151
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Jedwabny W, Dyguda-Kazimierowicz E, Pernal K, Szalewicz K, Patkowski K. Extension of an Atom-Atom Dispersion Function to Halogen Bonds and Its Use for Rational Design of Drugs and Biocatalysts. J Phys Chem A 2021; 125:1787-1799. [PMID: 33620223 PMCID: PMC8028329 DOI: 10.1021/acs.jpca.0c11347] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 02/10/2021] [Indexed: 12/17/2022]
Abstract
A dispersion function Das in the form of a damped atom-atom asymptotic expansion fitted to ab initio dispersion energies from symmetry-adapted perturbation theory was improved and extended to systems containing heavier halogen atoms. To illustrate its performance, the revised Das function was implemented in the multipole first-order electrostatic and second-order dispersion (MED) scoring model. The extension has allowed applications to a much larger set of biocomplexes than it was possible with the original Das. A reasonable correlation between MED and experimentally determined inhibitory activities was achieved in a number of test cases, including structures featuring nonphysically shortened intermonomer distances, which constitute a particular challenge for binding strength predictions. Since the MED model is also computationally efficient, it can be used for reliable and rapid assessment of the ligand affinity or multidimensional scanning of amino acid side-chain conformations in the process of rational design of novel drugs or biocatalysts.
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Affiliation(s)
- Wiktoria Jedwabny
- Department
of Chemistry, Wrocław University of
Science and Technology, Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland
| | - Edyta Dyguda-Kazimierowicz
- Department
of Chemistry, Wrocław University of
Science and Technology, Wybrzeże Wyspiańskiego 27, 50-370 Wrocław, Poland
| | - Katarzyna Pernal
- Institute
of Physics, Łódź University
of Technology, Wólczańska
219, 90-924 Łódź, Poland
| | - Krzysztof Szalewicz
- Department
of Physics and Astronomy, University of
Delaware, Newark, Delaware 19716, United
States
| | - Konrad Patkowski
- Department
of Chemistry and Biochemistry, Auburn University, Auburn, Alabama 36849, United States
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152
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Bekono BD, Sona AN, Eni DB, Owono LCO, Megnassan E, Ntie-Kang F. Molecular mechanics approaches for rational drug design: forcefields and solvation models. PHYSICAL SCIENCES REVIEWS 2021. [DOI: 10.1515/psr-2019-0128] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Abstract
The use of molecular mechanics (MM) in understanding the energy and target of a drug, its structures, and properties has increased recently. This is achieved by the formulation of a simple MM energy equation, which represents the sum of the different energy interactions, often referred to as “forcefields” (FFs). The concept of FFs is now widely used as one of the fundamental tools for the in silico prediction of drug-target interactions. To generate more accurate predictions in the in silico drug discovery projects, the solvent effects are often taken into account. This review seeks to present an introductory guide for the reader on the fundamentals of MM with special emphasis on the role of FFs and the solvation models.
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Affiliation(s)
- Boris D. Bekono
- Department of Physics, Ecole Normale Supérieure , University of Yaoundé I , P.O. Box 47 , Yaoundé , Cameroon
| | - Alfred N. Sona
- Department of Chemistry , University of Buea , P.O. Box 63 , Buea , Cameroon
| | - Donatus B. Eni
- Department of Chemistry , University of Buea , P.O. Box 63 , Buea , Cameroon
- Department of Inorganic Chemistry, Faculty of Science , University of Yaoundé I , BP 812 , Yaoundé , Cameroon
| | - Luc C. O. Owono
- Department of Physics, Ecole Normale Supérieure , University of Yaoundé I , P.O. Box 47 , Yaoundé , Cameroon
- CEPAMOQ, Faculty of Science , University of Douala , P.O. Box 8580 , Douala , Cameroon
| | - Eugène Megnassan
- Laboratoire de Physique Fondamentale et Appliquée (LPFA) , University of Abobo-Adjamé (now Nangui Abrogoua) , Abidjan 02 , Côte d’Ivoire
| | - Fidele Ntie-Kang
- Department of Chemistry , University of Buea , P.O. Box 63 , Buea , Cameroon
- Department of Pharmaceutical Chemistry , Martin-Luther University Halle-Wittenberg , Kurt-Mothes Str. 4, 06120 Halle (Saale) , Germany
- Institut für Botanik , Technische Universität Dresden , Zellescher Weg 20b, 01062 Dresden , Germany
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153
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Zhang Y, Haider K, Kaur D, Ngo VA, Cai X, Mao J, Khaniya U, Zhu X, Noskov S, Lazaridis T, Gunner MR. Characterizing the Water Wire in the Gramicidin Channel Found by Monte Carlo Sampling Using Continuum Electrostatics and in Molecular Dynamics Trajectories with Conventional or Polarizable Force Fields. JOURNAL OF COMPUTATIONAL BIOPHYSICS AND CHEMISTRY 2021. [DOI: 10.1142/s2737416520420016] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Water molecules play a key role in all biochemical processes. They help define the shape of proteins, and they are reactant or product in many reactions and are released as ligands are bound. They facilitate the transfer of protons through transmembrane proton channel, pump and transporter proteins. Continuum electrostatics (CE) force fields used by program Multiconformation CE (MCCE) capture electrostatic interactions in biomolecules with an implicit solvent, which captures the averaged solvent water equilibrium properties. Hybrid CE methods can use explicit water molecules within the protein surrounded by implicit solvent. These hybrid methods permit the study of explicit hydrogen bond networks within the protein and allow analysis of processes such as proton transfer reactions. Yet hybrid CE methods have not been rigorously tested. Here, we present an explicit treatment of water molecules in the Gramicidin A (gA) channel using MCCE and compare the resulting distributions of water molecules and key hydration features against those obtained with explicit solvent Molecular Dynamics (MD) simulations with the nonpolarizable CHARMM36 and polarizable Drude force fields. CHARMM36 leads to an aligned water wire in the channel characterized by a large absolute net water dipole moment; the MCCE and Drude analysis lead to a small net dipole moment as the water molecules change orientation within the channel. The correct orientation is not as yet known, so these calculations identify an open question.
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Affiliation(s)
- Yingying Zhang
- Department of Physics, City College of New York, City University of New York, New York, NY 10031, USA
- Department of Physics, The Graduate Center, City University of New York, New York, NY 10016, USA
| | - Kamran Haider
- Department of Physics, City College of New York, City University of New York, New York, NY 10031, USA
| | - Divya Kaur
- Department of Physics, City College of New York, City University of New York, New York, NY 10031, USA
- Department of Chemistry, The Graduate Center, City University of New York, New York, NY 10016, USA
| | - Van A. Ngo
- Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, NM 87544, USA
| | - Xiuhong Cai
- Department of Physics, City College of New York, City University of New York, New York, NY 10031, USA
- Department of Physics, The Graduate Center, City University of New York, New York, NY 10016, USA
| | - Junjun Mao
- Levich Institute, School of Engineering, City College of New York, City University of New York, New York, NY 10031, USA
| | - Umesh Khaniya
- Department of Physics, City College of New York, City University of New York, New York, NY 10031, USA
- Department of Physics, The Graduate Center, City University of New York, New York, NY 10016, USA
| | - Xuyu Zhu
- Department of Physics, City College of New York, City University of New York, New York, NY 10031, USA
- Department of Physics, The Graduate Center, City University of New York, New York, NY 10016, USA
| | - Sergei Noskov
- Department of Biological Sciences, Centre for Molecular Simulation, University of Calgary, Calgary, AB, Canada
| | - Themis Lazaridis
- Department of Chemistry, The Graduate Center, City University of New York, New York, NY 10016, USA
- Department of Chemistry, City College of New York, City University of New York, New York, NY 10031, USA
| | - M. R. Gunner
- Department of Physics, City College of New York, City University of New York, New York, NY 10031, USA
- Department of Physics, The Graduate Center, City University of New York, New York, NY 10016, USA
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154
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Gieseking RLM. A new release of MOPAC incorporating the INDO/S semiempirical model with CI excited states. J Comput Chem 2021; 42:365-378. [PMID: 33227163 DOI: 10.1002/jcc.26455] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Revised: 09/28/2020] [Accepted: 11/05/2020] [Indexed: 11/10/2022]
Abstract
The semiempirical INDO/S Hamiltonian is incorporated into a new release of MOPAC2016. The MOPAC2016 software package has long been at the forefront of semiempirical quantum chemical methods (SEQMs) for small molecules, proteins, and solids and until this release has included only NDDO-type SEQMs. The new code enables the calculation of excited states using the INDO/S Hamiltonian combined with a configuration interaction (CI) approach using single excitations (CIS), single and double excitations (CISD), or multiple reference determinants (MRCI) where reference determinants are generated using a complete active space (CAS) approach. The capacity to perform excited-state calculations beyond the CIS level makes INDO/CI one of the few low-cost computational methods capable of accurately modeling states with substantial double-excitation character. Solvent corrections to the ground-state and excited-state energies can be computed using the COSMO implicit solvent model, incorporating state-specific corrections to the excited states based on the solvent refractive index. This code produces physically reasonable electronic structures, absorption spectra, and solvatochromic shifts at low computational costs for systems up to hundreds of atoms, and for both organic molecules and metal clusters.
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155
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Bhadra P, Siu SWI. Effect of Concentration, Chain Length, Hydrophobicity, and an External Electric Field on the Growth of Mixed Alkanethiol Self-Assembled Monolayers: A Molecular Dynamics Study. LANGMUIR : THE ACS JOURNAL OF SURFACES AND COLLOIDS 2021; 37:1913-1924. [PMID: 33503375 DOI: 10.1021/acs.langmuir.0c03414] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Growing functionalized self-assembled monolayers (SAMs) with fewer defects and lower cost is the focus of ongoing investigations. In the present study, molecular dynamics simulations were performed to investigate the process of SAM formation on a gold substrate from mixed alkanethiolates in ethanol solution. Using the mixed-SAM system of 11-mercaptoundecanoic acid (MUA) with either 1-decanethiol (C9CH3) or 6-mercaptohexanol (C6OH) in a 3:7 ratio as the standard SAM model, we systematically investigated the effects of the concentration, chain length, functional group, and an external electric field on SAM growth. The results showed that the initial growth rate and surface coverage of the SAM are dependent on the ligand concentration. At a certain high concentration (about 1.2-1.5 times the minimum concentration), the final surface coverage is optimal. Reducing the chain length and increasing the proportion of hydrophobic diluting molecules are effective ways to improve the surface coverage, but the compositional ligands have to be changed, which may not be desirable for the functional requirements of SAMs. Furthermore, by investigating the behavior of the alkanethiolates and ethanol solvent under an applied external field, we find that a strong electric field with a proper field direction can facilitate the generation of defect-free monolayers. These findings will contribute to the understanding of mixed-SAM formation and provide insight into experimental design for efficient and effective SAM formation.
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Affiliation(s)
- Pratiti Bhadra
- Department of Computer and Information Science, University of Macau, Taipa, Macau
| | - Shirley W I Siu
- Department of Computer and Information Science, University of Macau, Taipa, Macau
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156
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Niklasson AMN. Extended Lagrangian Born-Oppenheimer molecular dynamics for orbital-free density-functional theory and polarizable charge equilibration models. J Chem Phys 2021; 154:054101. [PMID: 33557538 DOI: 10.1063/5.0038190] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Extended Lagrangian Born-Oppenheimer molecular dynamics (XL-BOMD) [A. M. N. Niklasson, Phys. Rev. Lett. 100, 123004 (2008)] is formulated for orbital-free Hohenberg-Kohn density-functional theory and for charge equilibration and polarizable force-field models that can be derived from the same orbital-free framework. The purpose is to introduce the most recent features of orbital-based XL-BOMD to molecular dynamics simulations based on charge equilibration and polarizable force-field models. These features include a metric tensor generalization of the extended harmonic potential, preconditioners, and the ability to use only a single Coulomb summation to determine the fully equilibrated charges and the interatomic forces in each time step for the shadow Born-Oppenheimer potential energy surface. The orbital-free formulation has a charge-dependent, short-range energy term that is separate from long-range Coulomb interactions. This enables local parameterizations of the short-range energy term, while the long-range electrostatic interactions can be treated separately. The theory is illustrated for molecular dynamics simulations of an atomistic system described by a charge equilibration model with periodic boundary conditions. The system of linear equations that determines the equilibrated charges and the forces is diagonal, and only a single Ewald summation is needed in each time step. The simulations exhibit the same features in accuracy, convergence, and stability as are expected from orbital-based XL-BOMD.
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Affiliation(s)
- Anders M N Niklasson
- Theoretical Division T-1, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
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157
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Ngo V, Li H, MacKerell AD, Allen TW, Roux B, Noskov S. Polarization Effects in Water-Mediated Selective Cation Transport across a Narrow Transmembrane Channel. J Chem Theory Comput 2021; 17:1726-1741. [PMID: 33539082 DOI: 10.1021/acs.jctc.0c00968] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Despite the progress in modeling complex molecular systems of ever-increasing complexity, a quantitatively accurate computational treatment of ion permeation through narrow membrane channels remains challenging. An important factor to reach this goal is induced electronic polarization, which is likely to impact the permeation rate of small ions through narrow molecular pores. In this work, we extended the recently developed polarizable force field based on the classical Drude oscillators to assess the role of induced polarization effects on the energetics of sodium and potassium ion transport across the gramicidin A (gA) ion channel. The inclusion of induced polarization lowers barriers present in 1D potential of mean force (PMF) for cation permeation by ∼50% compared to those obtained with the additive force field. Conductance properties calculated with 1D PMFs from Drude simulations are in better agreement with experimental results. Polarization of single-file water molecules and protein atoms forming the narrow pore has a direct impact on the free-energy barriers and cation-specific solid-state NMR chemical shifts. Sensitivity analysis indicates that small changes to water-channel interactions can alter the free energy barrier for ion permeation. These results, illustrating polarization effects present in the complex electrostatic environment of the gA channel, have broad implications for revising proposed mechanisms of ion permeation and selectivity in a variety of ion channels.
