1
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Tian H, Jiang X, Xiao S, La Force H, Larson EC, Tao P. LAST: Latent Space-Assisted Adaptive Sampling for Protein Trajectories. J Chem Inf Model 2023; 63:67-75. [PMID: 36472885 PMCID: PMC9904845 DOI: 10.1021/acs.jcim.2c01213] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Molecular dynamics (MD) simulation is widely used to study protein conformations and dynamics. However, conventional simulation suffers from being trapped in some local energy minima that are hard to escape. Thus, most of the computational time is spent sampling in the already visited regions. This leads to an inefficient sampling process and further hinders the exploration of protein movements in affordable simulation time. The advancement of deep learning provides new opportunities for protein sampling. Variational autoencoders are a class of deep learning models to learn a low-dimensional representation (referred to as the latent space) that can capture the key features of the input data. Based on this characteristic, we proposed a new adaptive sampling method, latent space-assisted adaptive sampling for protein trajectories (LAST), to accelerate the exploration of protein conformational space. This method comprises cycles of (i) variational autoencoder training, (ii) seed structure selection on the latent space, and (iii) conformational sampling through additional MD simulations. The proposed approach is validated through the sampling of four structures of two protein systems: two metastable states of Escherichia coli adenosine kinase (ADK) and two native states of Vivid (VVD). In all four conformations, seed structures were shown to lie on the boundary of conformation distributions. Moreover, large conformational changes were observed in a shorter simulation time when compared with structural dissimilarity sampling (SDS) and conventional MD (cMD) simulations in both systems. In metastable ADK simulations, LAST explored two transition paths toward two stable states, while SDS explored only one and cMD neither. In VVD light state simulations, LAST was three times faster than cMD simulation with a similar conformational space. Overall, LAST is comparable to SDS and is a promising tool in adaptive sampling. The LAST method is publicly available at https://github.com/smu-tao-group/LAST to facilitate related research.
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Affiliation(s)
- Hao Tian
- Department of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, Texas75206, United States
| | - Xi Jiang
- Department of Statistical Science, Southern Methodist University, Dallas, Texas75206, United States
| | - Sian Xiao
- Department of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, Texas75206, United States
| | - Hunter La Force
- Department of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, Texas75206, United States
| | - Eric C Larson
- Department of Computer Science, Southern Methodist University, Dallas, Texas75206, United States
| | - Peng Tao
- Department of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, Texas75206, United States
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2
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Berselli A, Benfenati F, Maragliano L, Alberini G. Multiscale modelling of claudin-based assemblies: a magnifying glass for novel structures of biological interfaces. Comput Struct Biotechnol J 2022; 20:5984-6010. [DOI: 10.1016/j.csbj.2022.10.038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 10/24/2022] [Accepted: 10/24/2022] [Indexed: 11/03/2022] Open
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3
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Copeland M, Do HN, Votapka L, Joshi K, Wang J, Amaro RE, Miao Y. Gaussian Accelerated Molecular Dynamics in OpenMM. J Phys Chem B 2022; 126:5810-5820. [PMID: 35895977 PMCID: PMC9773147 DOI: 10.1021/acs.jpcb.2c03765] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Gaussian accelerated molecular dynamics (GaMD) is a computational technique that provides both unconstrained enhanced sampling and free energy calculations of biomolecules. Here, we present the implementation of GaMD in the OpenMM simulation package and validate it on model systems of alanine dipeptide and RNA folding. For alanine dipeptide, 30 ns GaMD production simulations reproduced free energy profiles of 1000 ns conventional molecular dynamics (cMD) simulations. In addition, GaMD simulations captured the folding pathways of three hyperstable RNA tetraloops (UUCG, GCAA, and CUUG) and binding of the rbt203 ligand to the HIV-1 Tar RNA, both of which involved critical electrostatic interactions such as hydrogen bonding and base stacking. Together with previous implementations, GaMD in OpenMM will allow for wider applications in simulations of proteins, RNA, and other biomolecules.
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Affiliation(s)
- Matthew Copeland
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS 66047
| | - Hung N. Do
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS 66047
| | - Lane Votapka
- Department of Chemistry and Biochemistry, University of California at San Diego, La Jolla, CA 92093
| | - Keya Joshi
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS 66047
| | - Jinan Wang
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS 66047
| | - Rommie E. Amaro
- Department of Chemistry and Biochemistry, University of California at San Diego, La Jolla, CA 92093
| | - Yinglong Miao
- Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS 66047,To whom correspondence should be addressed:
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4
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Markutsya S, Haley A, Gordon MS. Coarse-Grained Water Model Development for Accurate Dynamics and Structure Prediction. ACS OMEGA 2022; 7:25898-25904. [PMID: 35910114 PMCID: PMC9330847 DOI: 10.1021/acsomega.2c03857] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Accepted: 06/30/2022] [Indexed: 06/15/2023]
Abstract
Several coarse-graining (CG) methods have been combined to develop a CG model of water capable of the accurate prediction of structure and dynamics properties. The multiscale coarse-graining (MS-CG) method based on force matching and the PDF-based coarse-graining method were used for accurate dynamics prediction. The iterative Boltzmann inversion (IBI) method was added for accurate structure representation. The approach is applied to bulk water, and the results show close reproduction of the CG structure when compared with the reference atomistic data. The combination of MS-CG and IBI methods facilitates the development of CG force fields at different temperatures based on a single MS-CG coarse-graining procedure. The dynamic properties of the CG water model closely match those obtained from the reference atomistic system. The general application of this approach to any existing coarse-graining methods is discussed.
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Affiliation(s)
- Sergiy Markutsya
- Department
of Mechanical Engineering, University of
Kentucky, Paducah, Kentucky 42001, United States
| | - Austin Haley
- Department
of Mechanical Engineering, University of
Kentucky, Paducah, Kentucky 42001, United States
| | - Mark S. Gordon
- Department
of Chemistry and Ames Laboratory, Iowa State
University, Ames, Iowa 50011, United States
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5
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Kognole AA, Lee J, Park SJ, Jo S, Chatterjee P, Lemkul JA, Huang J, MacKerell AD, Im W. CHARMM-GUI Drude prepper for molecular dynamics simulation using the classical Drude polarizable force field. J Comput Chem 2021; 43:359-375. [PMID: 34874077 DOI: 10.1002/jcc.26795] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Revised: 11/10/2021] [Accepted: 11/25/2021] [Indexed: 12/18/2022]
Abstract
Explicit treatment of electronic polarizability in empirical force fields (FFs) represents an extension over a traditional additive or pairwise FF and provides a more realistic model of the variations in electronic structure in condensed phase, macromolecular simulations. To facilitate utilization of the polarizable FF based on the classical Drude oscillator model, Drude Prepper has been developed in CHARMM-GUI. Drude Prepper ingests additive CHARMM protein structures file (PSF) and pre-equilibrated coordinates in CHARMM, PDB, or NAMD format, from which the molecular components of the system are identified. These include all residues and patches connecting those residues along with water, ions, and other solute molecules. This information is then used to construct the Drude FF-based PSF using molecular generation capabilities in CHARMM, followed by minimization and equilibration. In addition, inputs are generated for molecular dynamics (MD) simulations using CHARMM, GROMACS, NAMD, and OpenMM. Validation of the Drude Prepper protocol and inputs is performed through conversion and MD simulations of various heterogeneous systems that include proteins, nucleic acids, lipids, polysaccharides, and atomic ions using the aforementioned simulation packages. Stable simulations are obtained in all studied systems, including 5 μs simulation of ubiquitin, verifying the integrity of the generated Drude PSFs. In addition, the ability of the Drude FF to model variations in electronic structure is shown through dipole moment analysis in selected systems. The capabilities and availability of Drude Prepper in CHARMM-GUI is anticipated to greatly facilitate the application of the Drude FF to a range of condensed phase, macromolecular systems.
