1
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Skóra T. On the importance of the diffusivity gradient term in Brownian dynamics simulations. Biophys J 2024; 123:2638-2640. [PMID: 38897204 PMCID: PMC11365100 DOI: 10.1016/j.bpj.2024.05.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2024] [Revised: 05/17/2024] [Accepted: 05/31/2024] [Indexed: 06/21/2024] Open
Abstract
In a recent study, Garner et al. investigated diffusion in the cytoplasm of fission yeasts, revealing vast heterogeneity in intracellular viscosity. Their conclusion was based on a combination of single-particle-tracking experiments and Brownian dynamics simulations. However, in their simulations, the diffusivity gradient term has been neglected-an assumption common in some biophysical applications but unjustified in this particular case due to spatial variations in diffusivity. Here, we aim to comment on the importance of the diffusivity gradient term and the physical consequences of not including it. We also demonstrate that omitting this term likely leads to overestimating fission yeast intracellular viscosity variance and underestimating its mean. Additionally, we propose modifications to the simulations to incorporate the gradient term.
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Affiliation(s)
- Tomasz Skóra
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, Utah.
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2
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Joshi O, Skóra T, Yarema A, Rabbitt RD, Bidone TC. Contributions of the individual domains of α IIbβ 3 integrin to its extension: Insights from multiscale modeling. Cytoskeleton (Hoboken) 2024; 81:393-408. [PMID: 38682753 PMCID: PMC11333186 DOI: 10.1002/cm.21865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 04/09/2024] [Accepted: 04/10/2024] [Indexed: 05/01/2024]
Abstract
The platelet integrin αIIbβ3 undergoes long-range conformational transitions between bent and extended conformations to regulate platelet aggregation during hemostasis and thrombosis. However, how exactly αIIbβ3 transitions between conformations remains largely elusive. Here, we studied how transitions across bent and extended-closed conformations of αIIbβ3 integrin are regulated by effective interactions between its functional domains. We first carried out μs-long equilibrium molecular dynamics (MD) simulations of full-length αIIbβ3 integrins in bent and intermediate conformations, the latter characterized by an extended headpiece and closed legs. Then, we built heterogeneous elastic network models, perturbed inter-domain interactions, and evaluated their relative contributions to the energy barriers between conformations. Results showed that integrin extension emerges from: (i) changes in interfaces between functional domains; (ii) allosteric coupling of the head and upper leg domains with flexible lower leg domains. Collectively, these results provide new insights into integrin conformational activation based on short- and long-range interactions between its functional domains and highlight the importance of the lower legs in the regulation of integrin allostery.
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Affiliation(s)
- Onkar Joshi
- Department of Biomedical Engineering, University of Utah, Salt Lake City, Utah, USA
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, Utah, USA
| | - Tomasz Skóra
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, Utah, USA
| | - Anna Yarema
- Department of Biomedical Engineering, University of Utah, Salt Lake City, Utah, USA
| | - Richard D Rabbitt
- Department of Biomedical Engineering, University of Utah, Salt Lake City, Utah, USA
| | - Tamara C Bidone
- Department of Biomedical Engineering, University of Utah, Salt Lake City, Utah, USA
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, Utah, USA
- Department of Molecular Pharmaceutics, University of Utah, Salt Lake City, Utah, USA
- Department of Biochemistry, University of Utah, Salt Lake City, Utah, USA
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3
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Pirnia A, Maqdisi R, Mittal S, Sener M, Singharoy A. Perspective on Integrative Simulations of Bioenergetic Domains. J Phys Chem B 2024; 128:3302-3319. [PMID: 38562105 DOI: 10.1021/acs.jpcb.3c07335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Bioenergetic processes in cells, such as photosynthesis or respiration, integrate many time and length scales, which makes the simulation of energy conversion with a mere single level of theory impossible. Just like the myriad of experimental techniques required to examine each level of organization, an array of overlapping computational techniques is necessary to model energy conversion. Here, a perspective is presented on recent efforts for modeling bioenergetic phenomena with a focus on molecular dynamics simulations and its variants as a primary method. An overview of the various classical, quantum mechanical, enhanced sampling, coarse-grained, Brownian dynamics, and Monte Carlo methods is presented. Example applications discussed include multiscale simulations of membrane-wide electron transport, rate kinetics of ATP turnover from electrochemical gradients, and finally, integrative modeling of the chromatophore, a photosynthetic pseudo-organelle.
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Affiliation(s)
- Adam Pirnia
- School of Molecular Sciences, Arizona State University, Tempe, Arizona 85287-1004, United States
| | - Ranel Maqdisi
- School of Molecular Sciences, Arizona State University, Tempe, Arizona 85287-1004, United States
| | - Sumit Mittal
- VIT Bhopal University, Sehore 466114, Madhya Pradesh, India
| | - Melih Sener
- School of Molecular Sciences, Arizona State University, Tempe, Arizona 85287-1004, United States
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
| | - Abhishek Singharoy
- School of Molecular Sciences, Arizona State University, Tempe, Arizona 85287-1004, United States
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4
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Wu J, Jonniya NA, Hirakis SP, Olivieri C, Veglia G, Kornev AP, Taylor SS. Protein Kinase Structure and Dynamics: Role of the αC-β4 Loop. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.31.555822. [PMID: 37693538 PMCID: PMC10491255 DOI: 10.1101/2023.08.31.555822] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Although the αC-β4 loop is a stable feature of all protein kinases, the importance of this motif as a conserved element of secondary structure, as well as its links to the hydrophobic architecture of the kinase core, has been underappreciated. We first review the motif and then describe how it is linked to the hydrophobic spine architecture of the kinase core, which we first discovered using a computational tool, Local Spatial Pattern (LSP) alignment. Based on NMR predictions that a mutation in this motif abolishes the synergistic high-affinity binding of ATP and a pseudo substrate inhibitor, we used LSP to interrogate the F100A mutant. This comparison highlights the importance of the αC-β4 loop and key residues at the interface between the N- and C-lobes. In addition, we delved more deeply into the structure of the apo C-subunit, which lacks ATP. While apo C-subunit showed no significant changes in backbone dynamics of the αC-β4 loop, we found significant differences in the side chain dynamics of K105. The LSP analysis suggests disruption of communication between the N- and C-lobes in the F100A mutant, which would be consistent with the structural changes predicted by the NMR spectroscopy.