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Affiliation(s)
- Van Ngo
- Centre for Molecular Simulation, Department of Biological Sciences, University of Calgary, Calgary, Alberta T2N1N4, Canada.,Center for Nonlinear Studies, Los Alamos National Lab, Los Alamos, New Mexico 87544, United States
| | - Hui Li
- Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, Illinois 60637, United States
| | - Alexander D MacKerell
- Computer-Aided Drug Design Center, Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland, Baltimore, Maryland 21201, United States
| | - Toby W Allen
- School of Science, RMIT University, Melbourne, VIC 3001, Australia
| | - Benoît Roux
- Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, Illinois 60637, United States
| | - Sergei Noskov
- Centre for Molecular Simulation, Department of Biological Sciences, University of Calgary, Calgary, Alberta T2N1N4, Canada
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158
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Chen P, Vorobyov I, Roux B, Allen TW. Molecular Dynamics Simulations Based on Polarizable Models Show that Ion Permeation Interconverts between Different Mechanisms as a Function of Membrane Thickness. J Phys Chem B 2021; 125:1020-1035. [PMID: 33493394 DOI: 10.1021/acs.jpcb.0c08613] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Different mechanisms have been proposed to explain the permeation of charged compounds through lipid membranes. Overall, it is expected that an ion-induced defect permeation mechanism, where substantial membrane deformations accompany ion movement, should be dominant in thin membranes but that a solubility-diffusion mechanism, where ions partition into the membrane core with large associated dehydration energy costs, becomes dominant in thicker membranes. However, while this physical picture is intuitively reasonable, capturing the interconversion between these two permeation mechanisms in molecular dynamics (MD) simulations based on atomic models is challenging. In particular, simulations relying on nonpolarizable force fields are artificially unfavorable to the solubility-diffusion mechanism, as induced polarization of the nonpolar hydrocarbon is ignored, causing overestimated free energy costs for charged molecules to enter into this region of the membrane. In this study, all-atom MD simulations based on nonpolarizable and polarizable force fields are used to quantitatively characterize the permeation process for the arginine side chain analog methyl-guanidinium through bilayer membranes of mono-unsaturated phosphatidylcholine lipids with and without cholesterol, resulting in thicknesses spanning from ∼24 to ∼42 Å. With simulations based on a nonpolarizable force field, ion translocation can take place solely through an ion-induced defect mechanism, with free energy barriers increasing linearly from 14 to 40 kcal/mol, depending on the thickness. However, with simulations based on a polarizable force field, ion translocation is predominantly dominated by an ion-induced defect mechanism in thin membranes, which progressively converts to a solubility-diffusion mechanism as the membranes get thicker. The transition between the two mechanisms occurs at a thickness of ∼29 Å, with lipid tails of 22 or more carbon atoms. This situation appears to represent the upper limit for ion-induced defect permeation within the current polarizable models. Beyond this thickness, it becomes energetically preferable for the ion to dehydrate and partition into the membrane core-a phenomenon that cannot be captured using the nonpolarizable models. Induced electronic polarizability therefore leads not just to a shift in permeation energetics but to an interconversion between two strikingly different physical mechanisms. The result highlights the importance of induced polarizability in modeling lipid membranes.
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Affiliation(s)
- Peiran Chen
- Department of Chemistry, University of California, Davis, California 95616, United States
| | - Igor Vorobyov
- Department of Physiology & Membrane Biology, Department of Pharmacology, University of California, Davis, California 95616, United States
| | - Benoît Roux
- Department of Chemistry, University of Chicago, Chicago, Illinois 60637, United States
| | - Toby W Allen
- School of Science, RMIT University, Melbourne 3001, Australia
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159
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Sengupta A, Li Z, Song LF, Li P, Merz KM. Parameterization of Monovalent Ions for the OPC3, OPC, TIP3P-FB, and TIP4P-FB Water Models. J Chem Inf Model 2021; 61:869-880. [PMID: 33538599 DOI: 10.1021/acs.jcim.0c01390] [Citation(s) in RCA: 82] [Impact Index Per Article: 27.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Monovalent ions play significant roles in various biological and material systems. Recently, four new water models (OPC3, OPC, TIP3P-FB, and TIP4P-FB), with significantly improved descriptions of condensed phase water, have been developed. The pairwise interaction between the metal ion and water necessitates the development of ion parameters specifically for these water models. Herein, we parameterized the 12-6 and the 12-6-4 nonbonded models for 12 monovalent ions with the respective four new water models. These monovalent ions contain eight cations including alkali metal ions (Li+, Na+, K+, Rb+, Cs+), transition-metal ions (Cu+ and Ag+), and Tl+ from the boron family, along with four halide anions (F-, Cl-, Br-, I-). Our parameters were designed to reproduce the target hydration free energies (the 12-6 hydration free energy (HFE) set), the ion-oxygen distances (the 12-6 ion-oxygen distance (IOD) set), or both of them (the 12-6-4 set). The 12-6-4 parameter set provides highly accurate structural features overcoming the limitations of the routinely used 12-6 nonbonded model for ions. Specifically, we note that the 12-6-4 parameter set is able to reproduce experimental hydration free energies within 1 kcal/mol and experimental ion-oxygen distances within 0.01 Å simultaneously. We further reproduced the experimentally determined activity derivatives for salt solutions, validating the ion parameters for simulations of ion pairs. The improved performance of the present water models over our previous parameter sets for the TIP3P, TIP4P, and SPC/E water models (Li, P. et al J. Chem. Theory Comput. 2015 11 1645 1657) highlights the importance of the choice of water model in conjunction with the metal ion parameter set.
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Affiliation(s)
- Arkajyoti Sengupta
- Department of Chemistry, Michigan State University, East Lansing, Michigan 48824, United States
| | - Zhen Li
- Department of Chemistry, Michigan State University, East Lansing, Michigan 48824, United States
| | - Lin Frank Song
- Department of Chemistry, Michigan State University, East Lansing, Michigan 48824, United States
| | - Pengfei Li
- Department of Chemistry, Yale University, New Haven, Connecticut 06511, United States.,Department of Chemistry and Biochemistry, Loyola University Chicago, Chicago, Illinois 60660, United States
| | - Kenneth M Merz
- Department of Chemistry, Michigan State University, East Lansing, Michigan 48824, United States.,Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan 48824, United States
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160
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Rao S, Klesse G, Lynch CI, Tucker SJ, Sansom MSP. Molecular Simulations of Hydrophobic Gating of Pentameric Ligand Gated Ion Channels: Insights into Water and Ions. J Phys Chem B 2021; 125:981-994. [PMID: 33439645 PMCID: PMC7869105 DOI: 10.1021/acs.jpcb.0c09285] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 12/13/2020] [Indexed: 12/30/2022]
Abstract
Ion channels are proteins which form gated nanopores in biological membranes. Many channels exhibit hydrophobic gating, whereby functional closure of a pore occurs by local dewetting. The pentameric ligand gated ion channels (pLGICs) provide a biologically important example of hydrophobic gating. Molecular simulation studies comparing additive vs polarizable models indicate predictions of hydrophobic gating are robust to the model employed. However, polarizable models suggest favorable interactions of hydrophobic pore-lining regions with chloride ions, of relevance to both synthetic carriers and channel proteins. Electrowetting of a closed pLGIC hydrophobic gate requires too high a voltage to occur physiologically but may inform designs for switchable nanopores. Global analysis of ∼200 channels yields a simple heuristic for structure-based prediction of (closed) hydrophobic gates. Simulation-based analysis is shown to provide an aid to interpretation of functional states of new channel structures. These studies indicate the importance of understanding the behavior of water and ions within the nanoconfined environment presented by ion channels.
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Affiliation(s)
- Shanlin Rao
- Department
of Biochemistry, University of Oxford, Oxford, U.K.
| | - Gianni Klesse
- Clarendon
Laboratory, Department of Physics, University
of Oxford, Oxford, U.K.
| | | | - Stephen J. Tucker
- Clarendon
Laboratory, Department of Physics, University
of Oxford, Oxford, U.K.
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161
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Jaffrelot Inizan T, Célerse F, Adjoua O, El Ahdab D, Jolly LH, Liu C, Ren P, Montes M, Lagarde N, Lagardère L, Monmarché P, Piquemal JP. High-resolution mining of the SARS-CoV-2 main protease conformational space: supercomputer-driven unsupervised adaptive sampling. Chem Sci 2021; 12:4889-4907. [PMID: 34168762 PMCID: PMC8179654 DOI: 10.1039/d1sc00145k] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2021] [Accepted: 01/27/2021] [Indexed: 01/03/2023] Open
Abstract
We provide an unsupervised adaptive sampling strategy capable of producing μs-timescale molecular dynamics (MD) simulations of large biosystems using many-body polarizable force fields (PFFs). The global exploration problem is decomposed into a set of separate MD trajectories that can be restarted within a selective process to achieve sufficient phase-space sampling. Accurate statistical properties can be obtained through reweighting. Within this highly parallel setup, the Tinker-HP package can be powered by an arbitrary large number of GPUs on supercomputers, reducing exploration time from years to days. This approach is used to tackle the urgent modeling problem of the SARS-CoV-2 Main Protease (Mpro) producing more than 38 μs of all-atom simulations of its apo (ligand-free) dimer using the high-resolution AMOEBA PFF. The first 15.14 μs simulation (physiological pH) is compared to available non-PFF long-timescale simulation data. A detailed clustering analysis exhibits striking differences between FFs, with AMOEBA showing a richer conformational space. Focusing on key structural markers related to the oxyanion hole stability, we observe an asymmetry between protomers. One of them appears less structured resembling the experimentally inactive monomer for which a 6 μs simulation was performed as a basis for comparison. Results highlight the plasticity of the Mpro active site. The C-terminal end of its less structured protomer is shown to oscillate between several states, being able to interact with the other protomer, potentially modulating its activity. Active and distal site volumes are found to be larger in the most active protomer within our AMOEBA simulations compared to non-PFFs as additional cryptic pockets are uncovered. A second 17 μs AMOEBA simulation is performed with protonated His172 residues mimicking lower pH. Data show the protonation impact on the destructuring of the oxyanion loop. We finally analyze the solvation patterns around key histidine residues. The confined AMOEBA polarizable water molecules are able to explore a wide range of dipole moments, going beyond bulk values, leading to a water molecule count consistent with experimental data. Results suggest that the use of PFFs could be critical in drug discovery to accurately model the complexity of the molecular interactions structuring Mpro.
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Affiliation(s)
| | - Frédéric Célerse
- Sorbonne Université, LCT, UMR 7616 CNRS Paris France
- Sorbonne Université, IPCM, UMR 8232 CNRS Paris France
| | | | - Dina El Ahdab
- Sorbonne Université, LCT, UMR 7616 CNRS Paris France
- Université Saint-Joseph de Beyrouth, UR-EGP Faculté des Sciences Lebanon
| | | | - Chengwen Liu
- University of Texas at Austin, Department of Biomedical Engineering Texas USA
| | - Pengyu Ren
- University of Texas at Austin, Department of Biomedical Engineering Texas USA
| | - Matthieu Montes
- Laboratoire GBCM, EA 7528, CNAM, Hésam Université Paris France
| | | | - Louis Lagardère
- Sorbonne Université, LCT, UMR 7616 CNRS Paris France
- Sorbonne Université, IP2CT, FR 2622 CNRS Paris France
| | - Pierre Monmarché
- Sorbonne Université, LCT, UMR 7616 CNRS Paris France
- Sorbonne Université, LJLL, UMR 7598 CNRS Paris France
| | - Jean-Philip Piquemal
- Sorbonne Université, LCT, UMR 7616 CNRS Paris France
- University of Texas at Austin, Department of Biomedical Engineering Texas USA
- Institut Universitaire de France Paris France
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162
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Kuprov I, Morris LC, Glushka JN, Prestegard JH. Using molecular dynamics trajectories to predict nuclear spin relaxation behaviour in large spin systems. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2021; 323:106891. [PMID: 33445107 PMCID: PMC7873838 DOI: 10.1016/j.jmr.2020.106891] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 12/07/2020] [Accepted: 12/08/2020] [Indexed: 05/09/2023]
Abstract
Molecular dynamics (MD) trajectories provide useful insights into molecular structure and dynamics. However, questions persist about the quantitative accuracy of those insights. Experimental NMR spin relaxation rates can be used as tests, but only if relaxation superoperators can be efficiently computed from MD trajectories - no mean feat for the quantum Liouville space formalism where matrix dimensions quadruple with each added spin 1/2. Here we report a module for the Spinach software framework that computes Bloch-Redfield-Wangsness relaxation superoperators (including non-secular terms and cross-correlations) from MD trajectories. Predicted initial slopes of nuclear Overhauser effects for sucrose trajectories using advanced water models and a force field optimised for glycans are within 25% of experimental values.
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Affiliation(s)
- Ilya Kuprov
- School of Chemistry, University of Southampton, Southampton, UK
| | - Laura C Morris
- Complex Carbohydrate Research Center, University of Georgia, Athens, GA 30602, United States
| | - John N Glushka
- Complex Carbohydrate Research Center, University of Georgia, Athens, GA 30602, United States
| | - James H Prestegard
- Complex Carbohydrate Research Center, University of Georgia, Athens, GA 30602, United States.