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Affiliation(s)
- Abhishek A Kognole
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland, Baltimore, Maryland, USA
| | - Jumin Lee
- Department of Biological Sciences, Lehigh University, Bethlehem, Pennsylvania, USA
| | - Sang-Jun Park
- Department of Biological Sciences, Lehigh University, Bethlehem, Pennsylvania, USA
| | - Sunhwan Jo
- Leadership Computing Facility, Argonne National Laboratory, Argonne, Illinois, USA
| | - Payal Chatterjee
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland, Baltimore, Maryland, USA
| | - Justin A Lemkul
- Department of Biochemistry, Virginia Tech, Blacksburg, Virginia, USA
| | - Jing Huang
- Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Zhejiang, Hangzhou, China
| | - Alexander D MacKerell
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland, Baltimore, Maryland, USA
| | - Wonpil Im
- Department of Biological Sciences, Lehigh University, Bethlehem, Pennsylvania, USA
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6
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Ni D, Chai Z, Wang Y, Li M, Yu Z, Liu Y, Lu S, Zhang J. Along the allostery stream: Recent advances in computational methods for allosteric drug discovery. WIRES COMPUTATIONAL MOLECULAR SCIENCE 2021. [DOI: 10.1002/wcms.1585] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- Duan Ni
- College of Pharmacy Ningxia Medical University Yinchuan China
- The Charles Perkins Centre University of Sydney Sydney New South Wales Australia
| | - Zongtao Chai
- Department of Hepatic Surgery VI, Eastern Hepatobiliary Surgery Hospital Second Military Medical University Shanghai China
| | - Ying Wang
- State Key Laboratory of Oncogenes and Related Genes, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Mingyu Li
- State Key Laboratory of Oncogenes and Related Genes, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education Shanghai Jiao Tong University School of Medicine Shanghai China
| | | | - Yaqin Liu
- Medicinal Chemistry and Bioinformatics Center Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Shaoyong Lu
- College of Pharmacy Ningxia Medical University Yinchuan China
- State Key Laboratory of Oncogenes and Related Genes, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education Shanghai Jiao Tong University School of Medicine Shanghai China
- Medicinal Chemistry and Bioinformatics Center Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Jian Zhang
- College of Pharmacy Ningxia Medical University Yinchuan China
- State Key Laboratory of Oncogenes and Related Genes, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education Shanghai Jiao Tong University School of Medicine Shanghai China
- Medicinal Chemistry and Bioinformatics Center Shanghai Jiao Tong University School of Medicine Shanghai China
- School of Pharmaceutical Sciences Zhengzhou University Zhengzhou China
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7
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Giulini M, Rigoli M, Mattiotti G, Menichetti R, Tarenzi T, Fiorentini R, Potestio R. From System Modeling to System Analysis: The Impact of Resolution Level and Resolution Distribution in the Computer-Aided Investigation of Biomolecules. Front Mol Biosci 2021; 8:676976. [PMID: 34164432 PMCID: PMC8215203 DOI: 10.3389/fmolb.2021.676976] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2021] [Accepted: 05/06/2021] [Indexed: 12/18/2022] Open
Abstract
The ever increasing computer power, together with the improved accuracy of atomistic force fields, enables researchers to investigate biological systems at the molecular level with remarkable detail. However, the relevant length and time scales of many processes of interest are still hardly within reach even for state-of-the-art hardware, thus leaving important questions often unanswered. The computer-aided investigation of many biological physics problems thus largely benefits from the usage of coarse-grained models, that is, simplified representations of a molecule at a level of resolution that is lower than atomistic. A plethora of coarse-grained models have been developed, which differ most notably in their granularity; this latter aspect determines one of the crucial open issues in the field, i.e. the identification of an optimal degree of coarsening, which enables the greatest simplification at the expenses of the smallest information loss. In this review, we present the problem of coarse-grained modeling in biophysics from the viewpoint of system representation and information content. In particular, we discuss two distinct yet complementary aspects of protein modeling: on the one hand, the relationship between the resolution of a model and its capacity of accurately reproducing the properties of interest; on the other hand, the possibility of employing a lower resolution description of a detailed model to extract simple, useful, and intelligible information from the latter.
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Affiliation(s)
- Marco Giulini
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
| | - Marta Rigoli
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
| | - Giovanni Mattiotti
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
| | - Roberto Menichetti
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
| | - Thomas Tarenzi
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
| | - Raffaele Fiorentini
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
| | - Raffaello Potestio
- Physics Department, University of Trento, Trento, Italy.,INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, Trento, Italy
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8
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Oliva F, Flores-Canales JC, Pieraccini S, Morelli CF, Sironi M, Schiøtt B. Simulating Multiple Substrate-Binding Events by γ-Glutamyltransferase Using Accelerated Molecular Dynamics. J Phys Chem B 2020; 124:10104-10116. [PMID: 33112625 DOI: 10.1021/acs.jpcb.0c06907] [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
γ-Glutamyltransferase (GGT) is an enzyme that uses γ-glutamyl compounds as substrates and catalyzes their transfer to a water molecule or an acceptor substrate with varied physiological function in bacteria, plants, and animals. Crystal structures of GGT are known for different species and in different states of the chemical reaction; however, the structural dynamics of the substrate binding to the catalytic site of GGT are unknown. Here, we modeled Escherichia coli GGT's glutamine binding by using a swarm of accelerated molecular dynamics (aMD) simulations. Characterization of multiple binding events identified three structural binding motifs composed of polar residues in the binding pocket that govern glutamine binding into the active site. Simulated open and closed conformations of a lid-loop protecting the binding cavity suggest its role as a gating element by allowing or blocking substrates entry into the binding pocket. Partially open states of the lid-loop are accessible within thermal fluctuations, while the estimated free energy cost of a complete open state is 2.4 kcal/mol. Our results suggest that both specific electrostatic interactions and GGT conformational dynamics dictate the molecular recognition of substrate-GGT complexes.