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Affiliation(s)
- Jian Wu
- Department of Pharmacology, University of California, San Diego, La Jolla, CA 92037-0654, USA
| | - Nisha A. Jonniya
- Department of Pharmacology, University of California, San Diego, La Jolla, CA 92037-0654, USA
| | - Sophia P. Hirakis
- Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, CA 92037-0654, USA
| | - Cristina Olivieri
- Department of Biochemistry, Molecular Biology, and Biophysics, University of Minnesota, MN 55455, USA
| | - Gianluigi Veglia
- Department of Biochemistry, Molecular Biology, and Biophysics, University of Minnesota, MN 55455, USA
- Department of Chemistry, University of Minnesota, MN 55455, USA
| | - Alexandr P. Kornev
- Department of Pharmacology, University of California, San Diego, La Jolla, CA 92037-0654, USA
| | - Susan S. Taylor
- Department of Pharmacology, University of California, San Diego, La Jolla, CA 92037-0654, USA
- Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, CA 92037-0654, USA
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5
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Danchin A. Science, method and critical thinking. Microb Biotechnol 2023; 16:1888-1894. [PMID: 37462943 PMCID: PMC10527184 DOI: 10.1111/1751-7915.14315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 07/03/2023] [Indexed: 09/28/2023] Open
Abstract
Science is founded on a method based on critical thinking. A prerequisite for this is not only a sufficient command of language but also the comprehension of the basic concepts underlying our understanding of reality. This constraint implies an awareness of the fact that the truth of the World is not directly accessible to us, but can only be glimpsed through the construction of models designed to anticipate its behaviour. Because the relationship between models and reality rests on the interpretation of founding postulates and instantiations of their predictions (and is therefore deeply rooted in language and culture), there can be no demarcation between science and non-science. However, critical thinking is essential to ensure that the link between models and reality is gradually made more adequate to reality, based on what has already been established, thus guaranteeing that science progresses on this basis and excluding any form of relativism.
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Affiliation(s)
- Antoine Danchin
- School of Biomedical Sciences, Li KaShing Faculty of MedicineHong Kong UniversityPokfulamHong KongChina
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6
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Słyk E, Skóra T, Kondrat S. Minimal Coarse-Grained Model for Immunoglobulin G: Diffusion and Binding under Crowding. J Phys Chem B 2023; 127:7442-7448. [PMID: 37591305 PMCID: PMC10476189 DOI: 10.1021/acs.jpcb.3c02383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Revised: 07/25/2023] [Indexed: 08/19/2023]
Abstract
Immunoglobulin G (IgG) is the most common type of antibody found in blood and extracellular fluids and plays an essential role in our immune response. However, studies of the dynamics and reaction kinetics of IgG-antigen binding under physiological crowding conditions are scarce. Herein, we develop a coarse-grained model of IgG consisting of only six beads that we find minimal for a coarse representation of IgG's shape and a decent reproduction of its flexibility and diffusion properties measured experimentally. Using this model in Brownian dynamics simulations, we find that macromolecular crowding affects only slightly the IgG's flexibility, as described by the distribution of angles between the IgG's arms and stem. Our simulations indicate that, contrary to expectations, crowders slow down the translational diffusion of an IgG less strongly than they do for a smaller Ficoll 70, which we relate to the IgG's conformational size changes induced by crowding. We also find that crowders affect the binding kinetics by decreasing the rate of the first binding step and enhancing the second binding step.
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Affiliation(s)
- Edyta Słyk
- Institute
of Physical Chemistry, Polish Academy of
Sciences, Warsaw 01-224, Poland
- Department
of Theoretical Chemistry, Institute of Chemical Sciences, Faculty
of Chemistry, Maria Curie-Skłodowska
University in Lublin, Lublin 20-031, Poland
| | - Tomasz Skóra
- Institute
of Physical Chemistry, Polish Academy of
Sciences, Warsaw 01-224, Poland
| | - Svyatoslav Kondrat
- Institute
of Physical Chemistry, Polish Academy of
Sciences, Warsaw 01-224, Poland
- Institute
for Computational Physics, University of
Stuttgart, Stuttgart 70569, Germany
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7
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Melo MCR, Bernardi RC. Fostering discoveries in the era of exascale computing: How the next generation of supercomputers empowers computational and experimental biophysics alike. Biophys J 2023; 122:2833-2840. [PMID: 36738105 PMCID: PMC10398237 DOI: 10.1016/j.bpj.2023.01.042] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 01/24/2023] [Accepted: 01/30/2023] [Indexed: 02/05/2023] Open
Abstract
Over a century ago, physicists started broadly relying on theoretical models to guide new experiments. Soon thereafter, chemists began doing the same. Now, biological research enters a new era when experiment and theory walk hand in hand. Novel software and specialized hardware became essential to understand experimental data and propose new models. In fact, current petascale computing resources already allow researchers to reach unprecedented levels of simulation throughput to connect in silico and in vitro experiments. The reduction in cost and improved access allowed a large number of research groups to adopt supercomputing resources and techniques. Here, we outline how large-scale computing has evolved to expand decades-old research, spark new research efforts, and continuously connect simulation and observation. For instance, multiple publicly and privately funded groups have dedicated extensive resources to develop artificial intelligence tools for computational biophysics, from accelerating quantum chemistry calculations to proposing protein structure models. Moreover, advances in computer hardware have accelerated data processing from single-molecule experimental observations and simulations of chemical reactions occurring throughout entire cells. The combination of software and hardware has opened the way for exascale computing and the production of the first public exascale supercomputer, Frontier, inaugurated by the Oak Ridge National Laboratory in 2022. Ultimately, the popularization and development of computational techniques and the training of researchers to use them will only accelerate the diversification of tools and learning resources for future generations.
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Affiliation(s)
- Marcelo C R Melo
- Auburn University, Department of Physics, Auburn University, Auburn, Alabama
| | - Rafael C Bernardi
- Auburn University, Department of Physics, Auburn University, Auburn, Alabama.
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8
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Skóra T, Janssen M, Carlson A, Kondrat S. Crowding-Regulated Binding of Divalent Biomolecules. PHYSICAL REVIEW LETTERS 2023; 130:258401. [PMID: 37418731 DOI: 10.1103/physrevlett.130.258401] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Accepted: 05/08/2023] [Indexed: 07/09/2023]
Abstract
Macromolecular crowding affects biophysical processes as diverse as diffusion, gene expression, cell growth, and senescence. Yet, there is no comprehensive understanding of how crowding affects reactions, particularly multivalent binding. Herein, we use scaled particle theory and develop a molecular simulation method to investigate the binding of monovalent to divalent biomolecules. We find that crowding can increase or reduce cooperativity-the extent to which the binding of a second molecule is enhanced after binding a first molecule-by orders of magnitude, depending on the sizes of the involved molecular complexes. Cooperativity generally increases when a divalent molecule swells and then shrinks upon binding two ligands. Our calculations also reveal that, in some cases, crowding enables binding that does not occur otherwise. As an immunological example, we consider immunoglobulin G-antigen binding and show that crowding enhances its cooperativity in bulk but reduces it when an immunoglobulin G binds antigens on a surface.