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163
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Zhang Z, Vögele J, Mráziková K, Kruse H, Cang X, Wöhnert J, Krepl M, Šponer J. Phosphorothioate Substitutions in RNA Structure Studied by Molecular Dynamics Simulations, QM/MM Calculations, and NMR Experiments. J Phys Chem B 2021; 125:825-840. [PMID: 33467852 DOI: 10.1021/acs.jpcb.0c10192] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Phosphorothioates (PTs) are important chemical modifications of the RNA backbone where a single nonbridging oxygen of the phosphate is replaced with a sulfur atom. PT can stabilize RNAs by protecting them from hydrolysis and is commonly used as a tool to explore their function. It is, however, unclear what basic physical effects PT has on RNA stability and electronic structure. Here, we present molecular dynamics (MD) simulations, quantum mechanical (QM) calculations, and NMR spectroscopy measurements, exploring the effects of PT modifications in the structural context of the neomycin-sensing riboswitch (NSR). The NSR is the smallest biologically functional riboswitch with a well-defined structure stabilized by a U-turn motif. Three of the signature interactions of the U-turn: an H-bond, an anion-π interaction, and a potassium binding site; are formed by RNA phosphates, making the NSR an ideal model for studying how PT affects RNA structure and dynamics. By comparing with high-level QM calculations, we reveal the distinct physical properties of the individual interactions facilitated by the PT. The sulfur substitution, besides weakening the direct H-bond interaction, reduces the directionality of H-bonding while increasing its dispersion and induction components. It also reduces the induction and increases the dispersion component of the anion-π stacking. The sulfur force-field parameters commonly employed in the literature do not reflect these distinctions, leading to the unsatisfactory description of PT in simulations of the NSR. We show that it is not possible to accurately describe the PT interactions using one universal set of van der Waals sulfur parameters and provide suggestions for improving the force-field performance.
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Affiliation(s)
- Zhengyue Zhang
- CEITEC-Central European Institute of Technology, Masaryk University, Kamenice 5, 625 00 Brno, Czech Republic.,Faculty of Science, Masaryk University, Kotlarska 2, 602 00 Brno, Czech Republic
| | - Jennifer Vögele
- Institute of Molecular Biosciences and Center for Biomolecular Magnetic Resonance (BMRZ), Goethe-University Frankfurt, Max-von-Laue-Straße 9, 60438 Frankfurt, Germany
| | - Klaudia Mráziková
- Faculty of Science, Masaryk University, Kotlarska 2, 602 00 Brno, Czech Republic.,Institute of Biophysics of the Czech Academy of Sciences, Kralovopolska 135, 612 65 Brno, Czech Republic
| | - Holger Kruse
- Institute of Biophysics of the Czech Academy of Sciences, Kralovopolska 135, 612 65 Brno, Czech Republic
| | - Xiaohui Cang
- Institute of Genetics, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Jens Wöhnert
- Institute of Molecular Biosciences and Center for Biomolecular Magnetic Resonance (BMRZ), Goethe-University Frankfurt, Max-von-Laue-Straße 9, 60438 Frankfurt, Germany
| | - Miroslav Krepl
- Institute of Biophysics of the Czech Academy of Sciences, Kralovopolska 135, 612 65 Brno, Czech Republic
| | - Jiří Šponer
- CEITEC-Central European Institute of Technology, Masaryk University, Kamenice 5, 625 00 Brno, Czech Republic.,Institute of Biophysics of the Czech Academy of Sciences, Kralovopolska 135, 612 65 Brno, Czech Republic
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164
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Yoshida Y, Iuchi S, Sato H. A quantum chemical model for a series of self-assembled nanocages: the origin of stability behind the coordination-driven formation of transition metal complexes up to [M 12L 24] 24. Phys Chem Chem Phys 2021; 23:866-877. [PMID: 33107507 DOI: 10.1039/d0cp04755d] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Herein, we present a systematic computational model to study the electronic states and free energies of a self-assembled multi-metal complex series. By combining the previously developed model Hamiltonian approach for transition-metal complexes and the generalized Born model, the thermodynamics, optimized geometries, and electronic states of the [Pd12L24]24+ nanocage are revealed, together with [PdnLm]2n+ complex series. The effective model Hamiltonian is a theoretical method to obtain the d-electron wavefunction and potential energy including interaction energy between the transition-metal and ligands. In the present improvement, the electronic state on each transition-metal center is focused as a building unit and solved under the whole electronic field of the assembling system. We realize a reliable and systematic treatment of multi-transition-metal complexes with different sizes and charges. Consequently, our model could reproduce binding energies of the [PdnLm]2n+ complex series quantitatively as compared to density functional theory (DFT). Regarding free energy, we revealed that the assembling solute becomes unstable due to the electrostatic interaction, and effects of the solvent and counter anions mainly compensated it. Optimized geometries were also analysed. The local square-planar coordination structures around the palladium centres were characterized in the complex series. The relationships between the entire symmetrical geometries and the local coordination structures are also discussed. Finally, electronic structures of the [Pd12L24]24+ nanocage were well characterized as a single-determinant, where only dx2-y2 is unoccupied due to the ligand-field effect. We also found that the solvent polarized the electronic states of the Pd ions, whereas the counter anion suppressed the polarization. The present method realizes size-independent reliable and rapid computations, and therefore can be expected to further application studies on self-assembly dynamics.
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Affiliation(s)
- Yuichiro Yoshida
- Department of Molecular Engineering, Graduate School of Engineering, Kyoto University, Nishikyo-ku, Kyoto 615-8510, Japan.
| | - Satoru Iuchi
- Graduate School of Informatics, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8601, Japan.
| | - Hirofumi Sato
- Department of Molecular Engineering, Graduate School of Engineering, Kyoto University, Nishikyo-ku, Kyoto 615-8510, Japan. and Elements Strategy Initiative for Catalysts and Batteries (ESICB), Kyoto University, Nishikyo-ku, Kyoto 615-8520, Japan and Fukui Institute for Fundamental Chemistry, Kyoto University, Takano Nishihiraki-cho 34-4, Sakyo-ku, Kyoto 606-8103, Japan
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165
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Acharya A, Agarwal R, Baker M, Baudry J, Bhowmik D, Boehm S, Byler KG, Chen S, Coates L, Cooper C, Demerdash O, Daidone I, Eblen J, Ellingson S, Forli S, Glaser J, Gumbart JC, Gunnels J, Hernandez O, Irle S, Kneller D, Kovalevsky A, Larkin J, Lawrence T, LeGrand S, Liu SH, Mitchell J, Park G, Parks J, Pavlova A, Petridis L, Poole D, Pouchard L, Ramanathan A, Rogers D, Santos-Martins D, Scheinberg A, Sedova A, Shen Y, Smith J, Smith M, Soto C, Tsaris A, Thavappiragasam M, Tillack A, Vermaas J, Vuong V, Yin J, Yoo S, Zahran M, Zanetti-Polzi L. Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19. J Chem Inf Model 2020; 60:5832-5852. [PMID: 33326239 PMCID: PMC7754786 DOI: 10.1021/acs.jcim.0c01010] [Citation(s) in RCA: 109] [Impact Index Per Article: 27.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Indexed: 01/18/2023]
Abstract
We present a supercomputer-driven pipeline for in silico drug discovery using enhanced sampling molecular dynamics (MD) and ensemble docking. Ensemble docking makes use of MD results by docking compound databases into representative protein binding-site conformations, thus taking into account the dynamic properties of the binding sites. We also describe preliminary results obtained for 24 systems involving eight proteins of the proteome of SARS-CoV-2. The MD involves temperature replica exchange enhanced sampling, making use of massively parallel supercomputing to quickly sample the configurational space of protein drug targets. Using the Summit supercomputer at the Oak Ridge National Laboratory, more than 1 ms of enhanced sampling MD can be generated per day. We have ensemble docked repurposing databases to 10 configurations of each of the 24 SARS-CoV-2 systems using AutoDock Vina. Comparison to experiment demonstrates remarkably high hit rates for the top scoring tranches of compounds identified by our ensemble approach. We also demonstrate that, using Autodock-GPU on Summit, it is possible to perform exhaustive docking of one billion compounds in under 24 h. Finally, we discuss preliminary results and planned improvements to the pipeline, including the use of quantum mechanical (QM), machine learning, and artificial intelligence (AI) methods to cluster MD trajectories and rescore docking poses.
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Affiliation(s)
- A. Acharya
- School of Physics, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - R. Agarwal
- UT/ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory, TN, 37830, USA
- The University of Tennessee, Knoxville. Department of Biochemistry & Cellular and Molecular Biology, 309 Ken and Blaire Mossman Bldg. 1311 Cumberland Avenue Knoxville, TN, 37996, USA
- Graduate School of Genome Science and Technology, University of Tennessee, Knoxville, TN, 37996, USA
| | - M. Baker
- Computer Science and Mathematics Division, Oak Ridge National Lab, Oak Ridge, TN 37830, USA
| | - J. Baudry
- The University of Alabama in Huntsville, Department of Biological Sciences. 301 Sparkman Drive, Huntsville, AL 35899, USA
| | - D. Bhowmik
- Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - S. Boehm
- Computer Science and Mathematics Division, Oak Ridge National Lab, Oak Ridge, TN 37830, USA
| | - K. G. Byler
- The University of Alabama in Huntsville, Department of Biological Sciences. 301 Sparkman Drive, Huntsville, AL 35899, USA
| | - S.Y. Chen
- Computational Science Initiative, Brookhaven National Laboratory, Upton, NY 11973, USA
| | - L. Coates
- Neutron Scattering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - C.J. Cooper
- UT/ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory, TN, 37830, USA
- Graduate School of Genome Science and Technology, University of Tennessee, Knoxville, TN, 37996, USA
| | - O. Demerdash
- Biosciences Division, Oak Ridge National Lab, Oak Ridge, TN 37830, USA
| | - I. Daidone
- Department of Physical and Chemical Sciences, University of L’Aquila, I-67010 L’Aquila, Italy
| | - J.D. Eblen
- UT/ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory, TN, 37830, USA
- The University of Tennessee, Knoxville. Department of Biochemistry & Cellular and Molecular Biology, 309 Ken and Blaire Mossman Bldg. 1311 Cumberland Avenue Knoxville, TN, 37996, USA
| | - S. Ellingson
- University of Kentucky, Division of Biomedical Informatics, College of Medicine, UK Medical Center MN 150, Lexington KY, 40536, USA
| | - S. Forli
- Scripps Research, La Jolla, CA, 92037, USA
| | - J. Glaser
- National Center for Computational Sciences, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA
| | - J. C. Gumbart
- School of Physics, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - J. Gunnels
- HPC Engineering, Amazon Web Services, Seattle, WA 98121, USA
| | - O. Hernandez
- Computer Science and Mathematics Division, Oak Ridge National Lab, Oak Ridge, TN 37830, USA
| | - S. Irle
- Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee, Knoxville, TN 37996, USA
| | - D.W. Kneller
- Neutron Scattering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - A. Kovalevsky
- Neutron Scattering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - J. Larkin
- NVIDIA Corporation, Santa Clara, CA 95051, USA
| | - T.J. Lawrence
- Biosciences Division, Oak Ridge National Lab, Oak Ridge, TN 37830, USA
| | - S. LeGrand
- NVIDIA Corporation, Santa Clara, CA 95051, USA
| | - S.-H. Liu
- UT/ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory, TN, 37830, USA
- The University of Tennessee, Knoxville. Department of Biochemistry & Cellular and Molecular Biology, 309 Ken and Blaire Mossman Bldg. 1311 Cumberland Avenue Knoxville, TN, 37996, USA
| | - J.C. Mitchell
- Biosciences Division, Oak Ridge National Lab, Oak Ridge, TN 37830, USA
| | - G. Park
- Computational Science Initiative, Brookhaven National Laboratory, Upton, NY 11973, USA
| | - J.M. Parks
- UT/ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory, TN, 37830, USA
- The University of Tennessee, Knoxville. Department of Biochemistry & Cellular and Molecular Biology, 309 Ken and Blaire Mossman Bldg. 1311 Cumberland Avenue Knoxville, TN, 37996, USA
- Graduate School of Genome Science and Technology, University of Tennessee, Knoxville, TN, 37996, USA
| | - A. Pavlova
- School of Physics, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - L. Petridis
- UT/ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory, TN, 37830, USA
- The University of Tennessee, Knoxville. Department of Biochemistry & Cellular and Molecular Biology, 309 Ken and Blaire Mossman Bldg. 1311 Cumberland Avenue Knoxville, TN, 37996, USA
| | - D. Poole
- NVIDIA Corporation, Santa Clara, CA 95051, USA
| | - L. Pouchard
- Computational Science Initiative, Brookhaven National Laboratory, Upton, NY 11973, USA
| | - A. Ramanathan
- Data Science and Learning Division, Argonne National Lab, Lemont, IL 60439, USA
| | - D. Rogers
- National Center for Computational Sciences, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA
| | | | | | - A. Sedova
- Biosciences Division, Oak Ridge National Lab, Oak Ridge, TN 37830, USA
| | - Y. Shen
- UT/ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory, TN, 37830, USA
- The University of Tennessee, Knoxville. Department of Biochemistry & Cellular and Molecular Biology, 309 Ken and Blaire Mossman Bldg. 1311 Cumberland Avenue Knoxville, TN, 37996, USA
- Graduate School of Genome Science and Technology, University of Tennessee, Knoxville, TN, 37996, USA
| | - J.C. Smith
- UT/ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory, TN, 37830, USA
- The University of Tennessee, Knoxville. Department of Biochemistry & Cellular and Molecular Biology, 309 Ken and Blaire Mossman Bldg. 1311 Cumberland Avenue Knoxville, TN, 37996, USA
| | - M.D. Smith
- UT/ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory, TN, 37830, USA
- The University of Tennessee, Knoxville. Department of Biochemistry & Cellular and Molecular Biology, 309 Ken and Blaire Mossman Bldg. 1311 Cumberland Avenue Knoxville, TN, 37996, USA
| | - C. Soto
- Computational Science Initiative, Brookhaven National Laboratory, Upton, NY 11973, USA
| | - A. Tsaris
- National Center for Computational Sciences, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA
| | | | | | - J.V. Vermaas
- National Center for Computational Sciences, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA
| | - V.Q. Vuong
- Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
- Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee, Knoxville, TN 37996, USA
| | - J. Yin
- National Center for Computational Sciences, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA
| | - S. Yoo
- Computational Science Initiative, Brookhaven National Laboratory, Upton, NY 11973, USA
| | - M. Zahran
- Department of Biological Sciences, New York City College of Technology, The City University of New York (CUNY), Brooklyn, NY 11201, USA
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166
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Rogers TR, Wang F. Accurate MP2-based force fields predict hydration free energies for simple alkanes and alcohols in good agreement with experiments. J Chem Phys 2020; 153:244505. [PMID: 33380083 PMCID: PMC7771999 DOI: 10.1063/5.0035032] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Accepted: 12/07/2020] [Indexed: 12/21/2022] Open
Abstract
Force fields for four small molecules, methane, ethane, methanol, and ethanol, were created by force matching MP2 gradients computed with triple-zeta-quality basis sets using the Adaptive Force Matching method. Without fitting to any experimental properties, the force fields created were able to predict hydration free energies, enthalpies of hydration, and diffusion constants in excellent agreements with experiments. The root mean square error for the predicted hydration free energies is within 1 kJ/mol of experimental measurements of Ben-Naim et al. [J. Chem. Phys. 81(4), 2016-2027 (1984)]. The good prediction of hydration free energies is particularly noteworthy, as it is an important fundamental property. Similar hydration free energies of ethane relative to methane and of ethanol relative to methanol are attributed to a near cancellation of cavitation penalty and favorable contributions from dispersion and Coulombic interactions as a result of the additional methyl group.
