Evaluation of the Coupled Two-Dimensional Main Chain Torsional Potential in Modeling Intrinsically Disordered Proteins

Ya Gao, Chaomin Zhang, John Zhang, Ye Mei

Research output: Contribution to journalArticle

Abstract

Intrinsically disordered proteins (IDPs) carry out crucial biological functions in essential biological processes of life. Because of the highly dynamic and conformationally heterogeneous nature of the disordered states of IDPs, molecular dynamics simulations are becoming an indispensable tool for the investigation of the conformational ensembles and dynamic properties of IDPs. Nevertheless, there is still no consensus on the most reliable force field in molecular dynamics simulations for IDPs hitherto. In this work, the recently proposed AMBER99SB2D force field is evaluated in modeling some disordered polypeptides and proteins by checking its ability to reproduce experimental NMR data. The results highlight that when the ildn side-chain corrections are included, AMBER99SB2D-ildn exhibits reliable results that agree with experiments compared with its predecessors, the AMBER14SB, AMBER99SB, AMBER99SB-ildn, and AMBER99SB2D force fields, and that decreasing the overall magnitude of protein-protein interactions in favor of protein-water interactions is a key ingredient behind the improvement.

Original languageEnglish (US)
Pages (from-to)267-274
Number of pages8
JournalJournal of Chemical Information and Modeling
Volume57
Issue number2
DOIs
StatePublished - Feb 27 2017

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Intrinsically Disordered Proteins
Proteins
simulation
interaction
evaluation
Molecular dynamics
water
experiment
Computer simulation
ability
Nuclear magnetic resonance
Peptides
Water
Polypeptides
Experiments

ASJC Scopus subject areas

  • Chemistry(all)
  • Chemical Engineering(all)
  • Computer Science Applications
  • Library and Information Sciences

Cite this

Evaluation of the Coupled Two-Dimensional Main Chain Torsional Potential in Modeling Intrinsically Disordered Proteins. / Gao, Ya; Zhang, Chaomin; Zhang, John; Mei, Ye.

In: Journal of Chemical Information and Modeling, Vol. 57, No. 2, 27.02.2017, p. 267-274.

Research output: Contribution to journalArticle

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