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Affiliation(s)
- Tomasz Skóra
- Institute of Physical Chemistry, Polish Academy of Sciences, 01-224 Warsaw, Poland
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, Utah 84112, USA
| | - Mathijs Janssen
- Department of Mathematics, Mechanics Division, University of Oslo, N-0851 Oslo, Norway
- Centre for Cancer Cell Reprogramming, Faculty of Medicine, University of Oslo, Montebello, N-0379 Oslo, Norway
- Norwegian University of Life Sciences, Faculty of Science and Technology, Pb 5003, 1433 Ås, Norway
| | - Andreas Carlson
- Department of Mathematics, Mechanics Division, University of Oslo, N-0851 Oslo, Norway
| | - Svyatoslav Kondrat
- Institute of Physical Chemistry, Polish Academy of Sciences, 01-224 Warsaw, Poland
- Institute for Computational Physics, University of Stuttgart, Stuttgart 70569, Germany
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9
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Kim SH, Kearns FL, Rosenfeld MA, Votapka L, Casalino L, Papanikolas M, Amaro RE, Freeman R. SARS-CoV-2 evolved variants optimize binding to cellular glycocalyx. CELL REPORTS. PHYSICAL SCIENCE 2023; 4:101346. [PMID: 37077408 PMCID: PMC10080732 DOI: 10.1016/j.xcrp.2023.101346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 02/07/2023] [Accepted: 03/07/2023] [Indexed: 05/03/2023]
Abstract
Viral variants of concern continue to arise for SARS-CoV-2, potentially impacting both methods for detection and mechanisms of action. Here, we investigate the effect of an evolving spike positive charge in SARS-CoV-2 variants and subsequent interactions with heparan sulfate and the angiotensin converting enzyme 2 (ACE2) in the glycocalyx. We show that the positively charged Omicron variant evolved enhanced binding rates to the negatively charged glycocalyx. Moreover, we discover that while the Omicron spike-ACE2 affinity is comparable to that of the Delta variant, the Omicron spike interactions with heparan sulfate are significantly enhanced, giving rise to a ternary complex of spike-heparan sulfate-ACE2 with a large proportion of double-bound and triple-bound ACE2. Our findings suggest that SARS-CoV-2 variants evolve to be more dependent on heparan sulfate in viral attachment and infection. This discovery enables us to engineer a second-generation lateral-flow test strip that harnesses both heparin and ACE2 to reliably detect all variants of concern, including Omicron.
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Affiliation(s)
- Sang Hoon Kim
- Department of Applied Physical Sciences, University of North Carolina - Chapel Hill, 1112 Murray Hall, CB#3050, Chapel Hill, NC 27599-2100, USA
| | - Fiona L Kearns
- Department of Chemistry and Biochemistry, University of California, San Diego, 4238 Urey Hall, MC-0340, La Jolla, CA 92093-0340, USA
| | - Mia A Rosenfeld
- Department of Chemistry and Biochemistry, University of California, San Diego, 4238 Urey Hall, MC-0340, La Jolla, CA 92093-0340, USA
| | - Lane Votapka
- Department of Chemistry and Biochemistry, University of California, San Diego, 4238 Urey Hall, MC-0340, La Jolla, CA 92093-0340, USA
| | - Lorenzo Casalino
- Department of Chemistry and Biochemistry, University of California, San Diego, 4238 Urey Hall, MC-0340, La Jolla, CA 92093-0340, USA
| | - Micah Papanikolas
- Department of Applied Physical Sciences, University of North Carolina - Chapel Hill, 1112 Murray Hall, CB#3050, Chapel Hill, NC 27599-2100, USA
| | - Rommie E Amaro
- Department of Chemistry and Biochemistry, University of California, San Diego, 4238 Urey Hall, MC-0340, La Jolla, CA 92093-0340, USA
| | - Ronit Freeman
- Department of Applied Physical Sciences, University of North Carolina - Chapel Hill, 1112 Murray Hall, CB#3050, Chapel Hill, NC 27599-2100, USA
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10
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Miao Y, Chang CEA, Zhu W, McCammon JA. Editorial: Mechanisms, thermodynamics and kinetics of ligand binding revealed from molecular simulations and machine learning. Front Mol Biosci 2023; 10:1139471. [PMID: 36733435 PMCID: PMC9887283 DOI: 10.3389/fmolb.2023.1139471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2023] [Accepted: 01/11/2023] [Indexed: 01/18/2023] Open
Affiliation(s)
- Yinglong Miao
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS, United States
| | - Chia-En A. Chang
- Department of Chemistry, University of California, Riverside, Riverside, CA, United States
| | - Weiliang Zhu
- Drug Discovery and Design Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China
| | - J. Andrew McCammon
- Departments of Chemistry & Biochemistry and Pharmacology, University of California San Diego, San Diego, San Diego, CA, United States
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11
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Matveev VV. Close agreement between deterministic versus stochastic modeling of first-passage time to vesicle fusion. Biophys J 2022; 121:4569-4584. [PMID: 36815708 PMCID: PMC9748373 DOI: 10.1016/j.bpj.2022.10.033] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Revised: 09/13/2022] [Accepted: 10/24/2022] [Indexed: 11/22/2022] Open
Abstract
Ca2+-dependent cell processes, such as neurotransmitter or endocrine vesicle fusion, are inherently stochastic due to large fluctuations in Ca2+ channel gating, Ca2+ diffusion, and Ca2+ binding to buffers and target sensors. However, previous studies revealed closer-than-expected agreement between deterministic and stochastic simulations of Ca2+ diffusion, buffering, and sensing if Ca2+ channel gating is not Ca2+ dependent. To understand this result more fully, we present a comparative study complementing previous work, focusing on Ca2+ dynamics downstream of Ca2+ channel gating. Specifically, we compare deterministic (mean-field/mass-action) and stochastic simulations of vesicle exocytosis latency, quantified by the probability density of the first-passage time (FPT) to the Ca2+-bound state of a vesicle fusion sensor, following a brief Ca2+ current pulse. We show that under physiological constraints, the discrepancy between FPT densities obtained using the two approaches remains small even if as few as ∼50 Ca2+ ions enter per single channel-vesicle release unit. Using a reduced two-compartment model for ease of analysis, we illustrate how this close agreement arises from the smallness of correlations between fluctuations of the reactant molecule numbers, despite the large magnitude of fluctuation amplitudes. This holds if all relevant reactions are heteroreaction between molecules of different species, as is the case for bimolecular Ca2+ binding to buffers and downstream sensor targets. In this case, diffusion and buffering effectively decorrelate the state of the Ca2+ sensor from local Ca2+ fluctuations. Thus, fluctuations in the Ca2+ sensor's state underlying the FPT distribution are only weakly affected by the fluctuations in the local Ca2+ concentration around its average, deterministically computable value.