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Affiliation(s)
- T. Ryan Rogers
- Department of Chemistry and Biochemistry, University of Arkansas, Fayetteville, Arkansas 72701, USA
| | - Feng Wang
- Department of Chemistry and Biochemistry, University of Arkansas, Fayetteville, Arkansas 72701, USA
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167
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Decherchi S, Cavalli A. Thermodynamics and Kinetics of Drug-Target Binding by Molecular Simulation. Chem Rev 2020; 120:12788-12833. [PMID: 33006893 PMCID: PMC8011912 DOI: 10.1021/acs.chemrev.0c00534] [Citation(s) in RCA: 122] [Impact Index Per Article: 30.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Indexed: 12/19/2022]
Abstract
Computational studies play an increasingly important role in chemistry and biophysics, mainly thanks to improvements in hardware and algorithms. In drug discovery and development, computational studies can reduce the costs and risks of bringing a new medicine to market. Computational simulations are mainly used to optimize promising new compounds by estimating their binding affinity to proteins. This is challenging due to the complexity of the simulated system. To assess the present and future value of simulation for drug discovery, we review key applications of advanced methods for sampling complex free-energy landscapes at near nonergodicity conditions and for estimating the rate coefficients of very slow processes of pharmacological interest. We outline the statistical mechanics and computational background behind this research, including methods such as steered molecular dynamics and metadynamics. We review recent applications to pharmacology and drug discovery and discuss possible guidelines for the practitioner. Recent trends in machine learning are also briefly discussed. Thanks to the rapid development of methods for characterizing and quantifying rare events, simulation's role in drug discovery is likely to expand, making it a valuable complement to experimental and clinical approaches.
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Affiliation(s)
- Sergio Decherchi
- Computational
and Chemical Biology, Fondazione Istituto
Italiano di Tecnologia, 16163 Genoa, Italy
| | - Andrea Cavalli
- Computational
and Chemical Biology, Fondazione Istituto
Italiano di Tecnologia, 16163 Genoa, Italy
- Department
of Pharmacy and Biotechnology, University
of Bologna, 40126 Bologna, Italy
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168
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Lambros E, Lipparini F, Cisneros GA, Paesani F. A Many-Body, Fully Polarizable Approach to QM/MM Simulations. J Chem Theory Comput 2020; 16:7462-7472. [PMID: 33213149 PMCID: PMC8131112 DOI: 10.1021/acs.jctc.0c00932] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
We present a new development in quantum mechanics/molecular mechanics (QM/MM) methods by replacing conventional MM models with data-driven many-body (MB) representations rigorously derived from high-level QM calculations. The new QM/MM approach builds on top of mutually polarizable QM/MM schemes developed for polarizable force fields with inducible dipoles and uses permutationally invariant polynomials to effectively account for quantum-mechanical contributions (e.g., exchange-repulsion and charge transfer and penetration) that are difficult to describe by classical expressions adopted by conventional MM models. Using the many-body MB-pol and MB-DFT potential energy functions for water, which include explicit two-body and three-body terms fitted to reproduce the corresponding CCSD(T) and PBE0 two-body and three-body energies for water, we demonstrate a smooth energetic transition as molecules are transferred between QM and MM regions, without the need of a transition layer. By effectively elevating the accuracy of both the MM region and the QM/MM interface to that of the QM region, the new QM/MB-MM approach achieves an accuracy comparable to that obtained with a fully QM treatment of the entire system.
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Affiliation(s)
- Eleftherios Lambros
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, United States
| | - Filippo Lipparini
- Dipartimento di Chimica e Chimica Industriale, University of Pisa, via G. Moruzzi 13, 56124 Pisa, Italy
| | | | - Francesco Paesani
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, United States
- Materials Science and Engineering, University of California San Diego, La Jolla, California 92093, United States
- San Diego Supercomputer Center, University of California San Diego, La Jolla, California 92093, United States
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169
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Yuan Y, Ma Y, Huo D, Mills MJL, Wei J, Su W, Zhang R. Multipolar Description of Atom-Atom Electrostatic Interaction Energies in Single/Double-Stranded DNAs. J Phys Chem B 2020; 124:10089-10103. [PMID: 33138384 DOI: 10.1021/acs.jpcb.0c06757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Molecular force field simulation is an effective method to explore the properties of DNA molecules in depth. Almost all current popular force fields calculate atom-atom electrostatic interaction energies for DNAs based on the atomic charge and dipole or quadrupole moments, without considering high-rank atomic multipole moments for more accurate electrostatics. Actually, the distribution of electrons around atomic nuclei is not spherically symmetric but is geometry dependent. In this work, a multipole expansion method that allows us to combine polarizability and anisotropy was applied. One single-stranded DNA and one double-stranded DNA were selected as pilot systems. Deoxynucleotides were cut out from pilot systems and capped by mimicking the original DNA environment. Atomic multipole moments were integrated instead of fixed-point charges to calculate atom-atom electrostatic energies to improve the accuracy of force fields for DNA simulations. Also, the applicability of modeling the behavior of both single-stranded and double-stranded DNAs was investigated. The calculation results indicated that the models can be transferred from pilot systems to test systems, which is of great significance for the development of future DNA force fields.
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Affiliation(s)
- Yongna Yuan
- School of Information Science & Engineering, Lanzhou University, No. 222 South Tianshui Road, Lanzhou 730000, China
| | - Yan Ma
- School of Information Science & Engineering, Lanzhou University, No. 222 South Tianshui Road, Lanzhou 730000, China
| | - Dongxu Huo
- School of Information Science & Engineering, Lanzhou University, No. 222 South Tianshui Road, Lanzhou 730000, China
| | - Matthew J L Mills
- 3M Corporate Research Analytical Laboratory, Saint Paul, Minnesota 55114, United States
| | - Jiaxuan Wei
- School of Information Science & Engineering, Lanzhou University, No. 222 South Tianshui Road, Lanzhou 730000, China
| | - Wei Su
- School of Information Science & Engineering, Lanzhou University, No. 222 South Tianshui Road, Lanzhou 730000, China
| | - Ruisheng Zhang
- School of Information Science & Engineering, Lanzhou University, No. 222 South Tianshui Road, Lanzhou 730000, China
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170
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Gerig JT. Examination of Interactions of Hexafluoro-2-propanol with Trp-Cage in Hexafluoro-2-propanol-Water by MD Simulations and Intermolecular Nuclear Overhauser Effects. J Phys Chem B 2020; 124:9793-9802. [PMID: 33095591 DOI: 10.1021/acs.jpcb.0c06476] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
All-atom molecular dynamic simulations of the peptide Trp-cage in 30% hexafluoro-2-propanol- water (V/V) at 278 K have been carried out with the goal of exploring peptide hydrogen-solvent fluorine nuclear spin cross relaxation. Force field parameters for HFIP reported by Fioroni et al. along with the fluorine parameters of the TFE5 model reported by this lab were used. Water was represented by the TIP5P-Ew model. Peptide modeling used the AMBER99SB-ILDN force field. Translational diffusion coefficients of solution components at 278 K were predicted to within 35% of experimental values using these parameter sets. The simulations indicate that the solvent mixture is not homogeneous, with HFIP molecules clustered into aggregates as large as 53 fluoroalcohol molecules. The solvent environment of surface atoms of Trp-cage fluctuates between being HFIP-rich and more water-rich about every 10 ns. In accord with previous studies by other groups, the average concentration of HFIP near the surface of the peptide is significantly enhanced over the concentration of HFIP in the bulk solvent. In the simulations, ∼7% of the initial contacts between HFIP molecules and Trp-cage develop into peptide-fluoroalcohol interactions that persist for times as long as 8 ns. Most of the available experimental nuclear spin cross-relaxation rates (ΣHF) for hydrogens of the Trp-cage in 30% HFIP-water are reproduced from the MD trajectories to within uncertainties of the experimental data and the simulations. However, a few calculated ΣHF values for hydrogens of the Trp-cage do not agree with experiment. These tend to be situations where long-lived peptide-HFIP interactions are predicted. The disagreements between observed and calculated ΣHF in these instances signal defects in the modeling parameters and procedures that are presently unrecognized.
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Affiliation(s)
- J T Gerig
- Department of Chemistry & Biochemistry University of California, Santa Barbara Santa Barbara, California 93106, United States
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171
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Amin KS, Hu X, Salahub DR, Baldauf C, Lim C, Noskov S. Benchmarking polarizable and non-polarizable force fields for Ca2+–peptides against a comprehensive QM dataset. J Chem Phys 2020; 153:144102. [DOI: 10.1063/5.0020768] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Affiliation(s)
- Kazi S. Amin
- CMS – Centre for Molecular Simulation and Department of Biological Sciences, University of Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada
| | - Xiaojuan Hu
- Fritz-Haber-Institut der Max-Planck-Gesellschaft, Faradayweg 4-6, 14195 Berlin, Germany
| | - Dennis R. Salahub
- Department of Chemistry, CMS – Centre for Molecular Simulation, IQST – Institute for Quantum Science and Technology, Quantum Alberta, University of Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada
| | - Carsten Baldauf
- Fritz-Haber-Institut der Max-Planck-Gesellschaft, Faradayweg 4-6, 14195 Berlin, Germany
| | - Carmay Lim
- Institute of Biomedical Sciences, Academia Sinica, Taipei 115, Taiwan
- Department of Chemistry, National Tsing Hua University, Hsinchu 300, Taiwan
| | - Sergei Noskov
- CMS – Centre for Molecular Simulation and Department of Biological Sciences, University of Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada
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172
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Xiong Y, Shabane PS, Onufriev AV. Melting Points of OPC and OPC3 Water Models. ACS OMEGA 2020; 5:25087-25094. [PMID: 33043187 PMCID: PMC7542584 DOI: 10.1021/acsomega.0c02638] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Accepted: 08/27/2020] [Indexed: 06/11/2023]
Abstract
A recently introduced family of globally optimal water models, OPC, has shown promise in a variety of biomolecular simulations, but properties of these water models outside of the liquid phase remain mostly unexplored. Here, we contribute to filling the gap by reporting melting temperatures of ice I h of OPC and OPC3 water models. Through the direct coexistence method, which we make available in the AMBER package, the melting points of OPC and OPC3 are estimated as 242 and 210 K, similar to TIP4P-Ew and SPC/E models, respectively, and appreciably below the experimental value of 273.15 K under 1 bar pressure. Water models of the OPC family were optimized to best reproduce water properties in the liquid phase where these models offer noteworthy accuracy advantages over many models of previous generations. It is not surprising that the accuracy of OPC models in describing the phase transition to the solid state does not appear to offer similar improvements. The new anisotropic barostat option implemented in AMBER may benefit system preparation and simulation outside of the direct coexistence applications, such as modeling of membranes or very long DNA strands.
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Affiliation(s)
- Yeyue Xiong
- Department
of Biomedical Engineering and Mechanics, Virginia Tech, Blacksburg 24061-0131, United States
| | | | - Alexey V. Onufriev
- Department
of Physics, Virginia Tech, Blacksburg 24061-0131, United States
- Department
of Computer Science, Virginia Tech Department of Physics, Virginia Tech, Blacksburg 24061-0131, United States
- Center
for Soft Matter and Biological Physics, Virginia Tech, Blacksburg 24061-0131, United States
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173
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He X, Man VH, Yang W, Lee TS, Wang J. A fast and high-quality charge model for the next generation general AMBER force field. J Chem Phys 2020; 153:114502. [PMID: 32962378 DOI: 10.1063/5.0019056] [Citation(s) in RCA: 217] [Impact Index Per Article: 54.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
The General AMBER Force Field (GAFF) has been broadly used by researchers all over the world to perform in silico simulations and modelings on diverse scientific topics, especially in the field of computer-aided drug design whose primary task is to accurately predict the affinity and selectivity of receptor-ligand binding. The atomic partial charges in GAFF and the second generation of GAFF (GAFF2) were originally developed with the quantum mechanics derived restrained electrostatic potential charge, but in practice, users usually adopt an efficient charge method, Austin Model 1-bond charge corrections (AM1-BCC), based on which, without expensive ab initio calculations, the atomic charges could be efficiently and conveniently obtained with the ANTECHAMBER module implemented in the AMBER software package. In this work, we developed a new set of BCC parameters specifically for GAFF2 using 442 neutral organic solutes covering diverse functional groups in aqueous solution. Compared to the original BCC parameter set, the new parameter set significantly reduced the mean unsigned error (MUE) of hydration free energies from 1.03 kcal/mol to 0.37 kcal/mol. More excitingly, this new AM1-BCC model also showed excellent performance in the solvation free energy (SFE) calculation on diverse solutes in various organic solvents across a range of different dielectric constants. In this large-scale test with totally 895 neutral organic solvent-solute systems, the new parameter set led to accurate SFE predictions with the MUE and the root-mean-square-error of 0.51 kcal/mol and 0.65 kcal/mol, respectively. This newly developed charge model, ABCG2, paved a promising path for the next generation GAFF development.