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Affiliation(s)
- Francesco Oliva
- Dipartimento di Chimica, Università degli studi di Milano, Via Golgi 19, 20133 Milano, Italy
| | - Jose C Flores-Canales
- Department of Chemistry, Aarhus University, Langelandsgade 140, 8000 Aarhus, Denmark
| | - Stefano Pieraccini
- Dipartimento di Chimica, Università degli studi di Milano, Via Golgi 19, 20133 Milano, Italy
| | - Carlo F Morelli
- Dipartimento di Chimica, Università degli studi di Milano, Via Golgi 19, 20133 Milano, Italy
| | - Maurizio Sironi
- Dipartimento di Chimica, Università degli studi di Milano, Via Golgi 19, 20133 Milano, Italy
| | - Birgit Schiøtt
- Department of Chemistry, Aarhus University, Langelandsgade 140, 8000 Aarhus, Denmark
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9
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Lemkul JA. Pairwise-additive and polarizable atomistic force fields for molecular dynamics simulations of proteins. PROGRESS IN MOLECULAR BIOLOGY AND TRANSLATIONAL SCIENCE 2020; 170:1-71. [PMID: 32145943 DOI: 10.1016/bs.pmbts.2019.12.009] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Protein force fields have been undergoing continual development since the first complete parameter sets were introduced nearly four decades ago. The functional forms that underlie these models have many common elements for the treatment of bonded and nonbonded forces, which are reviewed here. The most widely used force fields to date use a fixed-charge convention in which electronic polarization effects are treated via a mean-field approximation during partial charge assignment. Despite success in modeling folded proteins over many years, the fixed-charge assumption has limitations that cannot necessarily be overcome within their potential energy equations. To overcome these limitations, several force fields have recently been derived that explicitly treat electronic polarization effects with straightforward extensions of the potential energy functions used by nonpolarizable force fields. Here, we review the history of the most popular nonpolarizable force fields (AMBER, CHARMM, OPLS, and GROMOS) as well as studies that have validated them and applied them to studies of protein folding and misfolding. Building upon these force fields are more recent polarizable interaction potentials, including fluctuating charge models, POSSIM, AMOEBA, and the classical Drude oscillator. These force fields differ in their implementations but all attempt to model electronic polarization in a computationally tractable manner. Despite their recent emergence in the field of protein folding, several studies have already applied these polarizable models to challenging problems in this domain, including the role of polarization in folding free energies and sequence-specific effects on the stability of α-helical structures.
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Affiliation(s)
- Justin A Lemkul
- Department of Biochemistry, Virginia Tech, Blacksburg, VA, United States.
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10
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Dubbeldam D, Walton KS, Vlugt TJH, Calero S. Design, Parameterization, and Implementation of Atomic Force Fields for Adsorption in Nanoporous Materials. ADVANCED THEORY AND SIMULATIONS 2019. [DOI: 10.1002/adts.201900135] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Affiliation(s)
- David Dubbeldam
- Van 't Hoff Institute for Molecular SciencesUniversity of AmsterdamScience Park 904 1098XH Amsterdam The Netherlands
| | - Krista S. Walton
- School of Chemical & Biomolecular EngineeringGeorgia Institute of Technology311 Ferst Dr. NW Atlanta GA 30332‐0100 USA
| | - Thijs J. H. Vlugt
- Delft University of TechnologyProcess & Energy DepartmentLeeghwaterstraat 39 2628CB Delft The Netherlands
| | - Sofia Calero
- Department of PhysicalChemical and Natural SystemsUniversity Pablo de OlavideSevilla 41013 Spain
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11
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Relative Contributions of Solubility and Mobility to the Stability of Amorphous Solid Dispersions of Poorly Soluble Drugs: A Molecular Dynamics Simulation Study. Pharmaceutics 2018; 10:pharmaceutics10030101. [PMID: 30037083 PMCID: PMC6161151 DOI: 10.3390/pharmaceutics10030101] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2018] [Revised: 07/13/2018] [Accepted: 07/18/2018] [Indexed: 11/29/2022] Open
Abstract
Amorphous solid dispersions are considered a promising formulation strategy for the oral delivery of poorly soluble drugs. The limiting factor for the applicability of this approach is the physical (in)stability of the amorphous phase in solid samples. Minimizing the risk of reduced shelf life for a new drug by establishing a suitable excipient/polymer-type from first principles would be desirable to accelerate formulation development. Here, we perform Molecular Dynamics simulations to determine properties of blends of eight different polymer–small molecule drug combinations for which stability data are available from a consistent set of literature data. We calculate thermodynamic factors (mixing energies) as well as mobilities (diffusion rates and roto-vibrational fluctuations). We find that either of the two factors, mobility and energetics, can determine the relative stability of the amorphous form for a given drug. Which factor is rate limiting depends on physico-chemical properties of the drug and the excipients/polymers. The methods outlined here can be readily employed for an in silico pre-screening of different excipients for a given drug to establish a qualitative ranking of the expected relative stabilities, thereby accelerating and streamlining formulation development.
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12
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Zhang YJ, Khorshidi A, Kastlunger G, Peterson AA. The potential for machine learning in hybrid QM/MM calculations. J Chem Phys 2018; 148:241740. [DOI: 10.1063/1.5029879] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Affiliation(s)
- Yin-Jia Zhang
- Department of Chemistry, Brown University, Providence, Rhode Island 02912, USA
| | - Alireza Khorshidi
- School of Engineering, Brown University, Providence, Rhode Island 02912, USA
| | - Georg Kastlunger
- School of Engineering, Brown University, Providence, Rhode Island 02912, USA
| | - Andrew A. Peterson
- School of Engineering, Brown University, Providence, Rhode Island 02912, USA
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13
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Affiliation(s)
- Pablo Ramos
- Department of Chemistry, Rutgers University, Newark, New Jersey 07102, USA
| | - Michele Pavanello
- Department of Chemistry, Rutgers University, Newark, New Jersey 07102, USA
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14
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Kilburg D, Gallicchio E. Assessment of a Single Decoupling Alchemical Approach for the Calculation of the Absolute Binding Free Energies of Protein-Peptide Complexes. Front Mol Biosci 2018; 5:22. [PMID: 29568737 PMCID: PMC5852065 DOI: 10.3389/fmolb.2018.00022] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2018] [Accepted: 02/21/2018] [Indexed: 01/24/2023] Open
Abstract
The computational modeling of peptide inhibitors to target protein-protein binding interfaces is growing in interest as these are often too large, too shallow, and too feature-less for conventional small molecule compounds. Here, we present a rare successful application of an alchemical binding free energy method for the calculation of converged absolute binding free energies of a series of protein-peptide complexes. Specifically, we report the binding free energies of a series of cyclic peptides derived from the LEDGF/p75 protein to the integrase receptor of the HIV1 virus. The simulations recapitulate the effect of mutations relative to the wild-type binding motif of LEDGF/p75, providing structural, energetic and dynamical interpretations of the observed trends. The equilibration and convergence of the calculations are carefully analyzed. Convergence is aided by the adoption of a single-decoupling alchemical approach with implicit solvation, which circumvents the convergence difficulties of conventional double-decoupling protocols. We hereby present the single-decoupling methodology and critically evaluate its advantages and limitations. We also discuss some of the challenges and potential pitfalls of binding free energy calculations for complex molecular systems which have generally limited their applicability to the quantitative study of protein-peptide binding equilibria.