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Affiliation(s)
- Victor V Matveev
- Department of Mathematical Sciences, New Jersey Institute of Technology, Newark, New Jersey.
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12
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Iwasa JH, Lyons B, Johnson GT. The dawn of interoperating spatial models in cell biology. Curr Opin Biotechnol 2022; 78:102838. [PMID: 36402095 DOI: 10.1016/j.copbio.2022.102838] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 06/01/2022] [Accepted: 10/07/2022] [Indexed: 11/18/2022]
Abstract
Spatial simulations are becoming an increasingly ubiquitous component in the cycle of discovery, experimentation, and communication across the sciences. In cell biology, many researchers share a vision of developing multiscale models that recapitulate observable behaviors spanning from atoms to cells to tissues. For this dream to become a reality, however, simulation technologies must provide a means for integration and interoperability as they advance. Already, the field has developed numerous methods that span scales of length, time, and complexity to create an extensive body of effective simulation approaches, and although these approaches rarely interoperate, they collectively cover a large spectrum of knowledge that future models may handle in a more unified manner. Here, we discuss the importance of making the data, workflows, and outputs of spatial simulations shareable and interoperable; and how democratization could encourage diverse biologists to participate more easily in developing models to advance our understanding of biological systems.
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Affiliation(s)
| | - Blair Lyons
- Visualization & Data Integration, Allen Institute for Cell Science, USA
| | - Graham T Johnson
- Visualization & Data Integration, Allen Institute for Cell Science, USA.
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13
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Subic T, Sbalzarini IF. A Gaussian jump process formulation of the reaction–diffusion master equation enables faster exact stochastic simulations. J Chem Phys 2022; 157:194110. [DOI: 10.1063/5.0123073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
We propose a Gaussian jump process model on a regular Cartesian lattice for the diffusion part of the Reaction–Diffusion Master Equation (RDME). We derive the resulting Gaussian RDME (GRDME) formulation from analogy with a kernel-based discretization scheme for continuous diffusion processes and quantify the limits of its validity relative to the classic RDME. We then present an exact stochastic simulation algorithm for the GRDME, showing that the accuracies of GRDME and RDME are comparable, but exact simulations of the GRDME require only a fraction of the computational cost of exact RDME simulations. We analyze the origin of this speedup and its scaling with problem dimension. The benchmarks suggest that the GRDME is a particularly beneficial model for diffusion-dominated systems in three dimensional spaces, often occurring in systems biology and cell biology.
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Affiliation(s)
- Tina Subic
- Technische Universität Dresden, Faculty of Computer Science, Dresden, Germany
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
- Center for Systems Biology Dresden, Dresden, Germany
| | - Ivo F. Sbalzarini
- Technische Universität Dresden, Faculty of Computer Science, Dresden, Germany
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
- Center for Systems Biology Dresden, Dresden, Germany
- Cluster of Excellence Physics of Life, TU Dresden, Dresden, Germany
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14
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Dey D, Nunes-Alves A, Wade RC, Schreiber G. Diffusion of small molecule drugs is affected by surface interactions and crowder proteins. iScience 2022; 25:105088. [PMID: 36157590 PMCID: PMC9490042 DOI: 10.1016/j.isci.2022.105088] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Revised: 08/04/2022] [Accepted: 08/31/2022] [Indexed: 11/30/2022] Open
Abstract
Crowded environments are known to affect the diffusion of macromolecules, but their effects on the diffusion of small molecules are largely uncharacterized. We investigate how three protein crowders, bovine serum albumin (BSA), hen egg-white lysozyme, and myoglobin, influence the diffusion rates and interactions of four small molecules: fluorescein, and three drugs, doxorubicin, glycogen synthase kinase-3 inhibitor SB216763, and quinacrine. Using Line-FRAP measurements, Brownian dynamics simulations, and molecular docking, we find that the diffusion rates of the small molecules are highly affected by self-aggregation, interactions with the proteins, and surface adsorption. The diffusion of fluorescein is decreased because of its interactions with the protein crowders and their surface adsorption. Protein crowders increase the diffusion rates of doxorubicin and SB216763 by reducing surface interactions and self-aggregation, respectively. Quinacrine diffusion was not affected by protein crowders. The mechanistic insights gained here may assist in optimization of compounds for higher mobility in complex macromolecular environments.
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Affiliation(s)
- Debabrata Dey
- Department of Biomolecular Sciences, Weizmann Institute of Science, Israel
| | - Ariane Nunes-Alves
- Molecular and Cellular Modeling Group, Heidelberg Institute for Theoretical Studies, Schloss-Wolfsbrunnenweg 35, 69118 Heidelberg, Germany.,Center for Molecular Biology (ZMBH), DKFZ-ZMBH Alliance, Heidelberg University, Im Neuenheimer Feld 282, 69120 Heidelberg, Germany
| | - Rebecca C Wade
- Molecular and Cellular Modeling Group, Heidelberg Institute for Theoretical Studies, Schloss-Wolfsbrunnenweg 35, 69118 Heidelberg, Germany.,Center for Molecular Biology (ZMBH), DKFZ-ZMBH Alliance, Heidelberg University, Im Neuenheimer Feld 282, 69120 Heidelberg, Germany.,Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, Im Neuenheimer Feld 205, Heidelberg, Germany
| | - Gideon Schreiber
- Department of Biomolecular Sciences, Weizmann Institute of Science, Israel
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15
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Hong X, Cholko T, Chang CEA, Wheeldon I. Multiscale simulation-guided design of enzyme bioconjugates with enhanced catalysis. CHEM CATALYSIS 2022; 2:2691-2703. [PMID: 36569428 PMCID: PMC9784400 DOI: 10.1016/j.checat.2022.09.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Biopolymer-scaffold modification is widely used to enhance enzyme catalysis. A central challenge is predicting the effects of scaffold position on enzyme properties. Here, we use a computational-experimental approach to develop a model for the effects of DNA scaffold position on enzyme kinetics. Using phosphotriesterase modified with a 20bp dsDNA, we demonstrate that conjugation position is as important as the scaffold's chemistry and structure. Multiscale simulations predict the effective substrate concentration increases close to the scaffold, which has μM-strength binding to the substrate. Kinetic analysis shows that the effective concentration that the scaffold provides is best utilized when positioned next to, but not blocking, the active site. At ~5Å distance between scaffold and active site a 7-fold increase in k cat /K M was achieved. A model that accounts for the substrate concentration as well PTE-DNA geometry accurately captures the kinetic enhancements, enabling prediction of the effect across a range of DNA positions.
