Literature DB >> 28864201

OPUS-DOSP: A Distance- and Orientation-Dependent All-Atom Potential Derived from Side-Chain Packing.

Gang Xu1, Tianqi Ma2, Tianwu Zang2, Weitao Sun3, Qinghua Wang4, Jianpeng Ma5.   

Abstract

We report a new distance- and orientation-dependent, all-atom statistical potential derived from side-chain packing, named OPUS-DOSP, for protein structure modeling. The framework of OPUS-DOSP is based on OPUS-PSP, previously developed by us [JMB (2008), 376, 288-301], with refinement and new features. In particular, distance or orientation contribution is considered depending on the range of contact distance. A new auxiliary function in energy function is also introduced, in addition to the traditional Boltzmann term, in order to adjust the contributions of extreme cases. OPUS-DOSP was tested on 11 decoy sets commonly used for statistical potential benchmarking. Among 278 native structures, 239 and 249 native structures were recognized by OPUS-DOSP without and with the auxiliary function, respectively. The results show that OPUS-DOSP has an increased decoy recognition capability comparing with those of other relevant potentials to date.
Copyright © 2017. Published by Elsevier Ltd.

Entities:  

Keywords:  decoy recognition; empirical potential function; protein folding; protein structure prediction; side-chain packing

Mesh:

Year:  2017        PMID: 28864201      PMCID: PMC6193766          DOI: 10.1016/j.jmb.2017.08.013

Source DB:  PubMed          Journal:  J Mol Biol        ISSN: 0022-2836            Impact factor:   5.469


  51 in total

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Authors:  H Gohlke; G Klebe
Journal:  Curr Opin Struct Biol       Date:  2001-04       Impact factor: 6.809

Review 2.  Knowledge-based potential functions in protein design.

Authors:  William P Russ; Rama Ranganathan
Journal:  Curr Opin Struct Biol       Date:  2002-08       Impact factor: 6.809

3.  A novel approach to decoy set generation: designing a physical energy function having local minima with native structure characteristics.

Authors:  Chen Keasar; Michael Levitt
Journal:  J Mol Biol       Date:  2003-05-23       Impact factor: 5.469

4.  Comparative protein structure modeling by iterative alignment, model building and model assessment.

Authors:  Bino John; Andrej Sali
Journal:  Nucleic Acids Res       Date:  2003-07-15       Impact factor: 16.971

5.  TOUCHSTONE II: a new approach to ab initio protein structure prediction.

Authors:  Yang Zhang; Andrzej Kolinski; Jeffrey Skolnick
Journal:  Biophys J       Date:  2003-08       Impact factor: 4.033

6.  Ab initio construction of protein tertiary structures using a hierarchical approach.

Authors:  Y Xia; E S Huang; M Levitt; R Samudrala
Journal:  J Mol Biol       Date:  2000-06-30       Impact factor: 5.469

Review 7.  Development of novel statistical potentials for protein fold recognition.

Authors:  N-V Buchete; J E Straub; D Thirumalai
Journal:  Curr Opin Struct Biol       Date:  2004-04       Impact factor: 6.809

8.  OPUS-Ca: a knowledge-based potential function requiring only Calpha positions.

Authors:  Yinghao Wu; Mingyang Lu; Mingzhi Chen; Jialin Li; Jianpeng Ma
Journal:  Protein Sci       Date:  2007-07       Impact factor: 6.725

9.  The coarse-grained OPEP force field for non-amyloid and amyloid proteins.

Authors:  Yassmine Chebaro; Samuela Pasquali; Philippe Derreumaux
Journal:  J Phys Chem B       Date:  2012-07-16       Impact factor: 2.991

10.  Potential functions for hydrogen bonds in protein structure prediction and design.

Authors:  Alexandre V Morozov; Tanja Kortemme
Journal:  Adv Protein Chem       Date:  2005
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  8 in total

1.  OPUS-SSF: A side-chain-inclusive scoring function for ranking protein structural models.

Authors:  Gang Xu; Tianqi Ma; Qinghua Wang; Jianpeng Ma
Journal:  Protein Sci       Date:  2019-04-11       Impact factor: 6.725

2.  OPUS-Rota4: a gradient-based protein side-chain modeling framework assisted by deep learning-based predictors.

Authors:  Gang Xu; Qinghua Wang; Jianpeng Ma
Journal:  Brief Bioinform       Date:  2022-01-17       Impact factor: 11.622

3.  Secondary structure specific simpler prediction models for protein backbone angles.

Authors:  M A Hakim Newton; Fereshteh Mataeimoghadam; Rianon Zaman; Abdul Sattar
Journal:  BMC Bioinformatics       Date:  2022-01-04       Impact factor: 3.169

4.  A simple neural network implementation of generalized solvation free energy for assessment of protein structural models.

Authors:  Shiyang Long; Pu Tian
Journal:  RSC Adv       Date:  2019-11-06       Impact factor: 4.036

5.  Benchmarking of structure refinement methods for protein complex models.

Authors:  Jacob Verburgt; Daisuke Kihara
Journal:  Proteins       Date:  2021-08-03

6.  Enhancing protein backbone angle prediction by using simpler models of deep neural networks.

Authors:  Fereshteh Mataeimoghadam; M A Hakim Newton; Abdollah Dehzangi; Abdul Karim; B Jayaram; Shoba Ranganathan; Abdul Sattar
Journal:  Sci Rep       Date:  2020-11-10       Impact factor: 4.379

Review 7.  Computational reconstruction of atomistic protein structures from coarse-grained models.

Authors:  Aleksandra E Badaczewska-Dawid; Andrzej Kolinski; Sebastian Kmiecik
Journal:  Comput Struct Biotechnol J       Date:  2019-12-26       Impact factor: 7.271

8.  OPUS-X: An Open-Source Toolkit for Protein Torsion Angles, Secondary Structure, Solvent Accessibility, Contact Map Predictions, and 3D Folding.

Authors:  Gang Xu; Qinghua Wang; Jianpeng Ma
Journal:  Bioinformatics       Date:  2021-09-03       Impact factor: 6.937

  8 in total

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