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Affiliation(s)
- Denise Kilburg
- Department of Chemistry, Brooklyn College, Brooklyn, NY, United States.,Ph.D. Program in Chemistry, The Graduate Center, City University of New York, New York, NY, United States
| | - Emilio Gallicchio
- Department of Chemistry, Brooklyn College, Brooklyn, NY, United States.,Ph.D. Program in Chemistry, The Graduate Center, City University of New York, New York, NY, United States.,Ph.D. Program in Biochemistry, The Graduate Center, City University of New York, New York, NY, United States
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15
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Polok K. Simulations of the OKE Response in Simple Liquids Using a Polarizable and a Nonpolarizable Force Field. J Phys Chem B 2018; 122:1638-1654. [DOI: 10.1021/acs.jpcb.7b08724] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Kamil Polok
- Department of Chemistry, University of Warsaw, Zwirki i Wigury 101, 02-089 Warsaw, Poland
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16
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Zhekova HR, Ngo V, da Silva MC, Salahub D, Noskov S. Selective ion binding and transport by membrane proteins – A computational perspective. Coord Chem Rev 2017. [DOI: 10.1016/j.ccr.2017.03.019] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
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17
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Balmith M, Soliman MES. Non-active site mutations disturb the loop dynamics, dimerization, viral budding and egress of VP40 of the Ebola virus. MOLECULAR BIOSYSTEMS 2017; 13:585-597. [PMID: 28170013 DOI: 10.1039/c6mb00803h] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
The first account of the dynamic features of the loop region of VP40 of the Ebola virus (EboV) using accelerated molecular dynamics (aMD) simulations is reported herein. Due to its major role in the Ebola life cycle, VP40 is considered a promising therapeutic target. The available experimental data on the N-terminal domain (NTD) loop indicates that mutations K127A, T129A and N130A demonstrate an unrecognized role for NTD-plasma membrane (PM) interaction for efficient VP40-PM localization, oligomerization, matrix assembly and egress. Despite experimental results, the molecular description of VP40 and the information it can provide still remain vague. Therefore, to gain further molecular insight into the effect of mutations on the loop region of VP40 and its effects on the overall protein conformation and VP40 dimerization, aMD simulations and post-dynamic analyses were employed for wildtype (WT) and mutant systems. The results showed significant variations in the presence of mutations as per RMSF, RMSD, Rg, PCA and distance calculations in comparison to the WT. These results could provide researchers with insight with regards to the conformational aspects concerning VP40 and its close relation to the experimental data. We believe that the results presented in this study will ultimately provide a useful understanding of the structural landscape of the loop region of VP40, which would contribute towards the discovery of novel EboV inhibitors.
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Affiliation(s)
- Marissa Balmith
- Molecular Modeling and Drug Design Research Group, School of Health Sciences, University of KwaZulu-Natal, Westville Campus, Durban 4001, South Africa.
| | - Mahmoud E S Soliman
- Molecular Modeling and Drug Design Research Group, School of Health Sciences, University of KwaZulu-Natal, Westville Campus, Durban 4001, South Africa. and Department of Pharmaceutical Organic Chemistry, Faculty of Pharmacy, Zagazig University, Zagazig, Egypt and College of Pharmacy and Pharmaceutical Sciences, Florida Agricultural and Mechanical University, FAMU, Tallahassee, Florida 32307, USA
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18
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Oguntade S, Ramharack P, Soliman MES. Characterizing the ligand-binding landscape of Zika NS3 helicase-promising lead compounds as potential inhibitors. Future Virol 2017. [DOI: 10.2217/fvl-2017-0014] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Aim: This study aims to provide insight into the binding features of the ATPase and ssRNA sites of the NS3 helicase. Methods: Clinically approved Flavivirus inhibitors were docked to the corresponding active sites of the protein, and the three best compounds were validated with molecular dynamic simulations. Result: Binding of Ivermectin to ssRNA site and Lapachol and HMC-HO1α to the ATPase site allowed for conformational rigidity of the Zika NS3 helicase, thus stabilizing residue fluctuations and allowing for protein stability. Favorable free binding energies were also noted between compounds and the helicase, thus supporting the intermolecular forces at the helicase active site. Conclusion: The pharmacophoric characteristics found in Lapachol, HMC-HO1α and Ivermectin may be utilized in the design of a potent hybrid drug that is able to show efficient inhibition of a multitude of diseases including the detrimental co-infection of Zika virus, dengue and chikungunya.
