Literature DB >> 21949272

RASP: rapid modeling of protein side chain conformations.

Zhichao Miao1, Yang Cao, Taijiao Jiang.   

Abstract

MOTIVATION: Modeling of side chain conformations constitutes an indispensable effort in protein structure modeling, protein-protein docking and protein design. Thanks to an intensive attention to this field, many of the existing programs can achieve reasonably good and comparable prediction accuracy. Moreover, in our previous work on CIS-RR, we argued that the prediction with few atomic clashes can complement the current existing methods for subsequent analysis and refinement of protein structures. However, these recent efforts to enhance the quality of predicted side chains have been accompanied by a significant increase of computational cost.
RESULTS: In this study, by mainly focusing on improving the speed of side chain conformation prediction, we present a RApid Side-chain Predictor, called RASP. To achieve a much faster speed with a comparable accuracy to the best existing methods, we not only employ the clash elimination strategy of CIS-RR, but also carefully optimize energy terms and integrate different search algorithms. In comprehensive benchmark testings, RASP is over one order of magnitude faster (~ 40 times over CIS-RR) than the recently developed methods, while achieving comparable or even better accuracy.

Mesh:

Substances:

Year:  2011        PMID: 21949272     DOI: 10.1093/bioinformatics/btr538

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  20 in total

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Journal:  Bioinformatics       Date:  2020-06-01       Impact factor: 6.937

4.  Assessment of protein side-chain conformation prediction methods in different residue environments.

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Journal:  Proteins       Date:  2014-03-31

5.  TMDIM: an improved algorithm for the structure prediction of transmembrane domains of bitopic dimers.

Authors:  Han Cao; Marcus C K Ng; Siti Azma Jusoh; Hio Kuan Tai; Shirley W I Siu
Journal:  J Comput Aided Mol Des       Date:  2017-09-01       Impact factor: 3.686

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Journal:  Nucleic Acids Res       Date:  2016-05-05       Impact factor: 16.971

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

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Journal:  Brief Bioinform       Date:  2022-01-17       Impact factor: 11.622

9.  Comparative evaluation of spin-label modeling methods for protein structural studies.

Authors:  Maxx H Tessmer; Elizabeth R Canarie; Stefan Stoll
Journal:  Biophys J       Date:  2022-08-10       Impact factor: 3.699

10.  Computational Feasibility of an Exhaustive Search of Side-Chain Conformations in Protein-Protein Docking.

Authors:  Taras Dauzhenka; Petras J Kundrotas; Ilya A Vakser
Journal:  J Comput Chem       Date:  2018-09-18       Impact factor: 3.376

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