Literature DB >> 31914313

Development of a Force Field for the Simulation of Single-Chain Proteins and Protein-Protein Complexes.

Stefano Piana1, Paul Robustelli1, Dazhi Tan1, Songela Chen1, David E Shaw1,2.   

Abstract

The accuracy of atomistic physics-based force fields for the simulation of biological macromolecules has typically been benchmarked experimentally using biophysical data from simple, often single-chain systems. In the case of proteins, the careful refinement of force field parameters associated with torsion-angle potentials and the use of improved water models have enabled a great deal of progress toward the highly accurate simulation of such monomeric systems in both folded and, more recently, disordered states. In living organisms, however, proteins constantly interact with other macromolecules, such as proteins and nucleic acids, and these interactions are often essential for proper biological function. Here, we show that state-of-the-art force fields tuned to provide an accurate description of both ordered and disordered proteins can be limited in their ability to accurately describe protein-protein complexes. This observation prompted us to perform an extensive reparameterization of one variant of the Amber protein force field. Our objective involved refitting not only the parameters associated with torsion-angle potentials but also the parameters used to model nonbonded interactions, the specification of which is expected to be central to the accurate description of multicomponent systems. The resulting force field, which we call DES-Amber, allows for more accurate simulations of protein-protein complexes, while still providing a state-of-the-art description of both ordered and disordered single-chain proteins. Despite the improvements, calculated protein-protein association free energies still appear to deviate substantially from experiment, a result suggesting that more fundamental changes to the force field, such as the explicit treatment of polarization effects, may simultaneously further improve the modeling of single-chain proteins and protein-protein complexes.

Entities:  

Year:  2020        PMID: 31914313     DOI: 10.1021/acs.jctc.9b00251

Source DB:  PubMed          Journal:  J Chem Theory Comput        ISSN: 1549-9618            Impact factor:   6.006


  18 in total

Review 1.  Markov State Models to Elucidate Ligand Binding Mechanism.

Authors:  Yunhui Ge; Vincent A Voelz
Journal:  Methods Mol Biol       Date:  2021

2.  Alchemical Binding Free Energy Calculations in AMBER20: Advances and Best Practices for Drug Discovery.

Authors:  Tai-Sung Lee; Bryce K Allen; Timothy J Giese; Zhenyu Guo; Pengfei Li; Charles Lin; T Dwight McGee; David A Pearlman; Brian K Radak; Yujun Tao; Hsu-Chun Tsai; Huafeng Xu; Woody Sherman; Darrin M York
Journal:  J Chem Inf Model       Date:  2020-09-16       Impact factor: 4.956

3.  Refining All-Atom Protein Force Fields for Polar-Rich, Prion-like, Low-Complexity Intrinsically Disordered Proteins.

Authors:  Wai Shing Tang; Nicolas L Fawzi; Jeetain Mittal
Journal:  J Phys Chem B       Date:  2020-10-20       Impact factor: 2.991

4.  Transient exposure of a buried phosphorylation site in an autoinhibited protein.

Authors:  Simone Orioli; Carl G Henning Hansen; Kresten Lindorff-Larsen
Journal:  Biophys J       Date:  2021-12-03       Impact factor: 4.033

5.  Integration of Experimental Data and Use of Automated Fitting Methods in Developing Protein Force Fields.

Authors:  Marcelo D Polêto; Justin A Lemkul
Journal:  Commun Chem       Date:  2022-03-18

6.  'RNA modulation of transport properties and stability in phase-separated condensates.

Authors:  Andrés R Tejedor; Adiran Garaizar; Jorge Ramírez; Jorge R Espinosa
Journal:  Biophys J       Date:  2021-11-09       Impact factor: 4.033

7.  Molecular Dynamics Simulations of Protein RNA Complexes by Using an Advanced Electrostatic Model.

Authors:  Zhifeng Jing; Pengyu Ren
Journal:  J Phys Chem B       Date:  2022-09-15       Impact factor: 3.466

8.  Development of Force Field Parameters for the Simulation of Single- and Double-Stranded DNA Molecules and DNA-Protein Complexes.

Authors:  Maxwell R Tucker; Stefano Piana; Dazhi Tan; Michael V LeVine; David E Shaw
Journal:  J Phys Chem B       Date:  2022-06-12       Impact factor: 3.466

9.  Ensemble cryo-EM reveals conformational states of the nsp13 helicase in the SARS-CoV-2 helicase replication-transcription complex.

Authors:  James Chen; Qi Wang; Brandon Malone; Eliza Llewellyn; Yakov Pechersky; Kashyap Maruthi; Ed T Eng; Jason K Perry; Elizabeth A Campbell; David E Shaw; Seth A Darst
Journal:  Nat Struct Mol Biol       Date:  2022-03-08       Impact factor: 18.361

10.  High-resolution mining of the SARS-CoV-2 main protease conformational space: supercomputer-driven unsupervised adaptive sampling.

Authors:  Théo Jaffrelot Inizan; Frédéric Célerse; Olivier Adjoua; Dina El Ahdab; Luc-Henri Jolly; Chengwen Liu; Pengyu Ren; Matthieu Montes; Nathalie Lagarde; Louis Lagardère; Pierre Monmarché; Jean-Philip Piquemal
Journal:  Chem Sci       Date:  2021-02-02       Impact factor: 9.825

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