Protein Folding Prediction in a Cubic Lattice in Hydrophobic-Polar Model

The tertiary structure of the proteins determines their functions. Therefore, the predicting of protein's tertiary structure, based on the primary amino acid sequence from long time, is the most important and challenging subject in biochemistry, molecular biology, and biophysics. One of the mos...

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Vydané v:Journal of computational biology Ročník 24; číslo 5; s. 412
Hlavní autori: Yanev, Nicola, Traykov, Metodi, Milanov, Peter, Yurukov, Borislav
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: United States 01.05.2017
Predmet:
Algorithms
Amino Acid Sequence
Amino Acids - chemistry
Computational Biology - methods
Hydrophobic and Hydrophilic Interactions
Models, Molecular
Monte Carlo Method
Protein Conformation
Protein Folding
Protein Structure, Tertiary
Proteins - chemistry
protein folding
3D lattice
heuristics
HP model
bioinformatics
mixed integer programming
ISSN:1557-8666, 1557-8666
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Shrnutí:The tertiary structure of the proteins determines their functions. Therefore, the predicting of protein's tertiary structure, based on the primary amino acid sequence from long time, is the most important and challenging subject in biochemistry, molecular biology, and biophysics. One of the most popular protein structure prediction methods, called Hydrophobic-Polar (HP) model, is based on the observation that in polar environment hydrophobic amino acids are in the core of the molecule-in contact between them and more polar amino acids are in contact with the polar environment. In this study, we present a new mixed integer programming formulation, exact algorithm, and two heuristic algorithms to solve the protein folding problem stated as a combinatorial optimization problem in a simple cubic lattice. The results from computational runs on a set of benchmarks are favorably compared to known algorithms for solving the 3D lattice HP model as genetic algorithms, ant colony optimization algorithm, and Monte Carlo algorithm.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1557-8666
1557-8666
DOI:10.1089/cmb.2016.0181