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Affiliation(s)
- Xibing He
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, USA
| | - Viet H Man
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, USA
| | - Wei Yang
- Department of Chemistry and Biochemistry and Institute of Molecular Biophysics, Florida State University, Tallahassee, Florida 32306, USA
| | - Tai-Sung Lee
- Laboratory for Biomolecular Simulation Research, Center for Integrative Proteomics Research, and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, New Jersey 08854, USA
| | - Junmei Wang
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, USA
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174
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van der Spoel D. Systematic design of biomolecular force fields. Curr Opin Struct Biol 2020; 67:18-24. [PMID: 32980615 DOI: 10.1016/j.sbi.2020.08.006] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Revised: 08/24/2020] [Accepted: 08/25/2020] [Indexed: 02/07/2023]
Abstract
Force fields for the study of biomolecules have been developed in a predominantly organic manner by regular updates over half a century. Together with better algorithms and advances in computer technology, force fields have improved to yield more robust predictions. However, there are also indications to suggest that intramolecular energy functions have not become better and that there still is room for improvement. In this review, systematic efforts toward development of novel force fields from scratch are described. This includes an estimate of the complexity of the problem and the prerequisites in the form of data and algorithms. It is suggested that in order to make progress, an effort is needed to standardize reference data and force field validation benchmarks.
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175
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Lazim R, Suh D, Choi S. Advances in Molecular Dynamics Simulations and Enhanced Sampling Methods for the Study of Protein Systems. Int J Mol Sci 2020; 21:E6339. [PMID: 32882859 PMCID: PMC7504087 DOI: 10.3390/ijms21176339] [Citation(s) in RCA: 68] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Revised: 08/10/2020] [Accepted: 08/11/2020] [Indexed: 12/12/2022] Open
Abstract
Molecular dynamics (MD) simulation is a rigorous theoretical tool that when used efficiently could provide reliable answers to questions pertaining to the structure-function relationship of proteins. Data collated from protein dynamics can be translated into useful statistics that can be exploited to sieve thermodynamics and kinetics crucial for the elucidation of mechanisms responsible for the modulation of biological processes such as protein-ligand binding and protein-protein association. Continuous modernization of simulation tools enables accurate prediction and characterization of the aforementioned mechanisms and these qualities are highly beneficial for the expedition of drug development when effectively applied to structure-based drug design (SBDD). In this review, current all-atom MD simulation methods, with focus on enhanced sampling techniques, utilized to examine protein structure, dynamics, and functions are discussed. This review will pivot around computer calculations of protein-ligand and protein-protein systems with applications to SBDD. In addition, we will also be highlighting limitations faced by current simulation tools as well as the improvements that have been made to ameliorate their efficiency.
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Affiliation(s)
- Raudah Lazim
- College of Pharmacy and Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul 03760, Korea
| | - Donghyuk Suh
- College of Pharmacy and Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul 03760, Korea
| | - Sun Choi
- College of Pharmacy and Graduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul 03760, Korea
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176
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Bissaro M, Sturlese M, Moro S. The rise of molecular simulations in fragment-based drug design (FBDD): an overview. Drug Discov Today 2020; 25:1693-1701. [PMID: 32592867 PMCID: PMC7314695 DOI: 10.1016/j.drudis.2020.06.023] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2020] [Revised: 05/24/2020] [Accepted: 06/19/2020] [Indexed: 12/31/2022]
Abstract
Fragment-based drug discovery (FBDD) is an innovative approach, progressively more applied in the academic and industrial context, to enhance hit identification for previously considered undruggable biological targets. In particular, FBDD discovers low-molecular-weight (LMW) ligands (<300Da) able to bind to therapeutically relevant macromolecules in an affinity range from the micromolar (μM) to millimolar (mM). X-ray crystallography (XRC) and nuclear magnetic resonance (NMR) spectroscopy are commonly the methods of choice to obtain 3D information about the bound ligand-protein complex, but this can occasionally be problematic, mainly for early, low-affinity fragments. The recent development of computational fragment-based approaches provides a further strategy for improving the identification of fragment hits. In this review, we summarize the state of the art of molecular dynamics simulations approaches used in FBDD, and discuss limitations and future perspectives for these approaches.
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Affiliation(s)
- Maicol Bissaro
- Molecular Modeling Section, Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Padova, Italy
| | - Mattia Sturlese
- Molecular Modeling Section, Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Padova, Italy
| | - Stefano Moro
- Molecular Modeling Section, Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Padova, Italy.
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177
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Yang X, Liu C, Walker BD, Ren P. Accurate description of molecular dipole surface with charge flux implemented for molecular mechanics. J Chem Phys 2020; 153:064103. [DOI: 10.1063/5.0016376] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Xudong Yang
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, 78712 Texas, USA
| | - Chengwen Liu
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, 78712 Texas, USA
| | - Brandon D. Walker
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, 78712 Texas, USA
| | - Pengyu Ren
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, 78712 Texas, USA
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178
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Long QT Syndrome Type 2: Emerging Strategies for Correcting Class 2 KCNH2 ( hERG) Mutations and Identifying New Patients. Biomolecules 2020. [PMID: 32759882 DOI: 10.3390/biom10081144s] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/25/2023] Open
Abstract
Significant advances in our understanding of the molecular mechanisms that cause congenital long QT syndrome (LQTS) have been made. A wide variety of experimental approaches, including heterologous expression of mutant ion channel proteins and the use of inducible pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) from LQTS patients offer insights into etiology and new therapeutic strategies. This review briefly discusses the major molecular mechanisms underlying LQTS type 2 (LQT2), which is caused by loss-of-function (LOF) mutations in the KCNH2 gene (also known as the human ether-à-go-go-related gene or hERG). Almost half of suspected LQT2-causing mutations are missense mutations, and functional studies suggest that about 90% of these mutations disrupt the intracellular transport, or trafficking, of the KCNH2-encoded Kv11.1 channel protein to the cell surface membrane. In this review, we discuss emerging strategies that improve the trafficking and functional expression of trafficking-deficient LQT2 Kv11.1 channel proteins to the cell surface membrane and how new insights into the structure of the Kv11.1 channel protein will lead to computational approaches that identify which KCNH2 missense variants confer a high-risk for LQT2.
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179
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Cuevas-Zuviría B, Pacios LF. Analytical Model of Electron Density and Its Machine Learning Inference. J Chem Inf Model 2020; 60:3831-3842. [DOI: 10.1021/acs.jcim.0c00197] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Affiliation(s)
- Bruno Cuevas-Zuviría
- Centro de Biotecnologı́a y Genómica de Plantas (CBGP, UPM-INIA), Instituto Nacional de Investigación y Tecnologı́a Agraria y Alimentaria (INIA), Universidad Politécnica de Madrid (UPM), Campus de Montegancedo-UPM, Pozuelo de Alarcón, 28223 Madrid, Spain
| | - Luis F. Pacios
- Centro de Biotecnologı́a y Genómica de Plantas (CBGP, UPM-INIA), Instituto Nacional de Investigación y Tecnologı́a Agraria y Alimentaria (INIA), Universidad Politécnica de Madrid (UPM), Campus de Montegancedo-UPM, Pozuelo de Alarcón, 28223 Madrid, Spain
- Departamento de Biotecnologı́a-Biologı́a Vegetal, Escuela Técnica Superior de Ingenierı́a Agraria, Alimentaria y de Biosistemas (ETSIAAB), Universidad Politécnica de Madrid (UPM), 28040 Madrid, Spain
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180
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Ono M, Burgess DE, Schroder EA, Elayi CS, Anderson CL, January CT, Sun B, Immadisetty K, Kekenes-Huskey PM, Delisle BP. Long QT Syndrome Type 2: Emerging Strategies for Correcting Class 2 KCNH2 ( hERG) Mutations and Identifying New Patients. Biomolecules 2020; 10:E1144. [PMID: 32759882 PMCID: PMC7464307 DOI: 10.3390/biom10081144] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 07/25/2020] [Accepted: 07/27/2020] [Indexed: 12/15/2022] Open
Abstract
Significant advances in our understanding of the molecular mechanisms that cause congenital long QT syndrome (LQTS) have been made. A wide variety of experimental approaches, including heterologous expression of mutant ion channel proteins and the use of inducible pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) from LQTS patients offer insights into etiology and new therapeutic strategies. This review briefly discusses the major molecular mechanisms underlying LQTS type 2 (LQT2), which is caused by loss-of-function (LOF) mutations in the KCNH2 gene (also known as the human ether-à-go-go-related gene or hERG). Almost half of suspected LQT2-causing mutations are missense mutations, and functional studies suggest that about 90% of these mutations disrupt the intracellular transport, or trafficking, of the KCNH2-encoded Kv11.1 channel protein to the cell surface membrane. In this review, we discuss emerging strategies that improve the trafficking and functional expression of trafficking-deficient LQT2 Kv11.1 channel proteins to the cell surface membrane and how new insights into the structure of the Kv11.1 channel protein will lead to computational approaches that identify which KCNH2 missense variants confer a high-risk for LQT2.
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Affiliation(s)
- Makoto Ono
- Department of Physiology, Cardiovascular Research Center, Center for Muscle Biology, University of Kentucky, Lexington, KY 40536, USA; (M.O.); (D.E.B.); (E.A.S.)
| | - Don E. Burgess
- Department of Physiology, Cardiovascular Research Center, Center for Muscle Biology, University of Kentucky, Lexington, KY 40536, USA; (M.O.); (D.E.B.); (E.A.S.)
| | - Elizabeth A. Schroder
- Department of Physiology, Cardiovascular Research Center, Center for Muscle Biology, University of Kentucky, Lexington, KY 40536, USA; (M.O.); (D.E.B.); (E.A.S.)
| | | | - Corey L. Anderson
- Cellular and Molecular Arrhythmia Research Program, University of Wisconsin, Madison, WI 53706, USA; (C.L.A.); (C.T.J.)
| | - Craig T. January
- Cellular and Molecular Arrhythmia Research Program, University of Wisconsin, Madison, WI 53706, USA; (C.L.A.); (C.T.J.)
| | - Bin Sun
- Department of Cellular & Molecular Physiology, Loyola University Chicago, Chicago, IL 60153, USA; (B.S.); (K.I.); (P.M.K.-H.)
| | - Kalyan Immadisetty
- Department of Cellular & Molecular Physiology, Loyola University Chicago, Chicago, IL 60153, USA; (B.S.); (K.I.); (P.M.K.-H.)
| | - Peter M. Kekenes-Huskey
- Department of Cellular & Molecular Physiology, Loyola University Chicago, Chicago, IL 60153, USA; (B.S.); (K.I.); (P.M.K.-H.)
| | - Brian P. Delisle
- Department of Physiology, Cardiovascular Research Center, Center for Muscle Biology, University of Kentucky, Lexington, KY 40536, USA; (M.O.); (D.E.B.); (E.A.S.)
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181
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Scheen J, Wu W, Mey ASJS, Tosco P, Mackey M, Michel J. Hybrid Alchemical Free Energy/Machine-Learning Methodology for the Computation of Hydration Free Energies. J Chem Inf Model 2020; 60:5331-5339. [PMID: 32639733 DOI: 10.1021/acs.jcim.0c00600] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
A methodology that combines alchemical free energy calculations (FEP) with machine learning (ML) has been developed to compute accurate absolute hydration free energies. The hybrid FEP/ML methodology was trained on a subset of the FreeSolv database and retrospectively shown to outperform most submissions from the SAMPL4 competition. Compared to pure machine-learning approaches, FEP/ML yields more precise estimates of free energies of hydration and requires a fraction of the training set size to outperform standalone FEP calculations. The ML-derived correction terms are further shown to be transferable to a range of related FEP simulation protocols. The approach may be used to inexpensively improve the accuracy of FEP calculations and to flag molecules which will benefit the most from bespoke force field parametrization efforts.
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Affiliation(s)
- Jenke Scheen
- EaStCHEM School of Chemistry, University of Edinburgh, David Brewster Road, Edinburgh EH9 3FJ, United Kingdom
| | - Wilson Wu
- EaStCHEM School of Chemistry, University of Edinburgh, David Brewster Road, Edinburgh EH9 3FJ, United Kingdom
| | - Antonia S J S Mey
- EaStCHEM School of Chemistry, University of Edinburgh, David Brewster Road, Edinburgh EH9 3FJ, United Kingdom
| | - Paolo Tosco
- Cresset Group, New Cambridge House, Bassingbourn Road, Litlington, Cambridgeshire SG8 0SS, United Kingdom
| | - Mark Mackey
- Cresset Group, New Cambridge House, Bassingbourn Road, Litlington, Cambridgeshire SG8 0SS, United Kingdom
| | - Julien Michel
- EaStCHEM School of Chemistry, University of Edinburgh, David Brewster Road, Edinburgh EH9 3FJ, United Kingdom
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182
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Giovannini T, Egidi F, Cappelli C. Molecular spectroscopy of aqueous solutions: a theoretical perspective. Chem Soc Rev 2020; 49:5664-5677. [PMID: 32744278 DOI: 10.1039/c9cs00464e] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/28/2024]
Abstract
Computational spectroscopy is an invaluable tool to both accurately reproduce the spectra of molecular systems and provide a rationalization for the underlying physics. However, the inherent difficulty to accurately model systems in aqueous solutions, owing to water's high polarity and ability to form hydrogen bonds, has severely hampered the development of the field. In this tutorial review we present a technique developed and tested in recent years based on a fully atomistic and polarizable classical modeling of water coupled with a quantum mechanical description of the solute. Thanks to its unparalleled accuracy and versatility, this method can change the perspective of computational and experimental chemists alike.
