Literature DB >> 23385383

The intrinsic conformational features of amino acids from a protein coil library and their applications in force field development.

Fan Jiang1, Wei Han, Yun-Dong Wu.   

Abstract

The local conformational (φ, ψ, χ) preferences of amino acid residues remain an active research area, which are important for the development of protein force fields. In this perspective article, we first summarize spectroscopic studies of alanine-based short peptides in aqueous solution. While most studies indicate a preference for the P(II) conformation in the unfolded state over α and β conformations, significant variations are also observed. A statistical analysis from various coil libraries of high-resolution protein structures is then summarized, which gives a more coherent view of the local conformational features. The φ, ψ, χ distributions of the 20 amino acids have been obtained from a protein coil library, considering both backbone and side-chain conformational preferences. The intrinsic side-chain χ(1) rotamer preference and χ(1)-dependent Ramachandran plot can be generally understood by combining the interaction of the side-chain Cγ/Oγ atom with two neighboring backbone peptide groups. Current all-atom force fields such as AMBER ff99sb-ILDN, ff03 and OPLS-AA/L do not reproduce these distributions well. A method has been developed by combining the φ, ψ plot of alanine with the influence of side-chain χ(1) rotamers to derive the local conformational features of various amino acids. It has been further applied to improve the OPLS-AA force field. The modified force field (OPLS-AA/C) reproduces experimental (3)J coupling constants for various short peptides quite well. It also better reproduces the temperature-dependence of the helix-coil transition for alanine-based peptides. The new force field can fold a series of peptides and proteins with various secondary structures to their experimental structures. MD simulations of several globular proteins using the improved force field give significantly less deviation (RMSD) to experimental structures. The results indicate that the local conformational features from coil libraries are valuable for the development of balanced protein force fields.

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Year:  2013        PMID: 23385383     DOI: 10.1039/c2cp43633g

Source DB:  PubMed          Journal:  Phys Chem Chem Phys        ISSN: 1463-9076            Impact factor:   3.676


  16 in total

1.  Insights into Unfolded Proteins from the Intrinsic ϕ/ψ Propensities of the AAXAA Host-Guest Series.

Authors:  Clare-Louise Towse; Jiri Vymetal; Jiri Vondrasek; Valerie Daggett
Journal:  Biophys J       Date:  2016-01-19       Impact factor: 4.033

2.  Effects of phosphorylation on the intrinsic propensity of backbone conformations of serine/threonine.

Authors:  Erbin He; Guanghui Yan; Jian Zhang; Jun Wang; Wenfei Li
Journal:  J Biol Phys       Date:  2016-01-12       Impact factor: 1.365

3.  Intrinsic α-helical and β-sheet conformational preferences: a computational case study of alanine.

Authors:  Diego Caballero; Jukka Määttä; Alice Qinhua Zhou; Maria Sammalkorpi; Corey S O'Hern; Lynne Regan
Journal:  Protein Sci       Date:  2014-05-09       Impact factor: 6.725

4.  The IDP-Specific Force Field ff14IDPSFF Improves the Conformer Sampling of Intrinsically Disordered Proteins.

Authors:  Dong Song; Ray Luo; Hai-Feng Chen
Journal:  J Chem Inf Model       Date:  2017-05-04       Impact factor: 4.956

5.  Molecular dynamics simulation and conformational analysis of some catalytically active peptides.

Authors:  Bahareh Honarparvar; Adam A Skelton
Journal:  J Mol Model       Date:  2015-04-01       Impact factor: 1.810

6.  ff14IDPs force field improving the conformation sampling of intrinsically disordered proteins.

Authors:  Dong Song; Wei Wang; Wei Ye; Dingjue Ji; Ray Luo; Hai-Feng Chen
Journal:  Chem Biol Drug Des       Date:  2016-09-19       Impact factor: 2.817

7.  Modeling the mechanism of CLN025 beta-hairpin formation.

Authors:  Keri A McKiernan; Brooke E Husic; Vijay S Pande
Journal:  J Chem Phys       Date:  2017-09-14       Impact factor: 3.488

8.  Prediction of nearest neighbor effects on backbone torsion angles and NMR scalar coupling constants in disordered proteins.

Authors:  Yang Shen; Julien Roche; Alexander Grishaev; Ad Bax
Journal:  Protein Sci       Date:  2017-10-25       Impact factor: 6.725

9.  New Dynamic Rotamer Libraries: Data-Driven Analysis of Side-Chain Conformational Propensities.

Authors:  Clare-Louise Towse; Steven J Rysavy; Ivan M Vulovic; Valerie Daggett
Journal:  Structure       Date:  2016-01-05       Impact factor: 5.006

10.  The effect of chirality and steric hindrance on intrinsic backbone conformational propensities: tools for protein design.

Authors:  Matthew Carter Childers; Clare-Louise Towse; Valerie Daggett
Journal:  Protein Eng Des Sel       Date:  2016-06-09       Impact factor: 1.650

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