Improved side-chain modeling by coupling clash-detection guided iterative search with rotamer relaxation

Motivation: Side-chain modeling has seen wide applications in computational structure biology. Most of the popular side-chain modeling programs explore the conformation space using discrete rigid rotamers for speed and efficiency. However, in the tightly packed environments of protein interiors, the...

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Published inBioinformatics Vol. 27; no. 6; pp. 785 - 790
Main Authors Cao, Yang, Song, Lin, Miao, Zhichao, Hu, Yun, Tian, Liqing, Jiang, Taijiao
Format Journal Article
LanguageEnglish
Published Oxford Oxford University Press 15.03.2011
Subjects
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ISSN1367-4803
1367-4811
1367-4811
1460-2059
DOI10.1093/bioinformatics/btr009

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Abstract Motivation: Side-chain modeling has seen wide applications in computational structure biology. Most of the popular side-chain modeling programs explore the conformation space using discrete rigid rotamers for speed and efficiency. However, in the tightly packed environments of protein interiors, these methods will inherently lead to atomic clashes and hinder the prediction accuracy. Results: We present a side-chain modeling method (CIS-RR), which couples a novel clash-detection guided iterative search (CIS) algorithm with continuous torsion space optimization of rotamers (RR). Benchmark testing shows that compared with the existing popular side-chain modeling methods, CIS-RR removes atomic clashes much more effectively and achieves comparable or even better prediction accuracy while having comparable computational cost. We believe that CIS-RR could be a useful method for accurate side-chain modeling. Availability: CIS-RR is available to non-commercial users at our website: http://jianglab.ibp.ac.cn/lims/cisrr/cisrr.html. Contact:  taijiao@moon.ibp.ac.cn Supplementary information:  Supplementary data are available at Bioinformatics online.
AbstractList Motivation: Side-chain modeling has seen wide applications in computational structure biology. Most of the popular side-chain modeling programs explore the conformation space using discrete rigid rotamers for speed and efficiency. However, in the tightly packed environments of protein interiors, these methods will inherently lead to atomic clashes and hinder the prediction accuracy.Results: We present a side-chain modeling method (CIS-RR), which couples a novel clash-detection guided iterative search (CIS) algorithm with continuous torsion space optimization of rotamers (RR). Benchmark testing shows that compared with the existing popular side-chain modeling methods, CIS-RR removes atomic clashes much more effectively and achieves comparable or even better prediction accuracy while having comparable computational cost. We believe that CIS-RR could be a useful method for accurate side-chain modeling.
Side-chain modeling has seen wide applications in computational structure biology. Most of the popular side-chain modeling programs explore the conformation space using discrete rigid rotamers for speed and efficiency. However, in the tightly packed environments of protein interiors, these methods will inherently lead to atomic clashes and hinder the prediction accuracy. We present a side-chain modeling method (CIS-RR), which couples a novel clash-detection guided iterative search (CIS) algorithm with continuous torsion space optimization of rotamers (RR). Benchmark testing shows that compared with the existing popular side-chain modeling methods, CIS-RR removes atomic clashes much more effectively and achieves comparable or even better prediction accuracy while having comparable computational cost. We believe that CIS-RR could be a useful method for accurate side-chain modeling. CIS-RR is available to non-commercial users at our website: http://jianglab.ibp.ac.cn/lims/cisrr/cisrr.html.
Side-chain modeling has seen wide applications in computational structure biology. Most of the popular side-chain modeling programs explore the conformation space using discrete rigid rotamers for speed and efficiency. However, in the tightly packed environments of protein interiors, these methods will inherently lead to atomic clashes and hinder the prediction accuracy.MOTIVATIONSide-chain modeling has seen wide applications in computational structure biology. Most of the popular side-chain modeling programs explore the conformation space using discrete rigid rotamers for speed and efficiency. However, in the tightly packed environments of protein interiors, these methods will inherently lead to atomic clashes and hinder the prediction accuracy.We present a side-chain modeling method (CIS-RR), which couples a novel clash-detection guided iterative search (CIS) algorithm with continuous torsion space optimization of rotamers (RR). Benchmark testing shows that compared with the existing popular side-chain modeling methods, CIS-RR removes atomic clashes much more effectively and achieves comparable or even better prediction accuracy while having comparable computational cost. We believe that CIS-RR could be a useful method for accurate side-chain modeling.RESULTSWe present a side-chain modeling method (CIS-RR), which couples a novel clash-detection guided iterative search (CIS) algorithm with continuous torsion space optimization of rotamers (RR). Benchmark testing shows that compared with the existing popular side-chain modeling methods, CIS-RR removes atomic clashes much more effectively and achieves comparable or even better prediction accuracy while having comparable computational cost. We believe that CIS-RR could be a useful method for accurate side-chain modeling.CIS-RR is available to non-commercial users at our website: http://jianglab.ibp.ac.cn/lims/cisrr/cisrr.html.AVAILABILITYCIS-RR is available to non-commercial users at our website: http://jianglab.ibp.ac.cn/lims/cisrr/cisrr.html.
Motivation: Side-chain modeling has seen wide applications in computational structure biology. Most of the popular side-chain modeling programs explore the conformation space using discrete rigid rotamers for speed and efficiency. However, in the tightly packed environments of protein interiors, these methods will inherently lead to atomic clashes and hinder the prediction accuracy. Results: We present a side-chain modeling method (CIS-RR), which couples a novel clash-detection guided iterative search (CIS) algorithm with continuous torsion space optimization of rotamers (RR). Benchmark testing shows that compared with the existing popular side-chain modeling methods, CIS-RR removes atomic clashes much more effectively and achieves comparable or even better prediction accuracy while having comparable computational cost. We believe that CIS-RR could be a useful method for accurate side-chain modeling. Availability: CIS-RR is available to non-commercial users at our website: http://jianglab.ibp.ac.cn/lims/cisrr/cisrr.html. Contact:  taijiao@moon.ibp.ac.cn Supplementary information:  Supplementary data are available at Bioinformatics online.
Author Hu, Yun
Jiang, Taijiao
Miao, Zhichao
Cao, Yang
Song, Lin
Tian, Liqing
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Snippet Motivation: Side-chain modeling has seen wide applications in computational structure biology. Most of the popular side-chain modeling programs explore the...
Side-chain modeling has seen wide applications in computational structure biology. Most of the popular side-chain modeling programs explore the conformation...
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SubjectTerms Algorithms
Biological and medical sciences
Computational Biology - methods
Fundamental and applied biological sciences. Psychology
General aspects
Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects)
Models, Molecular
Protein Conformation
Proteins - chemistry
Software
Title Improved side-chain modeling by coupling clash-detection guided iterative search with rotamer relaxation
URI https://www.ncbi.nlm.nih.gov/pubmed/21216772
https://www.proquest.com/docview/856766875
https://www.proquest.com/docview/869804273
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