Literature DB >> 24459460

Force Field for Peptides and Proteins based on the Classical Drude Oscillator.

Pedro E M Lopes1, Jing Huang1, Jihyun Shim1, Yun Luo2, Hui Li3, Benoît Roux3, Alexander D Mackerell1.   

Abstract

Presented is a polarizable force field based on a classical Drude oscillator framework, currently implemented in the programs CHARMM and NAMD, for modeling and molecular dynamics (MD) simulation studies of peptides and proteins. Building upon parameters for model compounds representative of the functional groups in proteins, the development of the force field focused on the optimization of the parameters for the polypeptide backbone and the connectivity between the backbone and side chains. Optimization of the backbone electrostatic parameters targeted quantum mechanical conformational energies, interactions with water, molecular dipole moments and polarizabilities and experimental condensed phase data for short polypeptides such as (Ala)5. Additional optimization of the backbone φ, ψ conformational preferences included adjustments of the tabulated two-dimensional spline function through the CMAP term. Validation of the model included simulations of a collection of peptides and proteins. This 1st generation polarizable model is shown to maintain the folded state of the studied systems on the 100 ns timescale in explicit solvent MD simulations. The Drude model typically yields larger RMS differences as compared to the additive CHARMM36 force field (C36) and shows additional flexibility as compared to the additive model. Comparison with NMR chemical shift data shows a small degradation of the polarizable model with respect to the additive, though the level of agreement may be considered satisfactory, while for residues shown to have significantly underestimated S2 order parameters in the additive model, improvements are calculated with the polarizable model. Analysis of dipole moments associated with the peptide backbone and tryptophan side chains show the Drude model to have significantly larger values than those present in C36, with the dipole moments of the peptide backbone enhanced to a greater extent in sheets versus helices and the dipoles of individual moieties observed to undergo significant variations during the MD simulations. Although there are still some limitations, the presented model, termed Drude-2013, is anticipated to yield a molecular picture of peptide and protein structure and function that will be of increased physical validity and internal consistency in a computationally accessible fashion.

Entities:  

Year:  2013        PMID: 24459460      PMCID: PMC3896220          DOI: 10.1021/ct400781b

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


  98 in total

1.  Accurate protein crystallography at ultra-high resolution: valence electron distribution in crambin.

Authors:  C Jelsch; M M Teeter; V Lamzin; V Pichon-Pesme; R H Blessing; C Lecomte
Journal:  Proc Natl Acad Sci U S A       Date:  2000-03-28       Impact factor: 11.205

Review 2.  Force fields for protein simulations.

Authors:  Jay W Ponder; David A Case
Journal:  Adv Protein Chem       Date:  2003

3.  Enhanced hairpin stability through loop design: the case of the protein G B1 domain hairpin.

Authors:  R Matthew Fesinmeyer; F Michael Hudson; Niels H Andersen
Journal:  J Am Chem Soc       Date:  2004-06-16       Impact factor: 15.419

4.  Validation of the 53A6 GROMOS force field.

Authors:  Chris Oostenbrink; Thereza A Soares; Nico F A van der Vegt; Wilfred F van Gunsteren
Journal:  Eur Biophys J       Date:  2005-04-01       Impact factor: 1.733

5.  Structure and dynamics of the homologous series of alanine peptides: a joint molecular dynamics/NMR study.

Authors:  Jürgen Graf; Phuong H Nguyen; Gerhard Stock; Harald Schwalbe
Journal:  J Am Chem Soc       Date:  2007-02-07       Impact factor: 15.419

6.  A polarizable force field for computing the infrared spectra of the polypeptide backbone.

Authors:  Verena Schultheis; Rudolf Reichold; Bernhard Schropp; Paul Tavan
Journal:  J Phys Chem B       Date:  2008-09-09       Impact factor: 2.991

7.  Optimization of the additive CHARMM all-atom protein force field targeting improved sampling of the backbone φ, ψ and side-chain χ(1) and χ(2) dihedral angles.

