Protein folding optimization based on 3D off-lattice model via an improved artificial bee colony algorithm

Verfasser / Beitragende:
[Bai Li, Mu Lin, Qiao Liu, Ya Li, Changjun Zhou]
Ort, Verlag, Jahr:
2015
Enthalten in:
Journal of Molecular Modeling, 21/10(2015-10-01), 1-15
Format:
Artikel (online)
ID: 605512337
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024 7 0 |a 10.1007/s00894-015-2806-y  |2 doi 
035 |a (NATIONALLICENCE)springer-10.1007/s00894-015-2806-y 
245 0 0 |a Protein folding optimization based on 3D off-lattice model via an improved artificial bee colony algorithm  |h [Elektronische Daten]  |c [Bai Li, Mu Lin, Qiao Liu, Ya Li, Changjun Zhou] 
520 3 |a Protein folding is a fundamental topic in molecular biology. Conventional experimental techniques for protein structure identification or protein folding recognition require strict laboratory requirements and heavy operating burdens, which have largely limited their applications. Alternatively, computer-aided techniques have been developed to optimize protein structures or to predict the protein folding process. In this paper, we utilize a 3D off-lattice model to describe the original protein folding scheme as a simplified energy-optimal numerical problem, where all types of amino acid residues are binarized into hydrophobic and hydrophilic ones. We apply a balance-evolution artificial bee colony (BE-ABC) algorithm as the minimization solver, which is featured by the adaptive adjustment of search intensity to cater for the varying needs during the entire optimization process. In this work, we establish a benchmark case set with 13 real protein sequences from the Protein Data Bank database and evaluate the convergence performance of BE-ABC algorithm through strict comparisons with several state-of-the-art ABC variants in short-term numerical experiments. Besides that, our obtained best-so-far protein structures are compared to the ones in comprehensive previous literature. This study also provides preliminary insights into how artificial intelligence techniques can be applied to reveal the dynamics of protein folding. Graphical Abstract Protein folding optimization using 3D off-lattice model and advanced optimization techniques 
540 |a Springer-Verlag Berlin Heidelberg, 2015 
690 7 |a Artificial bee colony  |2 nationallicence 
690 7 |a Numerical optimization  |2 nationallicence 
690 7 |a Off-lattice model  |2 nationallicence 
690 7 |a Protein folding  |2 nationallicence 
690 7 |a Protein structure optimization  |2 nationallicence 
700 1 |a Li  |D Bai  |u College of Control Science and Engineering, Zhejiang University, 310027, Hangzhou, China  |4 aut 
700 1 |a Lin  |D Mu  |u College of Biomedical Engineering and Instrument Science, Zhejiang University, 310027, Hangzhou, China  |4 aut 
700 1 |a Liu  |D Qiao  |u School of Advanced Engineering, Beihang University, 100191, Beijing, China  |4 aut 
700 1 |a Li  |D Ya  |u School of Mathematics and Systems Science & LMIB, Beihang University, 100191, Beijing, China  |4 aut 
700 1 |a Zhou  |D Changjun  |u Key Laboratory of Advanced Design and Intelligent Computing, Dalian University, 116622, Dalian, China  |4 aut 
773 0 |t Journal of Molecular Modeling  |d Springer Berlin Heidelberg  |g 21/10(2015-10-01), 1-15  |x 1610-2940  |q 21:10<1  |1 2015  |2 21  |o 894 
856 4 0 |u https://doi.org/10.1007/s00894-015-2806-y  |q text/html  |z Onlinezugriff via DOI 
898 |a BK010053  |b XK010053  |c XK010000 
900 7 |a Metadata rights reserved  |b Springer special CC-BY-NC licence  |2 nationallicence 
908 |D 1  |a research-article  |2 jats 
949 |B NATIONALLICENCE  |F NATIONALLICENCE  |b NL-springer 
950 |B NATIONALLICENCE  |P 856  |E 40  |u https://doi.org/10.1007/s00894-015-2806-y  |q text/html  |z Onlinezugriff via DOI 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Li  |D Bai  |u College of Control Science and Engineering, Zhejiang University, 310027, Hangzhou, China  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Lin  |D Mu  |u College of Biomedical Engineering and Instrument Science, Zhejiang University, 310027, Hangzhou, China  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Liu  |D Qiao  |u School of Advanced Engineering, Beihang University, 100191, Beijing, China  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Li  |D Ya  |u School of Mathematics and Systems Science & LMIB, Beihang University, 100191, Beijing, China  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Zhou  |D Changjun  |u Key Laboratory of Advanced Design and Intelligent Computing, Dalian University, 116622, Dalian, China  |4 aut 
950 |B NATIONALLICENCE  |P 773  |E 0-  |t Journal of Molecular Modeling  |d Springer Berlin Heidelberg  |g 21/10(2015-10-01), 1-15  |x 1610-2940  |q 21:10<1  |1 2015  |2 21  |o 894