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Affiliation(s)
- Xiao Hong
- Department of Biochemistry, University of California-Riverside, Riverside, CA, 92521
| | - Timothy Cholko
- Department of Chemistry, University of California-Riverside, Riverside, CA, 92521
| | - Chia-en A. Chang
- Department of Chemistry, University of California-Riverside, Riverside, CA, 92521
| | - Ian Wheeldon
- Department of Chemical and Environmental Engineering, University of California-Riverside, Riverside, CA, 92521
- Center for Industrial Biotechnology, University of California-Riverside, Riverside, CA, 92521
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16
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Vakser IA, Grudinin S, Jenkins NW, Kundrotas PJ, Deeds EJ. Docking-based long timescale simulation of cell-size protein systems at atomic resolution. Proc Natl Acad Sci U S A 2022; 119:e2210249119. [PMID: 36191203 PMCID: PMC9565162 DOI: 10.1073/pnas.2210249119] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Accepted: 09/02/2022] [Indexed: 01/03/2023] Open
Abstract
Computational methodologies are increasingly addressing modeling of the whole cell at the molecular level. Proteins and their interactions are the key component of cellular processes. Techniques for modeling protein interactions, thus far, have included protein docking and molecular simulation. The latter approaches account for the dynamics of the interactions but are relatively slow, if carried out at all-atom resolution, or are significantly coarse grained. Protein docking algorithms are far more efficient in sampling spatial coordinates. However, they do not account for the kinetics of the association (i.e., they do not involve the time coordinate). Our proof-of-concept study bridges the two modeling approaches, developing an approach that can reach unprecedented simulation timescales at all-atom resolution. The global intermolecular energy landscape of a large system of proteins was mapped by the pairwise fast Fourier transform docking and sampled in space and time by Monte Carlo simulations. The simulation protocol was parametrized on existing data and validated on a number of observations from experiments and molecular dynamics simulations. The simulation protocol performed consistently across very different systems of proteins at different protein concentrations. It recapitulated data on the previously observed protein diffusion rates and aggregation. The speed of calculation allows reaching second-long trajectories of protein systems that approach the size of the cells, at atomic resolution.
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Affiliation(s)
- Ilya A. Vakser
- Computational Biology Program, The University of Kansas, Lawrence, KS
- Department of Molecular Biosciences, The University of Kansas, Lawrence, KS
| | - Sergei Grudinin
- University of Grenoble Alpes, CNRS, Grenoble INP, LJK, Grenoble, France
| | - Nathan W. Jenkins
- Computational Biology Program, The University of Kansas, Lawrence, KS
| | | | - Eric J. Deeds
- Department of Integrative Biology and Physiology, Institute for Quantitative and Computational Biosciences, University of California, Los Angeles, CA
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17
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Votapka LW, Stokely AM, Ojha AA, Amaro RE. SEEKR2: Versatile Multiscale Milestoning Utilizing the OpenMM Molecular Dynamics Engine. J Chem Inf Model 2022; 62:3253-3262. [PMID: 35759413 PMCID: PMC9277580 DOI: 10.1021/acs.jcim.2c00501] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
![]()
We present SEEKR2
(simulation-enabled estimation of kinetic rates
version 2)—the latest iteration in the family of SEEKR programs
for using multiscale simulation methods to computationally estimate
the kinetics and thermodynamics of molecular processes, in particular,
ligand-receptor binding. SEEKR2 generates equivalent, or improved,
results compared to the earlier versions of SEEKR but with significant
increases in speed and capabilities. SEEKR2 has also been built with
greater ease of usability and with extensible features to enable future
expansions of the method. Now, in addition to supporting simulations
using NAMD, calculations may be run with the fast and extensible OpenMM
simulation engine. The Brownian dynamics portion of the calculation
has also been upgraded to Browndye 2. Furthermore, this version of
SEEKR supports hydrogen mass repartitioning, which significantly reduces
computational cost, while showing little, if any, loss of accuracy
in the predicted kinetics.
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Affiliation(s)
- Lane W Votapka
- University of California, San Diego, 9500 Gilman Dr., La Jolla, California 92093, United States
| | - Andrew M Stokely
- University of California, San Diego, 9500 Gilman Dr., La Jolla, California 92093, United States
| | - Anupam A Ojha
- University of California, San Diego, 9500 Gilman Dr., La Jolla, California 92093, United States
| | - Rommie E Amaro
- University of California, San Diego, 9500 Gilman Dr., La Jolla, California 92093, United States
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18
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Ahn SH, Huber GA, McCammon JA. Investigating Intrinsically Disordered Proteins With Brownian Dynamics. Front Mol Biosci 2022; 9:898838. [PMID: 35755809 PMCID: PMC9213797 DOI: 10.3389/fmolb.2022.898838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Accepted: 05/17/2022] [Indexed: 11/30/2022] Open
Abstract
Intrinsically disordered proteins (IDPs) have recently become systems of great interest due to their involvement in modulating many biological processes and their aggregation being implicated in many diseases. Since IDPs do not have a stable, folded structure, however, they cannot be easily studied with experimental techniques. Hence, conducting a computational study of these systems can be helpful and be complementary with experimental work to elucidate their mechanisms. Thus, we have implemented the coarse-grained force field for proteins (COFFDROP) in Browndye 2.0 to study IDPs using Brownian dynamics (BD) simulations, which are often used to study large-scale motions with longer time scales and diffusion-limited molecular associations. Specifically, we have checked our COFFDROP implementation with eight naturally occurring IDPs and have investigated five (Glu-Lys)25 IDP sequence variants. From measuring the hydrodynamic radii of eight naturally occurring IDPs, we found the ideal scaling factor of 0.786 for non-bonded interactions. We have also measured the entanglement indices (average C α distances to the other chain) between two (Glu-Lys)25 IDP sequence variants, a property related to molecular association. We found that entanglement indices decrease for all possible pairs at excess salt concentration, which is consistent with long-range interactions of these IDP sequence variants getting weaker at increasing salt concentration.