Authors:  Robert B Best; Xiao Zhu; Jihyun Shim; Pedro E M Lopes; Jeetain Mittal; Michael Feig; Alexander D Mackerell
Journal:  J Chem Theory Comput       Date:  2012-07-18       Impact factor: 6.006

8.  The Polarizable Atomic Multipole-based AMOEBA Force Field for Proteins.

Authors:  Yue Shi; Zhen Xia; Jiajing Zhang; Robert Best; Chuanjie Wu; Jay W Ponder; Pengyu Ren
Journal:  J Chem Theory Comput       Date:  2013       Impact factor: 6.006

9.  (Ala)(4)-X-(Ala)4 as a model system for the optimization of the χ1 and χ2 amino acid side-chain dihedral empirical force field parameters.

Authors:  Jihyun Shim; Xiao Zhu; Robert B Best; Alexander D MacKerell
Journal:  J Comput Chem       Date:  2012-11-29       Impact factor: 3.376

10.  Improved side-chain torsion potentials for the Amber ff99SB protein force field.

Authors:  Kresten Lindorff-Larsen; Stefano Piana; Kim Palmo; Paul Maragakis; John L Klepeis; Ron O Dror; David E Shaw
Journal:  Proteins       Date:  2010-06
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  108 in total

1.  Polarizable force field for RNA based on the classical drude oscillator.

Authors:  Justin A Lemkul; Alexander D MacKerell
Journal:  J Comput Chem       Date:  2018-12-15       Impact factor: 3.376

2.  AMOEBA+ Classical Potential for Modeling Molecular Interactions.

Authors:  Chengwen Liu; Jean-Philip Piquemal; Pengyu Ren
Journal:  J Chem Theory Comput       Date:  2019-06-11       Impact factor: 6.006

Review 3.  Force field development and simulations of intrinsically disordered proteins.

Authors:  Jing Huang; Alexander D MacKerell
Journal:  Curr Opin Struct Biol       Date:  2017-11-05       Impact factor: 6.809

4.  Drude polarizable force field for aliphatic ketones and aldehydes, and their associated acyclic carbohydrates.

Authors:  Meagan C Small; Asaminew H Aytenfisu; Fang-Yu Lin; Xibing He; Alexander D MacKerell
Journal:  J Comput Aided Mol Des       Date:  2017-02-11       Impact factor: 3.686

Review 5.  Metal Ion Modeling Using Classical Mechanics.

Authors:  Pengfei Li; Kenneth M Merz
Journal:  Chem Rev       Date:  2017-01-03       Impact factor: 60.622

6.  Further Optimization and Validation of the Classical Drude Polarizable Protein Force Field.

Authors:  Fang-Yu Lin; Jing Huang; Poonam Pandey; Chetan Rupakheti; Jing Li; Benoı T Roux; Alexander D MacKerell
Journal:  J Chem Theory Comput       Date:  2020-04-27       Impact factor: 6.006

7.  Molecular dynamics simulations using the drude polarizable force field on GPUs with OpenMM: Implementation, validation, and benchmarks.

Authors:  Jing Huang; Justin A Lemkul; Peter K Eastman; Alexander D MacKerell
Journal:  J Comput Chem       Date:  2018-05-04       Impact factor: 3.376

8.  Balancing the Interactions of Mg2+ in Aqueous Solution and with Nucleic Acid Moieties For a Polarizable Force Field Based on the Classical Drude Oscillator Model.

Authors:  Justin A Lemkul; Alexander D MacKerell
Journal:  J Phys Chem B       Date:  2016-10-27       Impact factor: 2.991

9.  pKa Calculations with the Polarizable Drude Force Field and Poisson-Boltzmann Solvation Model.

Authors:  Alexey Aleksandrov; Benoît Roux; Alexander D MacKerell
Journal:  J Chem Theory Comput       Date:  2020-06-12       Impact factor: 6.006

10.  Empirical Optimization of Interactions between Proteins and Chemical Denaturants in Molecular Simulations.

Authors:  Wenwei Zheng; Alessandro Borgia; Madeleine B Borgia; Benjamin Schuler; Robert B Best
Journal:  J Chem Theory Comput       Date:  2015-10-13       Impact factor: 6.006

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