Literature DB >> 31939671

PMFF: Development of a Physics-Based Molecular Force Field for Protein Simulation and Ligand Docking.

Sung Bo Hwang1, Chang Joon Lee2, Sehan Lee3, Songling Ma4, Young-Mook Kang5, Kwang Hwi Cho6, Su-Yeon Kim7, Oh Young Kwon8, Chang No Yoon9, Young Kee Kang10, Jeong Hyeok Yoon11, Ky-Youb Nam11, Seong-Gon Kim12, Youngyong In13, Han Ha Chai14, William E Acree15, J Andrew Grant16, Ken D Gibson16, Mu Shik Jhon16, Harold A Scheraga16, Kyoung Tai No1,17.   

Abstract

The physics-based molecular force field (PMFF) was developed by integrating a set of potential energy functions in which each term in an intermolecular potential energy function is derived based on experimental values, such as the dipole moments, lattice energy, proton transfer energy, and X-ray crystal structures. The term "physics-based" is used to emphasize the idea that the experimental observables that are considered to be the most relevant to each term are used for the parameterization rather than parameterizing all observables together against the target value. PMFF uses MM3 intramolecular potential energy terms to describe intramolecular interactions and includes an implicit solvation model specifically developed for the PMFF. We evaluated the PMFF in three ways. We concluded that the PMFF provides reliable information based on the structure in a biological system and interprets the biological phenomena accurately by providing more accurate evidence of the biological phenomena.

Entities:  

Year:  2020        PMID: 31939671      PMCID: PMC7217328          DOI: 10.1021/acs.jpcb.9b10339

Source DB:  PubMed          Journal:  J Phys Chem B        ISSN: 1520-5207            Impact factor:   2.991


  24 in total

1.  Development and testing of a general amber force field.

Authors:  Junmei Wang; Romain M Wolf; James W Caldwell; Peter A Kollman; David A Case
Journal:  J Comput Chem       Date:  2004-07-15       Impact factor: 3.376

2.  CHARMM fluctuating charge force field for proteins: II protein/solvent properties from molecular dynamics simulations using a nonadditive electrostatic model.

Authors:  Sandeep Patel; Alexander D Mackerell; Charles L Brooks
Journal:  J Comput Chem       Date:  2004-09       Impact factor: 3.376

3.  OPLS3: A Force Field Providing Broad Coverage of Drug-like Small Molecules and Proteins.

Authors:  Edward Harder; Wolfgang Damm; Jon Maple; Chuanjie Wu; Mark Reboul; Jin Yu Xiang; Lingle Wang; Dmitry Lupyan; Markus K Dahlgren; Jennifer L Knight; Joseph W Kaus; David S Cerutti; Goran Krilov; William L Jorgensen; Robert Abel; Richard A Friesner
Journal:  J Chem Theory Comput       Date:  2015-12-01       Impact factor: 6.006

4.  Derivation of force fields for molecular mechanics and dynamics from ab initio energy surfaces.

Authors:  J R Maple; U Dinur; A T Hagler
Journal:  Proc Natl Acad Sci U S A       Date:  1988-08       Impact factor: 11.205

5.  A universal approach to solvation modeling.

Authors:  Christopher J Cramer; Donald G Truhlar
Journal:  Acc Chem Res       Date:  2008-06       Impact factor: 22.384

6.  A generalized G-SFED continuum solvation free energy calculation model.

Authors:  Sehan Lee; Kwang-Hwi Cho; Young-Mook Kang; Harold A Scheraga; Kyoung Tai No
Journal:  Proc Natl Acad Sci U S A       Date:  2013-02-01       Impact factor: 11.205

7.  Energy functions for peptides and proteins. I. Derivation of a consistent force field including the hydrogen bond from amide crystals.

Authors:  A T Hagler; E Huler; S Lifson
Journal:  J Am Chem Soc       Date:  1974-08-21       Impact factor: 15.419

8.  Development of the CHARMM Force Field for Lipids.

Authors:  R W Pastor; A D Mackerell
Journal:  J Phys Chem Lett       Date:  2011       Impact factor: 6.475

9.  The Chemistry Development Kit (CDK): an open-source Java library for Chemo- and Bioinformatics.

Authors:  Christoph Steinbeck; Yongquan Han; Stefan Kuhn; Oliver Horlacher; Edgar Luttmann; Egon Willighagen
Journal:  J Chem Inf Comput Sci       Date:  2003 Mar-Apr

10.  PubChem Substance and Compound databases.

Authors:  Sunghwan Kim; Paul A Thiessen; Evan E Bolton; Jie Chen; Gang Fu; Asta Gindulyte; Lianyi Han; Jane He; Siqian He; Benjamin A Shoemaker; Jiyao Wang; Bo Yu; Jian Zhang; Stephen H Bryant
Journal:  Nucleic Acids Res       Date:  2015-09-22       Impact factor: 16.971

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  3 in total

1.  Machine learning assessment of the binding region as a tool for more efficient computational receptor-ligand docking.

Authors:  Matjaž Simončič; Miha Lukšič; Maksym Druchok
Journal:  J Mol Liq       Date:  2022-02-18       Impact factor: 6.165

2.  Identification of Novel Natural Product Inhibitors against Matrix Metalloproteinase 9 Using Quantum Mechanical Fragment Molecular Orbital-Based Virtual Screening Methods.

Authors:  Hocheol Lim; Hansol Hong; Seonik Hwang; Song Ja Kim; Sung Yum Seo; Kyoung Tai No
Journal:  Int J Mol Sci       Date:  2022-04-18       Impact factor: 6.208

3.  Identification of novel natural drug candidates against BRAF mutated carcinoma; An integrative in-silico structure-based pharmacophore modeling and virtual screening process.

Authors:  F A Dain Md Opo; Ahad Amer Alsaiari; Mohammad Habibur Rahman Molla; Md Afsar Ahmed Sumon; Khaled A Yaghmour; Foysal Ahammad; Farhan Mohammad; Jesus Simal-Gandara
Journal:  Front Chem       Date:  2022-10-04       Impact factor: 5.545

  3 in total

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