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Affiliation(s)
- Surl-Hee Ahn
- Department of Chemistry and Biochemistry, University of California, San Diego, San Diego, CA, United States
| | - Gary A. Huber
- Department of Chemistry and Biochemistry, University of California, San Diego, San Diego, CA, United States
- Department of Pharmacology, University of California, San Diego, San Diego, CA, United States
| | - J. Andrew McCammon
- Department of Chemistry and Biochemistry, University of California, San Diego, San Diego, CA, United States
- Department of Pharmacology, University of California, San Diego, San Diego, CA, United States
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19
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Cholko T, Kaushik S, Wu KY, Montes R, Chang CEA. GeomBD3: Brownian Dynamics Simulation Software for Biological and Engineered Systems. J Chem Inf Model 2022; 62:2257-2263. [PMID: 35549473 DOI: 10.1021/acs.jcim.1c01387] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
GeomBD3 is a robust Brownian dynamics simulation package designed to easily handle natural or engineered systems in diverse environments and arrangements. The software package described herein allows users to design, execute, and analyze BD simulations. The simulations use all-atom, rigid molecular models that diffuse according to overdamped Langevin dynamics and interact through electrostatic, Lennard-Jones, and ligand desolvation potentials. The program automatically calculates molecular association rates, surface residence times, and association statistics for any number of user-defined association criteria. Users can also extract molecular association pathways, diffusion coefficients, intermolecular interaction energies, intermolecular contact probability maps, and more using the provided supplementary analysis scripts. We detail the use of the package from start to finish and apply it to a protein-ligand system and a large nucleic acid biosensor. GeomBD3 provides a versatile tool for researchers from various disciplines that can aid in rational design of engineered systems or play an explanatory role as a complement to experiments. GeomBD version 3 is available on our website at http://chemcha-gpu0.ucr.edu/geombd3/ and KBbox at https://kbbox.h-its.org/toolbox/methods/molecular-simulation/geombd/.
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Affiliation(s)
- Timothy Cholko
- Department of Chemistry, University of California, Riverside, Riverside, California 92521, United States
| | - Shivansh Kaushik
- Department of Chemistry, University of California, Riverside, Riverside, California 92521, United States
| | - Kingsley Y Wu
- Department of Chemistry, University of California, Riverside, Riverside, California 92521, United States
| | - Ruben Montes
- Department of Chemistry, University of California, Riverside, Riverside, California 92521, United States
| | - Chia-En A Chang
- Department of Chemistry, University of California, Riverside, Riverside, California 92521, United States
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20
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Shen X, Song J, Sevencan C, Leong DT, Ariga K. Bio-interactive nanoarchitectonics with two-dimensional materials and environments. SCIENCE AND TECHNOLOGY OF ADVANCED MATERIALS 2022; 23:199-224. [PMID: 35370475 PMCID: PMC8973389 DOI: 10.1080/14686996.2022.2054666] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Revised: 03/12/2022] [Accepted: 03/15/2022] [Indexed: 05/19/2023]
Abstract
Like the proposal of nanotechnology by Richard Feynman, the nanoarchitectonics concept was initially proposed by Masakazu Aono. The nanoarchitectonics strategy conceptually fuses nanotechnology with other research fields including organic chemistry, supramolecular chemistry, micro/nanofabrication, materials science, and bio-related sciences, and aims to produce functional materials from nanoscale components. In this review article, bio-interactive nanoarchitectonics and two-dimensional materials and environments are discussed as a selected topic. The account gives general examples of nanoarchitectonics of two-dimensional materials for energy storage, catalysis, and biomedical applications, followed by explanations of bio-related applications with two-dimensional materials such as two-dimensional biomimetic nanosheets, fullerene nanosheets, and two-dimensional assemblies of one-dimensional fullerene nanowhiskers (FNWs). The discussion on bio-interactive nanoarchitectonics in two-dimensional environments further extends to liquid-liquid interfaces such as fluorocarbon-medium interfaces and viscous liquid interfaces as new frontiers of two-dimensional environments for bio-related applications. Controlling differentiation of stem cells at fluidic liquid interfaces is also discussed. Finally, a conclusive section briefly summarizes features of bio-interactive nanoarchitectonics with two-dimensional materials and environments and discusses possible future perspectives.
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Affiliation(s)
- Xuechen Shen
- Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan
- WPI Research Center for Materials Nanoarchitectonics (MANA), National Institute for Materials Science (NIMS), Ibaraki, Japan
| | - Jingwen Song
- Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan
- WPI Research Center for Materials Nanoarchitectonics (MANA), National Institute for Materials Science (NIMS), Ibaraki, Japan
| | - Cansu Sevencan
- Department of Chemical and Biomolecular Engineering, National University of Singapore, Singapore, Singapore
| | - David Tai Leong
- Department of Chemical and Biomolecular Engineering, National University of Singapore, Singapore, Singapore
| | - Katsuhiko Ariga
- Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan
- WPI Research Center for Materials Nanoarchitectonics (MANA), National Institute for Materials Science (NIMS), Ibaraki, Japan
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21
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Edwards T, Foloppe N, Harris SA, Wells G. The future of biomolecular simulation in the pharmaceutical industry: what we can learn from aerodynamics modelling and weather prediction. Part 1. understanding the physical and computational complexity of in silico drug design. Acta Crystallogr D Struct Biol 2021; 77:1348-1356. [PMID: 34726163 PMCID: PMC8561735 DOI: 10.1107/s2059798321009712] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Accepted: 09/17/2021] [Indexed: 02/04/2023] Open
Abstract
The predictive power of simulation has become embedded in the infrastructure of modern economies. Computer-aided design is ubiquitous throughout industry. In aeronautical engineering, built infrastructure and materials manufacturing, simulations are routinely used to compute the performance of potential designs before construction. The ability to predict the behaviour of products is a driver of innovation by reducing the cost barrier to new designs, but also because radically novel ideas can be piloted with relatively little risk. Accurate weather forecasting is essential to guide domestic and military flight paths, and therefore the underpinning simulations are critical enough to have implications for national security. However, in the pharmaceutical and biotechnological industries, the application of computer simulations remains limited by the capabilities of the technology with respect to the complexity of molecular biology and human physiology. Over the last 30 years, molecular-modelling tools have gradually gained a degree of acceptance in the pharmaceutical industry. Drug discovery has begun to benefit from physics-based simulations. While such simulations have great potential for improved molecular design, much scepticism remains about their value. The motivations for such reservations in industry and areas where simulations show promise for efficiency gains in preclinical research are discussed. In this, the first of two complementary papers, the scientific and technical progress that needs to be made to improve the predictive power of biomolecular simulations, and how this might be achieved, is firstly discussed (Part 1). In Part 2, the status of computer simulations in pharma is contrasted with aerodynamics modelling and weather forecasting, and comments are made on the cultural changes needed for equivalent computational technologies to become integrated into life-science industries.
