Cheung D, Cottone G, Donnini S, Foegeding EA, Gulzar M, Jacquier JC, Lobaskin V, MacKernan D, Mohammad Hosseini Naveh Z, Radhakrishnan R, Santiso EE. Understanding and Controlling Food Protein Structure and Function in Foods: Perspectives from Experiments and Computer Simulations. Annu Rev Food Sci Technol 2020; 11:365-387. [PMID: 31951485 DOI: 10.1146/annurev-food-032519-051640] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
The structure and interactions of proteins play a critical role in determining the quality attributes of many foods, beverages, and pharmaceutical products. Incorporating a multiscale understanding of the structure-function relationships of proteins can provide greater insight into, and control of, the relevant processes at play. Combining data from experimental measurements, human sensory panels, and computer simulations through machine learning allows the construction of statistical models relating nanoscale properties of proteins to the physicochemical properties, physiological outcomes, and tastes of foods. This review highlights several examples of advanced computer simulations at molecular, mesoscale, and multiscale levels that shed light on the mechanisms at play in foods, thereby facilitating their control. It includes a practical simulation toolbox for those new to in silico modeling.
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Affiliation(s)
- Fernando Luís Barroso da Silva
- School of Pharmaceutical Sciences at Ribeirão Preto, University of São Paulo, BR-14040-903, Ribeirão Preto, São Paulo, Brazil
| | - Paolo Carloni
- Institute for Computational Biomedicine (IAS-5/INM-9), Forschungszentrum Jülich, 52425 Jülich, Germany.,Department of Physics, RWTH Aachen University, 52062 Aachen, Germany
| | - David Cheung
- School of Chemistry, National University of Ireland Galway, Galway, Ireland
| | - Grazia Cottone
- Department of Physics and Chemistry, University of Palermo, 90128 Palermo, Italy
| | - Serena Donnini
- Department of Biological and Environmental Science, University of Jyväskylä, Jyväskylä 40014, Finland
| | - E Allen Foegeding
- Department of Food, Bioprocessing, & Nutrition Sciences, North Carolina State University, Raleigh, North Carolina 27695, USA
| | - Muhammad Gulzar
- UCD School of Agriculture and Food Science, University College Dublin, Dublin 4, Ireland
| | | | | | - Donal MacKernan
- UCD School of Physics, University College Dublin, Dublin 4, Ireland
| | | | - Ravi Radhakrishnan
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, 19104, USA
| | - Erik E Santiso
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina 27695, USA
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17
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Devillers M, Piquemal J, Salmon L, Gresh N. Calibration of the dianionic phosphate group: Validation on the recognition site of the homodimeric enzyme phosphoglucose isomerase. J Comput Chem 2020; 41:839-854. [DOI: 10.1002/jcc.26134] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2019] [Revised: 11/28/2019] [Accepted: 12/05/2019] [Indexed: 12/14/2022]
Affiliation(s)
- Marion Devillers
- Equipe de Chimie Bioorganique et Bioinorganique, Institut de Chimie Moléculaire et des Matériaux d'Orsay (ICMMO), Univ Paris‐Saclay, Univ Paris‐Sud, UMR 8182 CNRS, rue du Doyen Georges Poitou F‐91405 Orsay France
| | - Jean‐Philip Piquemal
- Laboratoire de Chimie Théorique, Sorbonne Université, UMR 7616 CNRS Paris France
- Department of Biomolecular EngineeringThe University of Texas at Austin Texas 78712
| | - Laurent Salmon
- Equipe de Chimie Bioorganique et Bioinorganique, Institut de Chimie Moléculaire et des Matériaux d'Orsay (ICMMO), Univ Paris‐Saclay, Univ Paris‐Sud, UMR 8182 CNRS, rue du Doyen Georges Poitou F‐91405 Orsay France
| | - Nohad Gresh
- Laboratoire de Chimie Théorique, Sorbonne Université, UMR 7616 CNRS Paris France
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18
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Poveda-Cuevas SA, Etchebest C, Barroso da Silva FL. Identification of Electrostatic Epitopes in Flavivirus by Computer Simulations: The PROCEEDpKa Method. J Chem Inf Model 2019; 60:944-963. [DOI: 10.1021/acs.jcim.9b00895] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Affiliation(s)
- Sergio A. Poveda-Cuevas
- Universidade de São Paulo, Programa Interunidades em Bioinformática, Rua do Matão, 1010, BR, 05508-090 São Paulo, São Paulo, Brazil
- Universidade de São Paulo, Departamento de Ciências Biomoleculares, Faculdade de Ciências Farmacêuticas de Ribeirão Preto, Av. Café, s/no−Campus da USP, BR, 14040-903 Ribeirão Preto, São Paulo, Brazil
- University of São Paulo-Université Sorbonne Paris Cité International Laboratory in Structural Bioinformatics, Av. do Café, s/no−FCFRP, Bloco B, BR, 14040-903 Ribeirão Preto, São Paulo, Brazil
| | - Catherine Etchebest
- Université de Paris, Biologie Intégrée du Globule Rouge, UMR_S1134, BIGR, INSERM, F-75015 Paris, France
- Equipe 2, Dynamique des Structures et des Interactions Moléculaires, Université Paris Diderot−Paris 7, INTS, 6 Rue Alexandre Cabanel, 75015 Paris, France
- Laboratoire d’Excellence GR-Ex, Paris, France
- University of São Paulo-Université Sorbonne Paris Cité International Laboratory in Structural Bioinformatics, Av. do Café, s/no−FCFRP, Bloco B, BR, 14040-903 Ribeirão Preto, São Paulo, Brazil
| | - Fernando L. Barroso da Silva
- Universidade de São Paulo, Programa Interunidades em Bioinformática, Rua do Matão, 1010, BR, 05508-090 São Paulo, São Paulo, Brazil
- Universidade de São Paulo, Departamento de Ciências Biomoleculares, Faculdade de Ciências Farmacêuticas de Ribeirão Preto, Av. Café, s/no−Campus da USP, BR, 14040-903 Ribeirão Preto, São Paulo, Brazil
- University of São Paulo-Université Sorbonne Paris Cité International Laboratory in Structural Bioinformatics, Av. do Café, s/no−FCFRP, Bloco B, BR, 14040-903 Ribeirão Preto, São Paulo, Brazil
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina 27695, United States
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19
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Recent Advances in Coarse-Grained Models for Biomolecules and Their Applications. Int J Mol Sci 2019; 20:ijms20153774. [PMID: 31375023 PMCID: PMC6696403 DOI: 10.3390/ijms20153774] [Citation(s) in RCA: 65] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2019] [Revised: 07/28/2019] [Accepted: 07/30/2019] [Indexed: 12/23/2022] Open
Abstract
Molecular dynamics simulations have emerged as a powerful tool to study biological systems at varied length and timescales. The conventional all-atom molecular dynamics simulations are being used by the wider scientific community in routine to capture the conformational dynamics and local motions. In addition, recent developments in coarse-grained models have opened the way to study the macromolecular complexes for time scales up to milliseconds. In this review, we have discussed the principle, applicability and recent development in coarse-grained models for biological systems. The potential of coarse-grained simulation has been reviewed through state-of-the-art examples of protein folding and structure prediction, self-assembly of complexes, membrane systems and carbohydrates fiber models. The multiscale simulation approaches have also been discussed in the context of their emerging role in unravelling hierarchical level information of biosystems. We conclude this review with the future scope of coarse-grained simulations as a constantly evolving tool to capture the dynamics of biosystems.
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