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Affiliation(s)
| | - Franco Egidi
- Scuola Normale Superiore, Piazza dei Cavalieri 7, I-56126 Pisa, Italy.
| | - Chiara Cappelli
- Scuola Normale Superiore, Piazza dei Cavalieri 7, I-56126 Pisa, Italy.
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183
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Acharya A, Agarwal R, Baker M, Baudry J, Bhowmik D, Boehm S, Byler KG, Coates L, Chen SY, Cooper CJ, Demerdash O, Daidone I, Eblen JD, Ellingson S, Forli S, Glaser J, Gumbart JC, Gunnels J, Hernandez O, Irle S, Larkin J, Lawrence TJ, LeGrand S, Liu SH, Mitchell JC, Park G, Parks JM, Pavlova A, Petridis L, Poole D, Pouchard L, Ramanathan A, Rogers D, Santos-Martins D, Scheinberg A, Sedova A, Shen S, Smith JC, Smith MD, Soto C, Tsaris A, Thavappiragasam M, Tillack AF, Vermaas JV, Vuong VQ, Yin J, Yoo S, Zahran M, Zanetti-Polzi L. Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19. CHEMRXIV : THE PREPRINT SERVER FOR CHEMISTRY 2020:12725465. [PMID: 33200117 PMCID: PMC7668744 DOI: 10.26434/chemrxiv.12725465] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Revised: 07/29/2020] [Indexed: 01/18/2023]
Abstract
We present a supercomputer-driven pipeline for in-silico drug discovery using enhanced sampling molecular dynamics (MD) and ensemble docking. We also describe preliminary results obtained for 23 systems involving eight protein targets of the proteome of SARS CoV-2. THe MD performed is temperature replica-exchange enhanced sampling, making use of the massively parallel supercomputing on the SUMMIT supercomputer at Oak Ridge National Laboratory, with which more than 1ms of enhanced sampling MD can be generated per day. We have ensemble docked repurposing databases to ten configurations of each of the 23 SARS CoV-2 systems using AutoDock Vina. We also demonstrate that using Autodock-GPU on SUMMIT, it is possible to perform exhaustive docking of one billion compounds in under 24 hours. Finally, we discuss preliminary results and planned improvements to the pipeline, including the use of quantum mechanical (QM), machine learning, and AI methods to cluster MD trajectories and rescore docking poses.
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Affiliation(s)
- A Acharya
- School of Physics, Georgia Institute of Technology, Atlanta, GA 30332
| | - R Agarwal
- UT/ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory, TN, 37830
- The University of Tennessee, Knoxville. Department of Biochemistry & Cellular and Molecular Biology, 309 Ken and Blaire Mossman Bldg. 1311 Cumberland Avenue Knoxville, TN, 37996
- Graduate School of Genome Science and Technology, University of Tennessee, Knoxville, TN, 37996
| | - M Baker
- Computer Science and Mathematics Division, Oak Ridge National Lab, Oak Ridge, TN 37830
| | - J Baudry
- The University of Alabama in Huntsville, Department of Biological Sciences. 301 Sparkman Drive, Huntsville, AL 35899
| | - D Bhowmik
- Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831
| | - S Boehm
- Computer Science and Mathematics Division, Oak Ridge National Lab, Oak Ridge, TN 37830
| | - K G Byler
- The University of Alabama in Huntsville, Department of Biological Sciences. 301 Sparkman Drive, Huntsville, AL 35899
| | - L Coates
- Neutron Scattering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831
| | - S Y Chen
- Computational Science Initiative, Brookhaven National Laboratory, Upton, NY 11973
| | - C J Cooper
- UT/ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory, TN, 37830
- Graduate School of Genome Science and Technology, University of Tennessee, Knoxville, TN, 37996
| | - O Demerdash
- Biosciences Division, Oak Ridge National Lab, Oak Ridge, TN 37830
| | - I Daidone
- Department of Physical and Chemical Sciences, University of L'Aquila, I-67010 L'Aquila, Italy
| | - J D Eblen
- UT/ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory, TN, 37830
- The University of Tennessee, Knoxville. Department of Biochemistry & Cellular and Molecular Biology, 309 Ken and Blaire Mossman Bldg. 1311 Cumberland Avenue Knoxville, TN, 37996
| | - S Ellingson
- University of Kentucky, Division of Biomedical Informatics, College of Medicine, UK Medical Center MN 150, Lexington KY, 40536
| | - S Forli
- Scripps Research, La Jolla, CA, 92037
| | - J Glaser
- National Center for Computational Sciences, Oak Ridge National Laboratory, Oak Ridge, TN 37830
| | - J C Gumbart
- School of Physics, Georgia Institute of Technology, Atlanta, GA 30332
| | - J Gunnels
- HPC Engineering, Amazon Web Services, Seattle, WA 98121
| | - O Hernandez
- Computer Science and Mathematics Division, Oak Ridge National Lab, Oak Ridge, TN 37830
| | - S Irle
- Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831
- Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee, Knoxville, TN 37996
| | - J Larkin
- NVIDIA Corporation, Santa Clara, CA 95051
| | - T J Lawrence
- Biosciences Division, Oak Ridge National Lab, Oak Ridge, TN 37830
| | - S LeGrand
- NVIDIA Corporation, Santa Clara, CA 95051
| | - S-H Liu
- UT/ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory, TN, 37830
- The University of Tennessee, Knoxville. Department of Biochemistry & Cellular and Molecular Biology, 309 Ken and Blaire Mossman Bldg. 1311 Cumberland Avenue Knoxville, TN, 37996
| | - J C Mitchell
- Biosciences Division, Oak Ridge National Lab, Oak Ridge, TN 37830
| | - G Park
- Computational Science Initiative, Brookhaven National Laboratory, Upton, NY 11973
| | - J M Parks
- UT/ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory, TN, 37830
- The University of Tennessee, Knoxville. Department of Biochemistry & Cellular and Molecular Biology, 309 Ken and Blaire Mossman Bldg. 1311 Cumberland Avenue Knoxville, TN, 37996
- Graduate School of Genome Science and Technology, University of Tennessee, Knoxville, TN, 37996
| | - A Pavlova
- School of Physics, Georgia Institute of Technology, Atlanta, GA 30332
| | - L Petridis
- UT/ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory, TN, 37830
- The University of Tennessee, Knoxville. Department of Biochemistry & Cellular and Molecular Biology, 309 Ken and Blaire Mossman Bldg. 1311 Cumberland Avenue Knoxville, TN, 37996
| | - D Poole
- NVIDIA Corporation, Santa Clara, CA 95051
| | - L Pouchard
- Computational Science Initiative, Brookhaven National Laboratory, Upton, NY 11973
| | - A Ramanathan
- Data Science and Learning Division, Argonne National Lab, Lemont, IL 60439
| | - D Rogers
- National Center for Computational Sciences, Oak Ridge National Laboratory, Oak Ridge, TN 37830
| | | | | | - A Sedova
- Biosciences Division, Oak Ridge National Lab, Oak Ridge, TN 37830
| | - S Shen
- UT/ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory, TN, 37830
- The University of Tennessee, Knoxville. Department of Biochemistry & Cellular and Molecular Biology, 309 Ken and Blaire Mossman Bldg. 1311 Cumberland Avenue Knoxville, TN, 37996
- Graduate School of Genome Science and Technology, University of Tennessee, Knoxville, TN, 37996
| | - J C Smith
- UT/ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory, TN, 37830
- The University of Tennessee, Knoxville. Department of Biochemistry & Cellular and Molecular Biology, 309 Ken and Blaire Mossman Bldg. 1311 Cumberland Avenue Knoxville, TN, 37996
| | - M D Smith
- UT/ORNL Center for Molecular Biophysics, Oak Ridge National Laboratory, TN, 37830
- The University of Tennessee, Knoxville. Department of Biochemistry & Cellular and Molecular Biology, 309 Ken and Blaire Mossman Bldg. 1311 Cumberland Avenue Knoxville, TN, 37996
| | - C Soto
- Computational Science Initiative, Brookhaven National Laboratory, Upton, NY 11973
| | - A Tsaris
- National Center for Computational Sciences, Oak Ridge National Laboratory, Oak Ridge, TN 37830
| | | | | | - J V Vermaas
- National Center for Computational Sciences, Oak Ridge National Laboratory, Oak Ridge, TN 37830
| | - V Q Vuong
- Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831
- Bredesen Center for Interdisciplinary Research and Graduate Education, University of Tennessee, Knoxville, TN 37996
| | - J Yin
- National Center for Computational Sciences, Oak Ridge National Laboratory, Oak Ridge, TN 37830
| | - S Yoo
- Computational Science Initiative, Brookhaven National Laboratory, Upton, NY 11973
| | - M Zahran
- Department of Biological Sciences, New York City College of Technology, The City University of New York (CUNY), Brooklyn, NY 11201
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184
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Kelly BD, Smith WR. A Simple Method for Including Polarization Effects in Solvation Free Energy Calculations When Using Fixed-Charge Force Fields: Alchemically Polarized Charges. ACS OMEGA 2020; 5:17170-17181. [PMID: 32715202 PMCID: PMC7376688 DOI: 10.1021/acsomega.0c01148] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Accepted: 06/11/2020] [Indexed: 06/11/2023]
Abstract
The incorporation of polarizability in classical force-field molecular simulations is an ongoing area of research. We focus here on its application to hydration free energy simulations of organic molecules. In contrast to computationally complex approaches involving the development of explicitly polarizable force fields, we present herein a simple methodology for incorporating polarization into such simulations using standard fixed-charge force fields, which we call the alchemically polarized charges (APolQ) method. APolQ employs a standard classical alchemical free energy change simulation to calculate the free energy difference between a fully polarized solute particle in a condensed phase and its unpolarized state in a vacuum. APolQ can in principle be applied to any microscopically homogeneous system (e.g., pure or mixed solvents). We applied APolQ to hydration free energy data for a test set of 45 neutral solute molecules in the FreeSolv database and compared results obtained using three different water models (SPC/E, TIP3P, and OPC3) and using minimal basis iterative Stockholder (MBIS) and restrained electrostatic potential (RESP) partial charge methodologies. In comparison with AM1-BCC, we found that APolQ outperforms it for the test set. Despite our method using default GAFF parameters, the MBIS partial charges yield absolute average deviations 1.5-1.9 kJ mol-1 lower than using AM1 bond charge correction (AM1-BCC). We conjecture that this method can be further improved by fitting the Lennard-Jones and torsional parameters to partial charges derived using MBIS or RESP methodologies.
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Affiliation(s)
- Braden D. Kelly
- Department
of Mathematics and Statistics, University
of Guelph, Guelph, Ontario N1G 2W1, Canada
| | - William R. Smith
- Department
of Mathematics and Statistics, University
of Guelph, Guelph, Ontario N1G 2W1, Canada
- Department
of Chemical Engineering, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada
- Faculty
of Science, Ontario Tech University, Oshawa, Ontario L1H 7K4, Canada
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185
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KRAS(G12C)-AMG 510 interaction dynamics revealed by all-atom molecular dynamics simulations. Sci Rep 2020; 10:11992. [PMID: 32686745 PMCID: PMC7371895 DOI: 10.1038/s41598-020-68950-y] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Accepted: 07/03/2020] [Indexed: 01/02/2023] Open
Abstract
The first KRAS(G12C) targeting inhibitor in clinical development, AMG 510, has shown promising antitumor activity in clinical trials. On the molecular level, however, the interaction dynamics of this covalently bound drug–protein complex has been undetermined. Here, we disclose the interaction dynamics of the KRAS(G12C)–AMG 510 complex by long timescale all-atom molecular dynamics (MD) simulations (total of 75 μs). Moreover, we investigated the influence of the recently reported post-translational modification (PTM) of KRAS’ N-terminus, removal of initiator methionine (iMet1) with acetylation of Thr2, to this complex. Our results demonstrate that AMG 510 does not entrap KRAS into a single conformation, as one would expect based on the crystal structure, but rather into an ensemble of conformations. AMG 510 binding is extremely stable regardless of highly dynamic interface of KRAS’ switches. Overall, KRAS(G12C)–AMG 510 complex partially mimic the native dynamics of GDP bound KRAS; however, AMG 510 stabilizes the α3-helix region. N-terminally modified KRAS displays similar interaction dynamics with AMG 510 as when Met1 is present, but this PTM appears to stabilize β2–β3-loop. These results provide novel conformational insights on the molecular level to KRAS(G12C)–AMG 510 interactions and dynamics, providing new perspectives to RAS related drug discovery.
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186
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Monmarché P, Weisman J, Lagardère L, Piquemal JP. Velocity jump processes: An alternative to multi-timestep methods for faster and accurate molecular dynamics simulations. J Chem Phys 2020; 153:024101. [PMID: 32668932 DOI: 10.1063/5.0005060] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
We propose a new route to accelerate molecular dynamics through the use of velocity jump processes allowing for an adaptive time step specific to each atom-atom pair (two-body) interactions. We start by introducing the formalism of the new velocity jump molecular dynamics, ergodic with respect to the canonical measure. We then introduce the new BOUNCE integrator that allows for long-range forces to be evaluated at random and optimal time steps, leading to strong savings in direct space. The accuracy and computational performances of a first BOUNCE implementation dedicated to classical (non-polarizable) force fields are tested in the cases of pure direct-space droplet-like simulations and of periodic boundary conditions (PBC) simulations using Smooth Particle Mesh Ewald method. An analysis of the capability of BOUNCE to reproduce several condensed-phase properties is provided. Since electrostatics and van der Waals two-body contributions are evaluated much less often than with standard integrators using a 1 fs time step, up to a 400% direct-space acceleration is observed. Applying the reversible reference system propagator algorithms [RESPA(1)] to reciprocal-space (many-body) interactions allows BOUNCE-RESPA(1) to maintain large speedups in PBC while maintaining precision. Overall, we show that replacing the BAOAB standard Langevin integrator by the BOUNCE adaptive framework preserves a similar accuracy and leads to significant computational savings.