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Affiliation(s)
- Tom Edwards
- School of Molecular and Cellular Biology, University of Leeds, Leeds, United Kingdom
- Astbury Centre for Structural and Molecular Biology, University of Leeds, Leeds, United Kingdom
| | | | - Sarah Anne Harris
- Astbury Centre for Structural and Molecular Biology, University of Leeds, Leeds, United Kingdom
- School of Physics and Astronomy, University of Leeds, Leeds, United Kingdom
| | - Geoff Wells
- School of Pharmacy, University College London, London, United Kingdom
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22
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Kaushik S, Chang CEA. Molecular Mechanics Study of Flow and Surface Influence in Ligand-Protein Association. Front Mol Biosci 2021; 8:659687. [PMID: 34041265 PMCID: PMC8142692 DOI: 10.3389/fmolb.2021.659687] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Accepted: 04/06/2021] [Indexed: 11/13/2022] Open
Abstract
Ligand–protein association is the first and critical step for many biological and chemical processes. This study investigated the molecular association processes under different environments. In biology, cells have different compartments where ligand–protein binding may occur on a membrane. In experiments involving ligand–protein binding, such as the surface plasmon resonance and continuous flow biosynthesis, a substrate flow and surface are required in experimental settings. As compared with a simple binding condition, which includes only the ligand, protein, and solvent, the association rate and processes may be affected by additional ligand transporting forces and other intermolecular interactions between the ligand and environmental objects. We evaluated these environmental factors by using a ligand xk263 binding to HIV protease (HIVp) with atomistic details. Using Brownian dynamics simulations, we modeled xk263 and HIVp association time and probability when a system has xk263 diffusion flux and a non-polar self-assembled monolayer surface. We also examined different protein orientations and accessible surfaces for xk263. To allow xk263 to access to the dimer interface of immobilized HIVp, we simulated the system by placing the protein 20Å above the surface because immobilizing HIVp on a surface prevented xk263 from contacting with the interface. The non-specific interactions increased the binding probability while the association time remained unchanged. When the xk263 diffusion flux increased, the effective xk263 concentration around HIVp, xk263–HIVp association time and binding probability decreased non-linearly regardless of interacting with the self-assembled monolayer surface or not. The work sheds light on the effects of the solvent flow and surface environment on ligand–protein associations and provides a perspective on experimental design.
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Affiliation(s)
- Shivansh Kaushik
- Department of Chemistry, University of Chemistry, Riverside, CA, United States
| | - Chia-En A Chang
- Department of Chemistry, University of Chemistry, Riverside, CA, United States
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23
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Wilson MA, Pohorille A. Electrophysiological Properties from Computations at a Single Voltage: Testing Theory with Stochastic Simulations. ENTROPY 2021; 23:e23050571. [PMID: 34066581 PMCID: PMC8148522 DOI: 10.3390/e23050571] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 04/24/2021] [Accepted: 04/28/2021] [Indexed: 12/13/2022]
Abstract
We use stochastic simulations to investigate the performance of two recently developed methods for calculating the free energy profiles of ion channels and their electrophysiological properties, such as current–voltage dependence and reversal potential, from molecular dynamics simulations at a single applied voltage. These methods require neither knowledge of the diffusivity nor simulations at multiple voltages, which greatly reduces the computational effort required to probe the electrophysiological properties of ion channels. They can be used to determine the free energy profiles from either forward or backward one-sided properties of ions in the channel, such as ion fluxes, density profiles, committor probabilities, or from their two-sided combination. By generating large sets of stochastic trajectories, which are individually designed to mimic the molecular dynamics crossing statistics of models of channels of trichotoxin, p7 from hepatitis C and a bacterial homolog of the pentameric ligand-gated ion channel, GLIC, we find that the free energy profiles obtained from stochastic simulations corresponding to molecular dynamics simulations of even a modest length are burdened with statistical errors of only 0.3 kcal/mol. Even with many crossing events, applying two-sided formulas substantially reduces statistical errors compared to one-sided formulas. With a properly chosen reference voltage, the current–voltage curves can be reproduced with good accuracy from simulations at a single voltage in a range extending for over 200 mV. If possible, the reference voltages should be chosen not simply to drive a large current in one direction, but to observe crossing events in both directions.
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Affiliation(s)
- Michael A. Wilson
- Exobiology Branch, MS 239-4, NASA Ames Research Center, Moffett Field, CA 94035, USA;
- SETI Institute, 189 Bernardo Ave, Suite 200, Mountain View, CA 94043, USA
| | - Andrew Pohorille
- Exobiology Branch, MS 239-4, NASA Ames Research Center, Moffett Field, CA 94035, USA;
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA 94132, USA
- Correspondence: ; Tel.: +1-650-604-5759
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24
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Zhang Z, Ricci CG, Fan C, Cheng LT, Li B, McCammon JA. Coupling Monte Carlo, Variational Implicit Solvation, and Binary Level-Set for Simulations of Biomolecular Binding. J Chem Theory Comput 2021; 17:2465-2478. [PMID: 33650860 DOI: 10.1021/acs.jctc.0c01109] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
We develop a hybrid approach that combines the Monte Carlo (MC) method, a variational implicit-solvent model (VISM), and a binary level-set method for the simulation of biomolecular binding in an aqueous solvent. The solvation free energy for the biomolecular complex is estimated by minimizing the VISM free-energy functional of all possible solute-solvent interfaces that are used as dielectric boundaries. This functional consists of the solute volumetric, solute-solvent interfacial, solute-solvent van der Waals interaction, and electrostatic free energy. A technique of shifting the dielectric boundary is used to accurately predict the electrostatic part of the solvation free energy. Minimizing such a functional in each MC move is made possible by our new and fast binary level-set method. This method is based on the approximation of surface area by the convolution of an indicator function with a compactly supported kernel and is implemented by simple flips of numerical grid cells locally around the solute-solvent interface. We apply our approach to the p53-MDM2 system for which the two molecules are approximated by rigid bodies. Our efficient approach captures some of the poses before the final bound state. All-atom molecular dynamics simulations with most of such poses quickly reach the final bound state. Our work is a new step toward realistic simulations of biomolecular interactions. With further improvement of coarse graining and MC sampling, and combined with other models, our hybrid approach can be used to study the free-energy landscape and kinetic pathways of ligand binding to proteins.