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Affiliation(s)
- Sofiat Oguntade
- Discipline of Pharmaceutical Sciences, School of Health Sciences, University of KwaZulu-Natal, Westville Campus, Durban 4001, South Africa
| | - Pritika Ramharack
- Discipline of Pharmaceutical Sciences, School of Health Sciences, University of KwaZulu-Natal, Westville Campus, Durban 4001, South Africa
| | - Mahmoud ES Soliman
- Discipline of Pharmaceutical Sciences, School of Health Sciences, University of KwaZulu-Natal, Westville Campus, Durban 4001, South Africa
- Department of Pharmaceutical Organic Chemistry, Faculty of Pharmacy, Zagazig University, Zagazig, Egypt
- College of Pharmacy & Pharmaceutical Sciences, Florida Agricultural & Mechanical University, FAMU, FL 32307, USA
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19
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Chu H, Cao L, Peng X, Li G. Polarizable force field development for lipids and their efficient applications in membrane proteins. WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE 2017. [DOI: 10.1002/wcms.1312] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Affiliation(s)
- Huiying Chu
- Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics; Dalian Institute of Chemical Physics, Chinese Academy of Science; Dalian China
| | - Liaoran Cao
- Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics; Dalian Institute of Chemical Physics, Chinese Academy of Science; Dalian China
| | - Xiangda Peng
- Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics; Dalian Institute of Chemical Physics, Chinese Academy of Science; Dalian China
| | - Guohui Li
- Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics; Dalian Institute of Chemical Physics, Chinese Academy of Science; Dalian China
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20
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Small MC, Aytenfisu AH, Lin FY, He X, MacKerell AD. Drude polarizable force field for aliphatic ketones and aldehydes, and their associated acyclic carbohydrates. J Comput Aided Mol Des 2017; 31:349-363. [PMID: 28190218 PMCID: PMC5392138 DOI: 10.1007/s10822-017-0010-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2016] [Accepted: 01/17/2017] [Indexed: 10/20/2022]
Abstract
The majority of computer simulations exploring biomolecular function employ Class I additive force fields (FF), which do not treat polarization explicitly. Accordingly, much effort has been made into developing models that go beyond the additive approximation. Development and optimization of the Drude polarizable FF has yielded parameters for selected lipids, proteins, DNA and a limited number of carbohydrates. The work presented here details parametrization of aliphatic aldehydes and ketones (viz. acetaldehyde, propionaldehyde, butaryaldehyde, isobutaryaldehyde, acetone, and butanone) as well as their associated acyclic sugars (D-allose and D-psicose). LJ parameters are optimized targeting experimental heats of vaporization and molecular volumes, while the electrostatic parameters are optimized targeting QM water interactions, dipole moments, and molecular polarizabilities. Bonded parameters are targeted to both QM and crystal survey values, with the models for ketones and aldehydes shown to be in good agreement with QM and experimental target data. The reported heats of vaporization and molecular volumes represent a compromise between the studied model compounds. Simulations of the model compounds show an increase in the magnitude and the fluctuations of the dipole moments in moving from gas phase to condensed phases, which is a phenomenon that the additive FF is intrinsically unable to reproduce. The result is a polarizable model for aliphatic ketones and aldehydes including the acyclic sugars D-allose and D-psicose, thereby extending the available biomolecules in the Drude polarizable FF.
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Affiliation(s)
- Meagan C Small
- Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, 20 Penn St., Baltimore, MD, 21201, USA
| | - Asaminew H Aytenfisu
- Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, 20 Penn St., Baltimore, MD, 21201, USA
| | - Fang-Yu Lin
- Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, 20 Penn St., Baltimore, MD, 21201, USA
| | - Xibing He
- Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, 20 Penn St., Baltimore, MD, 21201, USA
| | - Alexander D MacKerell
- Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, 20 Penn St., Baltimore, MD, 21201, USA.
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21
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Nocito D, Beran GJO. Fast divide-and-conquer algorithm for evaluating polarization in classical force fields. J Chem Phys 2017; 146:114103. [DOI: 10.1063/1.4977981] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Dominique Nocito
- Department of Chemistry, University of California, Riverside, California 92521, USA
| | - Gregory J. O. Beran
- Department of Chemistry, University of California, Riverside, California 92521, USA
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22
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Zhang B, Kilburg D, Eastman P, Pande VS, Gallicchio E. Efficient gaussian density formulation of volume and surface areas of macromolecules on graphical processing units. J Comput Chem 2017; 38:740-752. [PMID: 28160511 DOI: 10.1002/jcc.24745] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2016] [Revised: 01/05/2017] [Accepted: 01/08/2017] [Indexed: 11/07/2022]
Abstract
We present an algorithm to efficiently compute accurate volumes and surface areas of macromolecules on graphical processing unit (GPU) devices using an analytic model which represents atomic volumes by continuous Gaussian densities. The volume of the molecule is expressed by means of the inclusion-exclusion formula, which is based on the summation of overlap integrals among multiple atomic densities. The surface area of the molecule is obtained by differentiation of the molecular volume with respect to atomic radii. The many-body nature of the model makes a port to GPU devices challenging. To our knowledge, this is the first reported full implementation of this model on GPU hardware. To accomplish this, we have used recursive strategies to construct the tree of overlaps and to accumulate volumes and their gradients on the tree data structures so as to minimize memory contention. The algorithm is used in the formulation of a surface area-based non-polar implicit solvent model implemented as an open source plug-in (named GaussVol) for the popular OpenMM library for molecular mechanics modeling. GaussVol is 50 to 100 times faster than our best optimized implementation for the CPUs, achieving speeds in excess of 100 ns/day with 1 fs time-step for protein-sized systems on commodity GPUs. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Baofeng Zhang
- Department of Chemistry, Brooklyn College of the City University of New York, 2900 Bedford Avenue, Brooklyn, New York, 11210
| | - Denise Kilburg
- Department of Chemistry, Brooklyn College of the City University of New York, 2900 Bedford Avenue, Brooklyn, New York, 11210.,Ph.D. Program in Chemistry, The Graduate Center of the City University of New York, New York, New York, 10016
| | - Peter Eastman
- Department of Bioengineering, Stanford University, Stanford, California, 94035
| | - Vijay S Pande
- Department of Chemistry, Stanford University, Stanford, California, 94035
| | - Emilio Gallicchio
- Department of Chemistry, Brooklyn College of the City University of New York, 2900 Bedford Avenue, Brooklyn, New York, 11210.,Ph.D. Program in Chemistry, The Graduate Center of the City University of New York, New York, New York, 10016
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23
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Balmith M, Soliman MES. VP40 of the Ebola Virus as a Target for EboV Therapy: Comprehensive Conformational and Inhibitor Binding Landscape from Accelerated Molecular Dynamics. Cell Biochem Biophys 2017; 75:65-78. [PMID: 28144904 DOI: 10.1007/s12013-017-0783-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2016] [Accepted: 01/17/2017] [Indexed: 10/20/2022]
Abstract
The first account of the dynamic features of the loop region of VP40 of the Ebola virus was studied using accelerated molecular dynamics simulations and reported herein. Among the proteins of the Ebola virus, the matrix protein (VP40) plays a significant role in the virus lifecycle thereby making it a promising therapeutic target. Of interest is the newly elucidated N-terminal domain loop region of VP40 comprising residues K127, T129, and N130 which when mutated to alanine have demonstrated an unrecognized role for N-terminal domain-plasma membrane interaction for efficient VP40-plasma membrane localization, oligomerization, matrix assembly, and egress. The molecular understanding of the conformational features of VP40 in complex with a known inhibitor still remains elusive. Using accelerated molecular dynamics approaches, we conducted a comparative study on VP40 apo and bound systems to understand the conformational features of VP40 at the molecular level and to determine the effect of inhibitor binding with the aid of a number of post-dynamic analytical tools. Significant features were seen in the presence of an inhibitor as per molecular mechanics/generalized born surface area binding free energy calculations. Results revealed that inhibitor binding to VP40 reduces the flexibility and mobility of the protein as supported by root mean square fluctuation and root mean square deviation calculations. The study revealed a characteristic "twisting" motion and coiling of the loop region of VP40 accompanied by conformational changes in the dimer interface upon inhibitor binding. We believe that results presented in this study will ultimately provide useful insight into the binding landscape of VP40 which could assist researchers in the discovery of potent Ebola virus inhibitors for anti-Ebola therapies.