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Affiliation(s)
- Pierre Monmarché
- Sorbonne Université, Laboratoire Jacques-Louis Lions, UMR 7589 CNRS, and Laboratoire de Chimie Théorique, UMR 7616 CNRS, F-75005 Paris, France
| | - Jérémy Weisman
- Sorbonne Université, Laboratoire de Chimie Théorique, UMR 7616 CNRS, F-75005 Paris, France
| | - Louis Lagardère
- Sorbonne Université, Laboratoire de Chimie Théorique, UMR 7616 CNRS, F-75005 Paris, France
| | - Jean-Philip Piquemal
- Sorbonne Université, Laboratoire de Chimie Théorique, UMR 7616 CNRS, F-75005 Paris, France
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187
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Palomino‐Hernandez O, Margreiter MA, Rossetti G. Challenges in RNA Regulation in Huntington's Disease: Insights from Computational Studies. Isr J Chem 2020. [DOI: 10.1002/ijch.202000021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Oscar Palomino‐Hernandez
- Computational Biomedicine, Institute of Neuroscience and Medicine (INM-9)/Instute for advanced simulations (IAS-5)Forschungszentrum Juelich 52425 Jülich Germany
- Faculty 1RWTH Aachen 52425 Aachen Germany
- Computation-based Science and Technology Research CenterThe Cyprus Institute Nicosia 2121 Cyprus
- Institute of Life ScienceThe Hebrew University of Jerusalem Jerusalem 91904 Israel
| | - Michael A. Margreiter
- Computational Biomedicine, Institute of Neuroscience and Medicine (INM-9)/Instute for advanced simulations (IAS-5)Forschungszentrum Juelich 52425 Jülich Germany
- Faculty 1RWTH Aachen 52425 Aachen Germany
| | - Giulia Rossetti
- Computational Biomedicine, Institute of Neuroscience and Medicine (INM-9)/Instute for advanced simulations (IAS-5)Forschungszentrum Juelich 52425 Jülich Germany
- Jülich Supercomputing Centre (JSC)Forschungszentrum Jülich 52425 Jülich Germany
- Department of Hematology, Oncology, Hemostaseology and Stem Cell Transplantation University Hospital AachenRWTH Aachen University Pauwelsstraße 30 52074 Aachen Germany
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188
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Marcellini M, Nguyen MH, Martin M, Hologne M, Walker O. Accurate Prediction of Protein NMR Spin Relaxation by Means of Polarizable Force Fields. Application to Strongly Anisotropic Rotational Diffusion. J Phys Chem B 2020; 124:5103-5112. [DOI: 10.1021/acs.jpcb.0c01922] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Affiliation(s)
- Moreno Marcellini
- Institut des Sciences Analytiques (ISA), Univ Lyon, CNRS, UMR5280, Université Claude Bernard Lyon1, Lyon, France
| | - Minh-Ha Nguyen
- Institut des Sciences Analytiques (ISA), Univ Lyon, CNRS, UMR5280, Université Claude Bernard Lyon1, Lyon, France
| | - Marie Martin
- Institut des Sciences Analytiques (ISA), Univ Lyon, CNRS, UMR5280, Université Claude Bernard Lyon1, Lyon, France
| | - Maggy Hologne
- Institut des Sciences Analytiques (ISA), Univ Lyon, CNRS, UMR5280, Université Claude Bernard Lyon1, Lyon, France
| | - Olivier Walker
- Institut des Sciences Analytiques (ISA), Univ Lyon, CNRS, UMR5280, Université Claude Bernard Lyon1, Lyon, France
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189
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Willow SY, Xie B, Lawrence J, Eisenberg RS, Minh DDL. On the polarization of ligands by proteins. Phys Chem Chem Phys 2020; 22:12044-12057. [PMID: 32421120 PMCID: PMC8118567 DOI: 10.1039/d0cp00376j] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Although ligand-binding sites in many proteins contain a high number density of charged side chains that can polarize small organic molecules and influence binding, the magnitude of this effect has not been studied in many systems. Here, we use a quantum mechanics/molecular mechanics (QM/MM) approach, in which the ligand is the QM region, to compute the ligand polarization energy of 286 protein-ligand complexes from the PDBBind Core Set (release 2016). Calculations were performed both with and without implicit solvent based on the domain decomposition Conductor-like Screening Model. We observe that the ligand polarization energy is linearly correlated with the magnitude of the electric field acting on the ligand, the magnitude of the induced dipole moment, and the classical polarization energy. The influence of protein and cation charges on the ligand polarization diminishes with the distance and is below 2 kcal mol-1 at 9 Å and 1 kcal mol-1 at 12 Å. Compared to these embedding field charges, implicit solvent has a relatively minor effect on ligand polarization. Considering both polarization and solvation appears essential to computing negative binding energies in some crystallographic complexes. Solvation, but not polarization, is essential for achieving moderate correlation with experimental binding free energies.
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Affiliation(s)
- Soohaeng Yoo Willow
- Department of Chemistry, Illinois Institute of Technology, Chicago, Illinois 60616, USA.
| | - Bing Xie
- Department of Chemistry, Illinois Institute of Technology, Chicago, Illinois 60616, USA.
| | - Jason Lawrence
- Department of Computer Science, Illinois Institute of Technology, Chicago, Illinois 60616, USA
| | - Robert S Eisenberg
- Department of Applied Mathematics, Illinois Institute of Technology, Chicago, Illinois 60616, USA
| | - David D L Minh
- Department of Chemistry, Illinois Institute of Technology, Chicago, Illinois 60616, USA.
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190
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Tolmachev D, Lukasheva N, Mamistvalov G, Karttunen M. Influence of Calcium Binding on Conformations and Motions of Anionic Polyamino Acids. Effect of Side Chain Length. Polymers (Basel) 2020; 12:E1279. [PMID: 32503199 PMCID: PMC7362111 DOI: 10.3390/polym12061279] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 05/29/2020] [Accepted: 05/31/2020] [Indexed: 11/21/2022] Open
Abstract
Investigation of the effect of CaCl2 salt on conformations of two anionic poly(amino acids) with different side chain lengths, poly-(α-l glutamic acid) (PGA) and poly-(α-l aspartic acid) (PASA), was performed by atomistic molecular dynamics (MD) simulations. The simulations were performed using both unbiased MD and the Hamiltonian replica exchange (HRE) method. The results show that at low CaCl2 concentration adsorption of Ca2+ ions lead to a significant chain size reduction for both PGA and PASA. With the increase in concentration, the chains sizes partially recover due to electrostatic repulsion between the adsorbed Ca2+ ions. Here, the side chain length becomes important. Due to the longer side chain and its ability to distance the charged groups with adsorbed ions from both each other and the backbone, PGA remains longer in the collapsed state as the CaCl2 concentration is increased. The analysis of the distribution of the mineral ions suggests that both poly(amino acids) should induce the formation of mineral with the same structure of the crystal cell.
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Affiliation(s)
- Dmitry Tolmachev
- Institute of Macromolecular Compounds, Russian Academy of Sciences, Bolshoy pr. 31, 199004 St. Petersburg, Russia;
| | - Natalia Lukasheva
- Institute of Macromolecular Compounds, Russian Academy of Sciences, Bolshoy pr. 31, 199004 St. Petersburg, Russia;
| | - George Mamistvalov
- Faculty of Physics, St. Petersburg State University, Petrodvorets, 198504 St. Petersburg, Russia;
| | - Mikko Karttunen
- Institute of Macromolecular Compounds, Russian Academy of Sciences, Bolshoy pr. 31, 199004 St. Petersburg, Russia;
- Department of Chemistry, the University of Western Ontario, 1151 Richmond Street, London, ON N6A 5B7, Canada
- Department of Applied Mathematics, the University of Western Ontario, 1151 Richmond Street, London, ON N6A 5B7, Canada
- The Centre of Advanced Materials and Biomaterials Research, the University of Western Ontario, 1151 Richmond Street, London, ON N6A 5B7, Canada
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191
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Abal JPK, Bordin JR, Barbosa MC. Salt parameterization can drastically affect the results from classical atomistic simulations of water desalination by MoS 2 nanopores. Phys Chem Chem Phys 2020; 22:11053-11061. [PMID: 32373906 DOI: 10.1039/d0cp00484g] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
Water scarcity is a reality in our world, and scenarios predicted by leading scientists in this area indicate that it will worsen in the next decades. However, new technologies based on low-cost seawater desalination can prevent the worst scenarios, providing fresh water for humanity. With this goal, membranes based on nanoporous materials have been suggested in recent years. One of the materials suggested is MoS2, and classical Molecular Dynamics (MD) simulation is one of the most powerful tools to explore these nanomaterials. However, distinct force fields employed in MD simulations are parameterized based on distinct experimental quantities. In this paper, we compare two models of salt that were built based on distinct properties of water-salt mixtures. One model fits the hydration free energy and lattice properties, and the second fits the crystal density and the density and the dielectric constant of water and salt mixtures. To compare the models, MD simulations for salty water flow through nanopores of two sizes were used - one pore big enough to accommodate hydrated ions, and one smaller in which the ion has to dehydrate to enter - and two rigid water models from the TIP4P family - TIP4P/2005 and TIP4P/ε. Our results indicate that the water permeability and salt rejection by the membrane are more influenced by the salt model than by the water model, especially for the narrow pore. In fact, completely distinct mechanisms were observed, and they are related to the characteristics employed in the ion model parameterization. The results show that not only can the water model influence the outcomes, but the ion model plays a crucial role when the pore is small enough.
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Affiliation(s)
- João P K Abal
- Institute of Physics, Federal University of Rio Grande do Sul, 91501-970, Porto Alegre, Brazil.
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192
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Servis MJ, Martinez-Baez E, Clark AE. Hierarchical phenomena in multicomponent liquids: simulation methods, analysis, chemistry. Phys Chem Chem Phys 2020; 22:9850-9874. [PMID: 32154813 DOI: 10.1039/d0cp00164c] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Complex, multicomponent, solutions have often been studied solely through the lens of specific applications of interest. Yet advances to both simulation methodologies (enhanced sampling, etc.) and analysis techniques (network analysis algorithms and others), are creating a trove of data that reveal transcending characteristics across vast compositional phase space. This perspective discusses technical considerations of the reliable and accurate simulations of complex solutions, followed by the advances to analysis algorithms that elucidate coupling of different length and timescale behavior (hierarchical phenomena). The different manifestations of hierarchical phenomena are presented across an array of solution environments, emphasizing fundamental and ongoing science questions. With a more advanced molecular understanding in hand, a quintessential application (solvent extraction) is discussed, where significant opportunities exist to re-imagine the technical scope of an established technology.
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Affiliation(s)
- Michael J Servis
- Department of Chemistry, Washington State University, Pullman, WA 99164, USA.
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193
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Bradshaw RT, Dziedzic J, Skylaris CK, Essex JW. The Role of Electrostatics in Enzymes: Do Biomolecular Force Fields Reflect Protein Electric Fields? J Chem Inf Model 2020; 60:3131-3144. [DOI: 10.1021/acs.jcim.0c00217] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Affiliation(s)
- Richard T. Bradshaw
- School of Chemistry, University of Southampton, Highfield Campus, Southampton, SO17 1BJ, United Kingdom
| | - Jacek Dziedzic
- School of Chemistry, University of Southampton, Highfield Campus, Southampton, SO17 1BJ, United Kingdom
- Faculty of Applied Physics and Mathematics, Gdańsk University of Technology, 80-233 Gdańsk, Poland
| | - Chris-Kriton Skylaris
- School of Chemistry, University of Southampton, Highfield Campus, Southampton, SO17 1BJ, United Kingdom
| | - Jonathan W. Essex
- School of Chemistry, University of Southampton, Highfield Campus, Southampton, SO17 1BJ, United Kingdom
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194
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Pan C, Liu C, Peng J, Ren P, Huang X. Three-site and five-site fixed-charge water models compatible with AMOEBA force field. J Comput Chem 2020; 41:1034-1044. [PMID: 31976572 DOI: 10.1002/jcc.26151] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Accepted: 01/01/2020] [Indexed: 11/06/2022]
Abstract
In a typical biomolecular simulation using Atomic Multipole Optimized Energetics for Biomolecular Applications (AMOEBA) force field, the vast majority molecules in the simulation box consist of water, and these water molecules consume the most CPU power due to the explicit mutual induction effect. To improve the computational efficiency, we here develop two new nonpolarizable water models (with flexible bonds and fixed charges) that are compatible with AMOEBA solute: the 3-site AW3C and 5-site AW5C. To derive the force-field parameters for AW3C and AW5C, we fit to six experimental liquid thermodynamic properties: liquid density, enthalpy of vaporization, dielectric constant, isobaric heat capacity, isothermal compressibility and thermal expansion coefficient, at a broad range of temperatures from 261.15 to 353.15 K under 1.0 atm pressure. We further validate our AW3C and AW5C water models by showing that they can well reproduce the radial distribution function g(r), self-diffusion constant D, and hydration free energy from the AMOEBA03 water model and the experimental observations. Furthermore, we show that our AW3C and AW5C water models can greatly accelerate (>5 times) the bulk water as well as biomolecular simulations when compared to AMOEBA water. Specifically, we demonstrate that the applications of AW3C and AW5C water models to simulate a DNA duplex lead to a threefold acceleration, and in the meanwhile well maintain the structural properties as the fully polarizable AMOEBA water. We expect that our AW3C and AW5C water models hold great promise to be widely applied to simulate complex bio-molecules using the AMOEBA force field.
