Literature DB >> 34942567

Recent progress in general force fields of small molecules.

Xibing He1, Brandon Walker2, Viet H Man1, Pengyu Ren3, Junmei Wang4.   

Abstract

Recent advances in computational hardware and free energy algorithms enable a broader application of molecular simulation of binding interactions between receptors and small-molecule ligands. The underlying molecular mechanics force fields (FFs) for small molecules have also achieved advancements in accuracy, user-friendliness, and speed during the past several years (2018-2020). Besides the expansion of chemical space coverage of ligand-like molecules among major popular classical additive FFs and polarizable FFs, new charge models have been proposed for better accuracy and transferability, new chemical perception of avoiding predefined atom types have been applied, and new automated parameterization toolkits, including machine learning approaches, have been developed for users' convenience.
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Year:  2021        PMID: 34942567      PMCID: PMC8860847          DOI: 10.1016/j.sbi.2021.11.011

Source DB:  PubMed          Journal:  Curr Opin Struct Biol        ISSN: 0959-440X            Impact factor:   6.809


  46 in total

1.  Toward Learned Chemical Perception of Force Field Typing Rules.

Authors:  Camila Zanette; Caitlin C Bannan; Christopher I Bayly; Josh Fass; Michael K Gilson; Michael R Shirts; John D Chodera; David L Mobley
Journal:  J Chem Theory Comput       Date:  2018-12-24       Impact factor: 6.006

2.  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

3.  DeepAtomicCharge: a new graph convolutional network-based architecture for accurate prediction of atomic charges.

Authors:  Jike Wang; Dongsheng Cao; Cunchen Tang; Lei Xu; Qiaojun He; Bo Yang; Xi Chen; Huiyong Sun; Tingjun Hou
Journal:  Brief Bioinform       Date:  2021-05-20       Impact factor: 11.622

Review 4.  Molecular Dynamics Simulation for All.

Authors:  Scott A Hollingsworth; Ron O Dror
Journal:  Neuron       Date:  2018-09-19       Impact factor: 17.173

5.  Elucidating Hyperconjugation from Electronegativity to Predict Drug Conformational Energy in a High Throughput Manner.

Authors:  Zhaomin Liu; Joshua Pottel; Moeed Shahamat; Anna Tomberg; Paul Labute; Nicolas Moitessier
Journal:  J Chem Inf Model       Date:  2016-04-12       Impact factor: 4.956

6.  ff19SB: Amino-Acid-Specific Protein Backbone Parameters Trained against Quantum Mechanics Energy Surfaces in Solution.

Authors:  Chuan Tian; Koushik Kasavajhala; Kellon A A Belfon; Lauren Raguette; He Huang; Angela N Migues; John Bickel; Yuzhang Wang; Jorge Pincay; Qin Wu; Carlos Simmerling
Journal:  J Chem Theory Comput       Date:  2019-12-03       Impact factor: 6.006

7.  Automation of AMOEBA polarizable force field parameterization for small molecules.

Authors:  Johnny C Wu; Gaurav Chattree; Pengyu Ren
Journal:  Theor Chem Acc       Date:  2012-02-26       Impact factor: 1.702

8.  Force Fields for Small Molecules.

Authors:  Fang-Yu Lin; Alexander D MacKerell
Journal:  Methods Mol Biol       Date:  2019

9.  FFParam: Standalone package for CHARMM additive and Drude polarizable force field parametrization of small molecules.

Authors:  Anmol Kumar; Ozge Yoluk; Alexander D MacKerell
Journal:  J Comput Chem       Date:  2019-12-30       Impact factor: 3.376

10.  All-atom empirical potential for molecular modeling and dynamics studies of proteins.

Authors:  A D MacKerell; D Bashford; M Bellott; R L Dunbrack; J D Evanseck; M J Field; S Fischer; J Gao; H Guo; S Ha; D Joseph-McCarthy; L Kuchnir; K Kuczera; F T Lau; C Mattos; S Michnick; T Ngo; D T Nguyen; B Prodhom; W E Reiher; B Roux; M Schlenkrich; J C Smith; R Stote; J Straub; M Watanabe; J Wiórkiewicz-Kuczera; D Yin; M Karplus
Journal:  J Phys Chem B       Date:  1998-04-30       Impact factor: 2.991

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