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Affiliation(s)
- Zirui Zhang
- Department of Mathematics, University of California, San Diego, La Jolla, California 92093-0112, United States
| | - Clarisse G Ricci
- Department of Chemistry and Biochemistry and Department of Pharmacology, University of California, San Diego, La Jolla, California 92093-0365, United States
| | - Chao Fan
- Department of Mathematics, University of California, San Diego, La Jolla, California 92093-0112, United States
| | - Li-Tien Cheng
- Department of Mathematics, University of California, San Diego, La Jolla, California 92093-0112, United States
| | - Bo Li
- Department of Mathematics and Quantitative Biology Ph.D. Program, University of California, San Diego, La Jolla, California 92093-0112, United States
| | - J Andrew McCammon
- Department of Chemistry and Biochemistry and Department of Pharmacology, University of California, San Diego, La Jolla, California 92093-0365, United States
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25
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Fadda E. Understanding the Structure and Function of Viral Glycosylation by Molecular Simulations: State-of-the-Art and Recent Case Studies. COMPREHENSIVE GLYCOSCIENCE 2021. [PMCID: PMC7834635 DOI: 10.1016/b978-0-12-819475-1.00056-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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26
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Multiscale Simulations Examining Glycan Shield Effects on Drug Binding to Influenza Neuraminidase. Biophys J 2020; 119:2275-2289. [PMID: 33130120 DOI: 10.1016/j.bpj.2020.10.024] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Revised: 10/08/2020] [Accepted: 10/21/2020] [Indexed: 12/18/2022] Open
Abstract
Influenza neuraminidase is an important drug target. Glycans are present on neuraminidase and are generally considered to inhibit antibody binding via their glycan shield. In this work, we studied the effect of glycans on the binding kinetics of antiviral drugs to the influenza neuraminidase. We created all-atom in silico systems of influenza neuraminidase with experimentally derived glycoprofiles consisting of four systems with different glycan conformations and one system without glycans. Using Brownian dynamics simulations, we observe a two- to eightfold decrease in the rate of ligand binding to the primary binding site of neuraminidase due to the presence of glycans. These glycans are capable of covering much of the surface area of neuraminidase, and the ligand binding inhibition is derived from glycans sterically occluding the primary binding site on a neighboring monomer. Our work also indicates that drugs preferentially bind to the primary binding site (i.e., the active site) over the secondary binding site, and we propose a binding mechanism illustrating this. These results help illuminate the complex interplay between glycans and ligand binding on the influenza membrane protein neuraminidase.
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27
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Ding F, Peng W, Peng YK, Liu BQ. Elucidating the potential neurotoxicity of chiral phenthoate: Molecular insight from experimental and computational studies. CHEMOSPHERE 2020; 255:127007. [PMID: 32416396 DOI: 10.1016/j.chemosphere.2020.127007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2020] [Revised: 05/05/2020] [Accepted: 05/06/2020] [Indexed: 06/11/2023]
Abstract
Chiral organophosphorus pollutants are existed ubiquitously in the ecological environment, but the enantioselective toxicities of these nerve agents to humans and their molecular bases have not been fully elucidated. Using experimental and computational approaches, this story was to explore the neurotoxic response process of the target acetylcholinesterase (AChE) to chiral phenthoate and further decipher the microscopic mechanism of such toxicological effect at the enantiomeric level. The results showed that the toxic reaction of AChE with chiral phenthoate exhibited significant enantioselectivity, and (R)-phenthoate (K=1.486 × 105 M-1) has a bioaffinity for the nerve enzyme nearly three times that of (S)-phenthoate (K=4.503 × 104 M-1). Dynamic research outcomes interpreted the wet experiments, and the inherent conformational flexibility of the target enzyme has a great influence on the enantioselective neurotoxicological action processes, especially reflected in the conformational changes of the three key loop regions (i.e. residues His-447, Gly-448, and Tyr-449; residues Gly-122, Phe-123, and Tyr-124; and residues Thr-75, Leu-76, and Tyr-77) around the reaction patch. This was supported by the quantitative results of conformational studies derived from circular dichroism spectroscopy (α-helix: 34.7%→30.2%/31.6%; β-sheet: 23.6%→19.5%/20.7%; turn: 19.2%→22.4%/21.9%; and random coil: 22.5%→27.9%/25.8%). Meanwhile, via analyzing the modes of toxic action and free energies, we can find that (R)-phenthoate has a strong inhibitory effect on the enzymatic activity of AChE, as compared with (S)-phenthoate, and electrostatic energy (-23.79/-17.77 kJ mol-1) played a critical role in toxicological reactions. These points were the underlying causes of chiral phenthoate displaying different degrees of enantioselective neurotoxicity.
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Affiliation(s)
- Fei Ding
- Department of Environmental Science and Engineering, School of Water and Environment, Chang'an University, Xi'an, 710054, China; Key Laboratory of Subsurface Hydrology and Ecological Effect in Arid Region of Ministry of Education, Chang'an University, No. 126 Yanta Road, Yanta District, Xi'an, 710054, China
| | - Wei Peng
- State Key Laboratory of Physical Chemistry of Solid Surfaces and Fujian Provincial Key Laboratory of Theoretical and Computational Chemistry, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, 361005, China.
| | - Yu-Kui Peng
- Center for Food Quality Supervision, Inspection & Testing, Ministry of Agriculture and Rural Affairs, Northwest A&F University, Yangling, 712100, China
| | - Bing-Qi Liu
- Department of Agricultural Chemistry, Qingdao Agricultural University, Qingdao, 266109, China
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28
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Ding F, Peng W, Peng YK, Liu BQ. Estimating the potential toxicity of chiral diclofop-methyl: Mechanistic insight into the enantioselective behavior. Toxicology 2020; 438:152446. [DOI: 10.1016/j.tox.2020.152446] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Revised: 02/26/2020] [Accepted: 03/25/2020] [Indexed: 02/06/2023]
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29
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Jagger BR, Kochanek SE, Haldar S, Amaro RE, Mulholland AJ. Multiscale simulation approaches to modeling drug-protein binding. Curr Opin Struct Biol 2020; 61:213-221. [PMID: 32113133 DOI: 10.1016/j.sbi.2020.01.014] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Revised: 01/16/2020] [Accepted: 01/21/2020] [Indexed: 01/19/2023]
Abstract
Simulations can provide detailed insight into the molecular processes involved in drug action, such as protein-ligand binding, and can therefore be a valuable tool for drug design and development. Processes with a large range of length and timescales may be involved, and understanding these different scales typically requires different types of simulation methodology. Ideally, simulations should be able to connect across scales, to analyze and predict how changes at one scale can influence another. Multiscale simulation methods, which combine different levels of treatment, are an emerging frontier with great potential in this area. Here we review multiscale frameworks of various types, and selected applications to biomolecular systems with a focus on drug-ligand binding.
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Affiliation(s)
- Benjamin R Jagger
- Department of Chemistry and Biochemistry, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, United States
| | - Sarah E Kochanek
- Department of Chemistry and Biochemistry, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, United States
| | - Susanta Haldar
- Centre for Computational Chemistry, School of Chemistry, University of Bristol, Bristol, BS8 1TS, UK
| | - Rommie E Amaro
- Department of Chemistry and Biochemistry, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, United States.
| | - Adrian J Mulholland
- Centre for Computational Chemistry, School of Chemistry, University of Bristol, Bristol, BS8 1TS, UK.
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