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Affiliation(s)
- Cong Pan
- Department of Chemistry, The Hong Kong University of Science and Technology, Hong Kong
| | - Chengwen Liu
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas
| | - Junhui Peng
- Department of Chemistry, The Hong Kong University of Science and Technology, Hong Kong
| | - Pengyu Ren
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas
| | - Xuhui Huang
- Department of Chemistry, The Hong Kong University of Science and Technology, Hong Kong.,Center of Systems Biology and Human Health, State Key Laboratory of Molecular Neuroscience, The Hong Kong University of Science and Technology, Kowloon, Hong Kong
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195
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Surpeta B, Sequeiros-Borja CE, Brezovsky J. Dynamics, a Powerful Component of Current and Future in Silico Approaches for Protein Design and Engineering. Int J Mol Sci 2020; 21:E2713. [PMID: 32295283 PMCID: PMC7215530 DOI: 10.3390/ijms21082713] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Revised: 04/10/2020] [Accepted: 04/12/2020] [Indexed: 12/13/2022] Open
Abstract
Computational prediction has become an indispensable aid in the processes of engineering and designing proteins for various biotechnological applications. With the tremendous progress in more powerful computer hardware and more efficient algorithms, some of in silico tools and methods have started to apply the more realistic description of proteins as their conformational ensembles, making protein dynamics an integral part of their prediction workflows. To help protein engineers to harness benefits of considering dynamics in their designs, we surveyed new tools developed for analyses of conformational ensembles in order to select engineering hotspots and design mutations. Next, we discussed the collective evolution towards more flexible protein design methods, including ensemble-based approaches, knowledge-assisted methods, and provable algorithms. Finally, we highlighted apparent challenges that current approaches are facing and provided our perspectives on their further development.
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Affiliation(s)
- Bartłomiej Surpeta
- Laboratory of Biomolecular Interactions and Transport, Department of Gene Expression, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, Uniwersytetu Poznanskiego 6, 61-614 Poznan, Poland; (B.S.); (C.E.S.-B.)
- International Institute of Molecular and Cell Biology in Warsaw, Ks Trojdena 4, 02-109 Warsaw, Poland
| | - Carlos Eduardo Sequeiros-Borja
- Laboratory of Biomolecular Interactions and Transport, Department of Gene Expression, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, Uniwersytetu Poznanskiego 6, 61-614 Poznan, Poland; (B.S.); (C.E.S.-B.)
- International Institute of Molecular and Cell Biology in Warsaw, Ks Trojdena 4, 02-109 Warsaw, Poland
| | - Jan Brezovsky
- Laboratory of Biomolecular Interactions and Transport, Department of Gene Expression, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, Uniwersytetu Poznanskiego 6, 61-614 Poznan, Poland; (B.S.); (C.E.S.-B.)
- International Institute of Molecular and Cell Biology in Warsaw, Ks Trojdena 4, 02-109 Warsaw, Poland
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196
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Goel H, Yu W, Ustach VD, Aytenfisu AH, Sun D, MacKerell AD. Impact of electronic polarizability on protein-functional group interactions. Phys Chem Chem Phys 2020; 22:6848-6860. [PMID: 32195493 PMCID: PMC7194236 DOI: 10.1039/d0cp00088d] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Interactions of proteins with functional groups are key to their biological functions, making it essential that they be accurately modeled. To investigate the impact of the inclusion of explicit treatment of electronic polarizability in force fields on protein-functional group interactions, the additive CHARMM and Drude polarizable force field are compared in the context of the Site-Identification by Ligand Competitive Saturation (SILCS) simulation methodology from which functional group interaction patterns with five proteins for which experimental binding affinities of multiple ligands are available, were obtained. The explicit treatment of polarizability produces significant differences in the functional group interactions in the ligand binding sites including overall enhanced binding of functional groups to the proteins. This is associated with variations of the dipole moments of solutes representative of functional groups in the binding sites relative to aqueous solution with higher dipole moments systematically occurring in the latter, though exceptions occur with positively charged methylammonium. Such variation indicates the complex, heterogeneous nature of the electronic environments of ligand binding sites and emphasizes the inherent limitation of fixed charged, additive force fields for modeling ligand-protein interactions. These effects yield more defined orientation of the functional groups in the binding pockets and a small, but systematic improvement in the ability of the SILCS method to predict the binding orientation and relative affinities of ligands to their target proteins. Overall, these results indicate that the physical model associated with the explicit treatment of polarizability along with the presence of lone pairs in a force field leads to changes in the nature of the interactions of functional groups with proteins versus that occurring with additive force fields, suggesting the utility of polarizable force fields in obtaining a more realistic understanding of protein-ligand interactions.
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Affiliation(s)
- Himanshu Goel
- Computer Aided Drug Design Center, Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, 20, Penn St., Baltimore, Maryland 21201, USA.
| | - Wenbo Yu
- Computer Aided Drug Design Center, Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, 20, Penn St., Baltimore, Maryland 21201, USA.
| | - Vincent D Ustach
- Computer Aided Drug Design Center, Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, 20, Penn St., Baltimore, Maryland 21201, USA.
| | - Asaminew H Aytenfisu
- Computer Aided Drug Design Center, Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, 20, Penn St., Baltimore, Maryland 21201, USA.
| | - Delin Sun
- Computer Aided Drug Design Center, Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, 20, Penn St., Baltimore, Maryland 21201, USA.
| | - Alexander D MacKerell
- Computer Aided Drug Design Center, Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, 20, Penn St., Baltimore, Maryland 21201, USA.
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197
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Zhao CL, Zhao DX, Jiang QY, Zhang HX, Li S, Yang ZZ. Polarizable TIP7P Water Model with Perturbation Charges Evaluated from ABEEM. J Phys Chem B 2020; 124:2450-2464. [PMID: 32141292 DOI: 10.1021/acs.jpcb.9b11775] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
A polarizable version of the rigid seven-site (TIP7P) water model with the atom-bond electronegativity equalization method (ABEEM) is proposed. The model uses direct polarization, where an isolated water monomer in the equilibrium geometry is assumed as a reference state and the polarization of the monomer arises from interacting with other molecules as a perturbation of the reference state. The charge on each site of the monomer splits into reference charge and perturbation charge. The perturbation charge arises only because of other reference charges. The interaction of the perturbation charge with other perturbation charges is replaced using polarization scaling to enhance the interaction of perturbation charge with the reference charges of the sites from other molecules. The perturbation charges are updated by evaluating explicit expressions once. This direct polarization is time-reversible because the charge update is independent of the charges in previous simulation steps. A Slater-type damping function moderates the short-range electrostatics to treat charge diffusion. The Ewald method corrects the long-range electrostatics both in the nuclei movement and in electronegativity equalization to diminish the size effect. The water model is parameterized by fitting the ab initio results of water clusters and the experimental results of water monomers and thermodynamic properties for liquid water. Owing to polarizability, the model performs better than the TIP7P model in terms of vaporization enthalpy, isothermal compressibility, and shear viscosity of the liquid phase. It performs better at the melting point of ice but slightly worse under critical conditions than the TIP7P model. Direct polarization has a low time complexity of O(N) and is a good choice for ABEEM to improve its computational efficiency.
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Affiliation(s)
- Chong-Li Zhao
- School of Chemistry and Chemical Engineering, Liaoning Normal University, Dalian 116029, People's Republic of China
| | - Dong-Xia Zhao
- School of Chemistry and Chemical Engineering, Liaoning Normal University, Dalian 116029, People's Republic of China
| | - Qian-Ying Jiang
- School of Chemistry and Chemical Engineering, Liaoning Normal University, Dalian 116029, People's Republic of China
| | - Hai-Xia Zhang
- School of Chemistry and Chemical Engineering, Liaoning Normal University, Dalian 116029, People's Republic of China
| | - Shenmin Li
- College of Environment and Chemical Engineering, Dalian University, Dalian 116622, People's Republic of China
| | - Zhong-Zhi Yang
- School of Chemistry and Chemical Engineering, Liaoning Normal University, Dalian 116029, People's Republic of China
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Coban MA, Fraga S, Caulfield TR. Structural And Computational Perspectives of Selectively Targeting Mutant Proteins. Curr Drug Discov Technol 2020; 18:365-378. [PMID: 32160847 DOI: 10.2174/1570163817666200311114819] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2019] [Revised: 01/24/2020] [Accepted: 01/28/2020] [Indexed: 11/22/2022]
Abstract
Diseases are often caused by mutant proteins. Many drugs have limited effectiveness and/or toxic side effects because of a failure to selectively target the disease-causing mutant variant, rather than the functional wild type protein. Otherwise, the drugs may even target different proteins with similar structural features. Designing drugs that successfully target mutant proteins selectively represents a major challenge. Decades of cancer research have led to an abundance of potential therapeutic targets, often touted to be "master regulators". For many of these proteins, there are no FDA-approved drugs available; for others, off-target effects result in dose-limiting toxicity. Cancer-related proteins are an excellent medium to carry the story of mutant-specific targeting, as the disease is both initiated and sustained by mutant proteins; furthermore, current chemotherapies generally fail at adequate selective distinction. This review discusses some of the challenges associated with selective targeting from a structural biology perspective, as well as some of the developments in algorithm approach and computational workflow that can be applied to address those issues. One of the most widely researched proteins in cancer biology is p53, a tumor suppressor. Here, p53 is discussed as a specific example of a challenging target, with contemporary drugs and methodologies used as examples of burgeoning successes. The oncogene KRAS, which has been described as "undruggable", is another extensively investigated protein in cancer biology. This review also examines KRAS to exemplify progress made towards selective targeting of diseasecausing mutant proteins. Finally, possible future directions relevant to the topic are discussed.
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Affiliation(s)
- Mathew A Coban
- Department of Cancer Biology, Mayo Clinic, Jacksonville, FL, 32224, United States
| | - Sarah Fraga
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, 32224, United States
| | - Thomas R Caulfield
- Department of Cancer Biology, Mayo Clinic, Jacksonville, FL, 32224, United States
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199
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Banavali NK. The Mechanism of Cholesterol Modification of Hedgehog Ligand. J Comput Chem 2020; 41:520-527. [PMID: 31823413 DOI: 10.1002/jcc.26097] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2019] [Revised: 09/06/2019] [Accepted: 10/14/2019] [Indexed: 12/21/2022]
Abstract
Hedgehog (Hh) proteins are important components of signal transduction pathways involved in animal development, and their defects are implicated in carcinogenesis. Their N-terminal domain (HhN) acts as a signaling ligand, and their C-terminal domain (HhC) performs an autocatalytic function of cleaving itself away, while adding a cholesterol moiety to HhN. HhC has two sub-domains: a hedgehog/intein (hint) domain that primarily performs the autocatalytic activity, and a sterol-recognition region (SRR) that binds to cholesterol and properly positions it with respect to HhN. The three-dimensional details of this autocatalytic mechanism remain unknown, as does the structure of the precursor Hh protein. In this study, a complete cholesterol-bound precursor form of the drosophila Hh precursor is modeled using known crystal structures of HhN and the hint domain, and a hypothesized similarity of SRR to an unrelated but similar-sized cholesterol binding protein. The restrained geometries and topology switching (RGATS) strategy is then used to predict atomic-detail pathways for the full autocatalytic reaction starting from the precursor and ending in a cholesterol-linked HhN domain and a cleaved HhC domain. The RGATS explicit solvent simulations indicate the roles of individual HhC residues in facilitating the reaction, which can be confirmed through mutational experiments. These simulations also provide plausible structural models for the N/S acyl transfer intermediate and the product states of this reaction. This study thus provides a good framework for future computational and experimental studies to develop a full structural and dynamic understanding of Hh autoprocessing. © 2019 Wiley Periodicals, Inc.
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Affiliation(s)
- Nilesh K Banavali
- Laboratory of Cellular and Molecular Basis of Diseases, Division of Translational Medicine, Wadsworth Center, New York State Department of Health, Albany, New York, USA
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Shiref H, Bergman S, Clivio S, Sahai MA. The fine art of preparing membrane transport proteins for biomolecular simulations: Concepts and practical considerations. Methods 2020; 185:3-14. [PMID: 32081744 PMCID: PMC10062712 DOI: 10.1016/j.ymeth.2020.02.009] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2019] [Revised: 02/14/2020] [Accepted: 02/14/2020] [Indexed: 10/25/2022] Open
Abstract
Molecular dynamics (MD) simulations have developed into an invaluable tool in bimolecular research, due to the capability of the method in capturing molecular events and structural transitions that describe the function as well as the physiochemical properties of biomolecular systems. Due to the progressive development of more efficient algorithms, expansion of the available computational resources, as well as the emergence of more advanced methodologies, the scope of computational studies has increased vastly over time. We now have access to a multitude of online databases, software packages, larger molecular systems and novel ligands due to the phenomenon of emerging novel psychoactive substances (NPS). With so many advances in the field, it is understandable that novices will no doubt find it challenging setting up a protein-ligand system even before they run their first MD simulation. These initial steps, such as homology modelling, ligand docking, parameterization, protein preparation and membrane setup have become a fundamental part of the drug discovery pipeline, and many areas of biomolecular sciences benefit from the applications provided by these technologies. However, there still remains no standard on their usage. Therefore, our aim within this review is to provide a clear overview of a variety of concepts and methodologies to consider, providing a workflow for a case study of a membrane transport protein, the full-length human dopamine transporter (hDAT) in complex with different stimulants, where MD simulations have recently been applied successfully.
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Affiliation(s)
- Hana Shiref
- Department of Life Sciences, University of Roehampton, London SW15 4JD, UK
| | - Shana Bergman
- Department of Physiology and Biophysics, Weill Cornell Medical College of Cornell University (WCMC), New York, NY 10065, USA
| | | | - Michelle A Sahai
- Department of Life Sciences, University of Roehampton, London SW15 4JD, UK.
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