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Affiliation(s)
- Marissa Balmith
- Molecular Modeling and Drug Design Research Group, School of Health Sciences, University of KwaZulu-Natal, Westville Campus, Durban, 4001, South Africa
| | - Mahmoud E S Soliman
- Molecular Modeling and Drug Design Research Group, School of Health Sciences, University of KwaZulu-Natal, Westville Campus, Durban, 4001, South Africa.
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24
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Leelananda SP, Lindert S. Computational methods in drug discovery. Beilstein J Org Chem 2016; 12:2694-2718. [PMID: 28144341 PMCID: PMC5238551 DOI: 10.3762/bjoc.12.267] [Citation(s) in RCA: 285] [Impact Index Per Article: 35.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2016] [Accepted: 11/22/2016] [Indexed: 12/11/2022] Open
Abstract
The process for drug discovery and development is challenging, time consuming and expensive. Computer-aided drug discovery (CADD) tools can act as a virtual shortcut, assisting in the expedition of this long process and potentially reducing the cost of research and development. Today CADD has become an effective and indispensable tool in therapeutic development. The human genome project has made available a substantial amount of sequence data that can be used in various drug discovery projects. Additionally, increasing knowledge of biological structures, as well as increasing computer power have made it possible to use computational methods effectively in various phases of the drug discovery and development pipeline. The importance of in silico tools is greater than ever before and has advanced pharmaceutical research. Here we present an overview of computational methods used in different facets of drug discovery and highlight some of the recent successes. In this review, both structure-based and ligand-based drug discovery methods are discussed. Advances in virtual high-throughput screening, protein structure prediction methods, protein-ligand docking, pharmacophore modeling and QSAR techniques are reviewed.
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Affiliation(s)
- Sumudu P Leelananda
- Department of Chemistry and Biochemistry, Ohio State University, Columbus, OH 43210, USA
| | - Steffen Lindert
- Department of Chemistry and Biochemistry, Ohio State University, Columbus, OH 43210, USA
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25
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Di Pasquale N, Bane M, Davie SJ, Popelier PLA. FEREBUS: Highly parallelized engine for kriging training. J Comput Chem 2016; 37:2606-16. [PMID: 27649926 DOI: 10.1002/jcc.24486] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2016] [Revised: 08/13/2016] [Accepted: 08/20/2016] [Indexed: 11/10/2022]
Abstract
FFLUX is a novel force field based on quantum topological atoms, combining multipolar electrostatics with IQA intraatomic and interatomic energy terms. The program FEREBUS calculates the hyperparameters of models produced by the machine learning method kriging. Calculation of kriging hyperparameters (θ and p) requires the optimization of the concentrated log-likelihood L̂(θ,p). FEREBUS uses Particle Swarm Optimization (PSO) and Differential Evolution (DE) algorithms to find the maximum of L̂(θ,p). PSO and DE are two heuristic algorithms that each use a set of particles or vectors to explore the space in which L̂(θ,p) is defined, searching for the maximum. The log-likelihood is a computationally expensive function, which needs to be calculated several times during each optimization iteration. The cost scales quickly with the problem dimension and speed becomes critical in model generation. We present the strategy used to parallelize FEREBUS, and the optimization of L̂(θ,p) through PSO and DE. The code is parallelized in two ways. MPI parallelization distributes the particles or vectors among the different processes, whereas the OpenMP implementation takes care of the calculation of L̂(θ,p), which involves the calculation and inversion of a particular matrix, whose size increases quickly with the dimension of the problem. The run time shows a speed-up of 61 times going from single core to 90 cores with a saving, in one case, of ∼98% of the single core time. In fact, the parallelization scheme presented reduces computational time from 2871 s for a single core calculation, to 41 s for 90 cores calculation. © 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.
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Affiliation(s)
- Nicodemo Di Pasquale
- Manchester Institute of Biotechnology (MIB), 131 Princess Street, Manchester M1 7DN, Great Britain and School of Chemistry, University of Manchester, Oxford Road, Manchester, M13 9PL, Great Britain
| | - Michael Bane
- Research IT, The University of Manchester and High End Compute, http://highendcompute.co.uk, Manchester, M13 0EL
| | - Stuart J Davie
- Manchester Institute of Biotechnology (MIB), 131 Princess Street, Manchester M1 7DN, Great Britain and School of Chemistry, University of Manchester, Oxford Road, Manchester, M13 9PL, Great Britain
| | - Paul L A Popelier
- Manchester Institute of Biotechnology (MIB), 131 Princess Street, Manchester M1 7DN, Great Britain and School of Chemistry, University of Manchester, Oxford Road, Manchester, M13 9PL, Great Britain.
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26
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Bradshaw RT, Essex JW. Evaluating Parametrization Protocols for Hydration Free Energy Calculations with the AMOEBA Polarizable Force Field. J Chem Theory Comput 2016; 12:3871-83. [PMID: 27341007 DOI: 10.1021/acs.jctc.6b00276] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Hydration free energy (HFE) calculations are often used to assess the performance of biomolecular force fields and the quality of assigned parameters. The AMOEBA polarizable force field moves beyond traditional pairwise additive models of electrostatics and may be expected to improve upon predictions of thermodynamic quantities such as HFEs over and above fixed-point-charge models. The recent SAMPL4 challenge evaluated the AMOEBA polarizable force field in this regard but showed substantially worse results than those using the fixed-point-charge GAFF model. Starting with a set of automatically generated AMOEBA parameters for the SAMPL4 data set, we evaluate the cumulative effects of a series of incremental improvements in parametrization protocol, including both solute and solvent model changes. Ultimately, the optimized AMOEBA parameters give a set of results that are not statistically significantly different from those of GAFF in terms of signed and unsigned error metrics. This allows us to propose a number of guidelines for new molecule parameter derivation with AMOEBA, which we expect to have benefits for a range of biomolecular simulation applications such as protein-ligand binding studies.
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Affiliation(s)
- Richard T Bradshaw
- School of Chemistry, University of Southampton, Highfield Campus , Southampton SO17 1BJ, U.K
| | - Jonathan W Essex
- School of Chemistry, University of Southampton, Highfield Campus , Southampton SO17 1BJ, U.K
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27
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Kastner KW, Izaguirre JA. Accelerated molecular dynamics simulations of the octopamine receptor using GPUs: discovery of an alternate agonist-binding position. Proteins 2016; 84:1480-9. [PMID: 27318014 DOI: 10.1002/prot.25091] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2016] [Revised: 05/23/2016] [Accepted: 06/13/2016] [Indexed: 11/08/2022]
Abstract
Octopamine receptors (OARs) perform key biological functions in invertebrates, making this class of G-protein coupled receptors (GPCRs) worth considering for insecticide development. However, no crystal structures and very little research exists for OARs. Furthermore, GPCRs are large proteins, are suspended in a lipid bilayer, and are activated on the millisecond timescale, all of which make conventional molecular dynamics (MD) simulations infeasible, even if run on large supercomputers. However, accelerated Molecular Dynamics (aMD) simulations can reduce this timescale to even hundreds of nanoseconds, while running the simulations on graphics processing units (GPUs) would enable even small clusters of GPUs to have processing power equivalent to hundreds of CPUs. Our results show that aMD simulations run on GPUs can successfully obtain the active and inactive state conformations of a GPCR on this reduced timescale. Furthermore, we discovered a potential alternate active-state agonist-binding position in the octopamine receptor which has yet to be observed and may be a novel GPCR agonist-binding position. These results demonstrate that a complex biological system with an activation process on the millisecond timescale can be successfully simulated on the nanosecond timescale using a simple computing system consisting of a small number of GPUs. Proteins 2016; 84:1480-1489. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Kevin W Kastner
- Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, Indiana
| | - Jesús A Izaguirre
- Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, Indiana.
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28
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Frank AT, Andricioaei I. Reaction Coordinate-Free Approach to Recovering Kinetics from Potential-Scaled Simulations: Application of Kramers’ Rate Theory. J Phys Chem B 2016; 120:8600-5. [DOI: 10.1021/acs.jpcb.6b02654] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Aaron T. Frank
- Department
of Chemistry, The University of California, Irvine, 4212 Natural
Sciences 1, Irvine, California 92697, United States
| | - Ioan Andricioaei
- Department
of Chemistry, The University of California, Irvine, 4212 Natural
Sciences 1, Irvine, California 92697, United States
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29
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Wagner JR, Lee CT, Durrant JD, Malmstrom RD, Feher VA, Amaro RE. Emerging Computational Methods for the Rational Discovery of Allosteric Drugs. Chem Rev 2016; 116:6370-90. [PMID: 27074285 PMCID: PMC4901368 DOI: 10.1021/acs.chemrev.5b00631] [Citation(s) in RCA: 148] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
![]()
Allosteric drug development holds
promise for delivering medicines
that are more selective and less toxic than those that target orthosteric
sites. To date, the discovery of allosteric binding sites and lead
compounds has been mostly serendipitous, achieved through high-throughput
screening. Over the past decade, structural data has become more readily
available for larger protein systems and more membrane protein classes
(e.g., GPCRs and ion channels), which are common allosteric drug targets.
In parallel, improved simulation methods now provide better atomistic
understanding of the protein dynamics and cooperative motions that
are critical to allosteric mechanisms. As a result of these advances,
the field of predictive allosteric drug development is now on the
cusp of a new era of rational structure-based computational methods.
Here, we review algorithms that predict allosteric sites based on
sequence data and molecular dynamics simulations, describe tools that
assess the druggability of these pockets, and discuss how Markov state
models and topology analyses provide insight into the relationship
between protein dynamics and allosteric drug binding. In each section,
we first provide an overview of the various method classes before
describing relevant algorithms and software packages.
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Affiliation(s)
- Jeffrey R Wagner
- Department of Chemistry & Biochemistry and ‡National Biomedical Computation Resource, University of California, San Diego , La Jolla, California 92093, United States
| | - Christopher T Lee
- Department of Chemistry & Biochemistry and ‡National Biomedical Computation Resource, University of California, San Diego , La Jolla, California 92093, United States
| | - Jacob D Durrant
- Department of Chemistry & Biochemistry and ‡National Biomedical Computation Resource, University of California, San Diego , La Jolla, California 92093, United States
| | - Robert D Malmstrom
- Department of Chemistry & Biochemistry and ‡National Biomedical Computation Resource, University of California, San Diego , La Jolla, California 92093, United States
| | - Victoria A Feher
- Department of Chemistry & Biochemistry and ‡National Biomedical Computation Resource, University of California, San Diego , La Jolla, California 92093, United States
| | - Rommie E Amaro
- Department of Chemistry & Biochemistry and ‡National Biomedical Computation Resource, University of California, San Diego , La Jolla, California 92093, United States
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30
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Guo W, Cheng L, Chu H, Cao L, Zhang D, Liu J, Xu P, Zheng X, Li G. Some polarisable force fields for molecular dynamics simulations of lipids, and bilayers. MOLECULAR SIMULATION 2016. [DOI: 10.1080/08927022.2016.1161190] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
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31
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Peng X, Zhang Y, Chu H, Li G. Free energy simulations with the AMOEBA polarizable force field and metadynamics on GPU platform. J Comput Chem 2015; 37:614-22. [PMID: 26493154 DOI: 10.1002/jcc.24227] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2015] [Revised: 09/14/2015] [Accepted: 09/24/2015] [Indexed: 01/08/2023]
Abstract
The free energy calculation library PLUMED has been incorporated into the OpenMM simulation toolkit, with the purpose to perform enhanced sampling MD simulations using the AMOEBA polarizable force field on GPU platform. Two examples, (I) the free energy profile of water pair separation (II) alanine dipeptide dihedral angle free energy surface in explicit solvent, are provided here to demonstrate the accuracy and efficiency of our implementation. The converged free energy profiles could be obtained within an affordable MD simulation time when the AMOEBA polarizable force field is employed. Moreover, the free energy surfaces estimated using the AMOEBA polarizable force field are in agreement with those calculated from experimental data and ab initio methods. Hence, the implementation in this work is reliable and would be utilized to study more complicated biological phenomena in both an accurate and efficient way. © 2015 Wiley Periodicals, Inc.
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Affiliation(s)
- Xiangda Peng
- Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Rd, Dalian, 116023, People's Republic of China
| | - Yuebin Zhang
- Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Rd, Dalian, 116023, People's Republic of China
| | - Huiying Chu
- Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Rd, Dalian, 116023, People's Republic of China
| | - Guohui Li
- Laboratory of Molecular Modeling and Design, State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Rd, Dalian, 116023, People's Republic of China
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32
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Walczewska-Szewc K, Deplazes E, Corry B. Comparing the Ability of Enhanced Sampling Molecular Dynamics Methods To Reproduce the Behavior of Fluorescent Labels on Proteins. J Chem Theory Comput 2015; 11:3455-65. [DOI: 10.1021/acs.jctc.5b00205] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Affiliation(s)
- Katarzyna Walczewska-Szewc
- In
Silico Numerical Laboratory and Institute
of Experimental Physics, University of Gdansk, 80-952 Gdańsk, Poland
- Research
School of Biology, Australian National University, Acton ACT 2601, Australia
| | - Evelyne Deplazes
- Institute for Molecular Bioscience and School of Chemistry & Molecular Biosciences, The University of Queensland, Brisbane QLD 4072, Australia
| | - Ben Corry
- Research
School of Biology, Australian National University, Acton ACT 2601, Australia
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33
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Korb O, Finn PW, Jones G. The cloud and other new computational methods to improve molecular modelling. Expert Opin Drug Discov 2014; 9:1121-31. [DOI: 10.1517/17460441.2014.941800] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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34
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Doshi U, Hamelberg D. Towards fast, rigorous and efficient conformational sampling of biomolecules: Advances in accelerated molecular dynamics. Biochim Biophys Acta Gen Subj 2014; 1850:878-888. [PMID: 25153688 DOI: 10.1016/j.bbagen.2014.08.003] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2014] [Revised: 08/12/2014] [Accepted: 08/13/2014] [Indexed: 02/06/2023]
Abstract
BACKGROUND Accelerated molecular dynamics (aMD) has been proven to be a powerful biasing method for enhanced sampling of biomolecular conformations on general-purpose computational platforms. Biologically important long timescale events that are beyond the reach of standard molecular dynamics can be accessed without losing the detailed atomistic description of the system in aMD. Over other biasing methods, aMD offers the advantages of tuning the level of acceleration to access the desired timescale without any advance knowledge of the reaction coordinate. SCOPE OF REVIEW Recent advances in the implementation of aMD and its applications to small peptides and biological macromolecules are reviewed here along with a brief account of all the aMD variants introduced in the last decade. MAJOR CONCLUSIONS In comparison to the original implementation of aMD, the recent variant in which all the rotatable dihedral angles are accelerated (RaMD) exhibits faster convergence rates and significant improvement in statistical accuracy of retrieved thermodynamic properties. RaMD in conjunction with accelerating diffusive degrees of freedom, i.e. dual boosting, has been rigorously tested for the most difficult conformational sampling problem, protein folding. It has been shown that RaMD with dual boosting is capable of efficiently sampling multiple folding and unfolding events in small fast folding proteins. GENERAL SIGNIFICANCE RaMD with the dual boost approach opens exciting possibilities for sampling multiple timescales in biomolecules. While equilibrium properties can be recovered satisfactorily from aMD-based methods, directly obtaining dynamics and kinetic rates for larger systems presents a future challenge. This article is part of a Special Issue entitled Recent developments of molecular dynamics.
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Affiliation(s)
- Urmi Doshi
- Department of Chemistry and the Center for Biotechnology and Drug Design, Georgia State University, Atlanta, GA 30302-3965, United States
| | - Donald Hamelberg
- Department of Chemistry and the Center for Biotechnology and Drug Design, Georgia State University, Atlanta, GA 30302-3965, United States.
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35
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Camilloni C, Vendruscolo M. Statistical mechanics of the denatured state of a protein using replica-averaged metadynamics. J Am Chem Soc 2014; 136:8982-91. [PMID: 24884637 DOI: 10.1021/ja5027584] [Citation(s) in RCA: 58] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
The characterization of denatured states of proteins is challenging because the lack of permanent structure in these states makes it difficult to apply to them standard methods of structural biology. In this work we use all-atom replica-averaged metadynamics (RAM) simulations with NMR chemical shift restraints to determine an ensemble of structures representing an acid-denatured state of the 86-residue protein ACBP. This approach has enabled us to reach convergence in the free energy landscape calculations, obtaining an ensemble of structures in relatively accurate agreement with independent experimental data used for validation. By observing at atomistic resolution the transient formation of native and non-native structures in this acid-denatured state of ACBP, we rationalize the effects of single-point mutations on the folding rate, stability, and transition-state structures of this protein, thus characterizing the role of the unfolded state in determining the folding process.
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Affiliation(s)
- Carlo Camilloni
- Department of Chemistry, University of Cambridge , Cambridge CB2 1EW, United Kingdom
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Götz AW, Bucher D, Lindert S, McCammon JA. Dipeptide Aggregation in Aqueous Solution from Fixed Point-Charge Force Fields. J Chem Theory Comput 2014; 10:1631-1637. [PMID: 24803868 PMCID: PMC3986234 DOI: 10.1021/ct401049q] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2013] [Indexed: 11/29/2022]
Abstract
The description of aggregation processes with molecular dynamics simulations is a playground for testing biomolecular force fields, including a new generation of force fields that explicitly describe electronic polarization. In this work, we study a system consisting of 50 glycyl-l-alanine (Gly-Ala) dipeptides in solution with 1001 water molecules. Neutron diffraction experiments have shown that at this concentration, Gly-Ala aggregates into large clusters. However, general-purpose force fields in combination with established water models can fail to correctly describe this aggregation process, highlighting important deficiencies in how solute-solute and solute-solvent interactions are parametrized in these force fields. We found that even for the fully polarizable AMOEBA force field, the degree of association is considerably underestimated. Instead, a fixed point-charge approach based on the newly developed IPolQ scheme [Cerutti et al. J. Phys. Chem.2013, 117, 2328] allows for the correct modeling of the dipeptide aggregation in aqueous solution. This result should stimulate interest in novel fitting schemes that aim to improve the description of the solvent polarization effect within both explicitly polarizable and fixed point-charge frameworks.
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Affiliation(s)
- Andreas W Götz
- San Diego Supercomputer Center, University of California San Diego , 9500 Gilman Drive, La Jolla, California 92093, United States ; Department of Chemistry and Biochemistry, University of California San Diego , 9500 Gilman Drive, La Jolla, California 92093, United States
| | - Denis Bucher
- Department of Chemistry and Biochemistry, University of California San Diego , 9500 Gilman Drive, La Jolla, California 92093, United States
| | - Steffen Lindert
- Department of Chemistry and Biochemistry, University of California San Diego , 9500 Gilman Drive, La Jolla, California 92093, United States
| | - J Andrew McCammon
- Department of Chemistry and Biochemistry, University of California San Diego , 9500 Gilman Drive, La Jolla, California 92093, United States ; Department of Pharmacology, University of California San Diego , 9500 Gilman Drive, La Jolla, California 92093, United States ; Howard Hughes Medical Institute, University of California San Diego , 9500 Gilman Drive, La Jolla, California 92093, United States
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