Paper Info
Title
Mixing Energy Models in Genetic Algorithms for On-Lattice Protein Structure Prediction.
Abstract
Protein structure prediction (PSP) is computationally a very challenging problem. The challenge largely comes from the fact that the energy function that needs to be minimised in order to obtain the native structure of a given protein is not clearly known. A high resolution 20x20 energy model could better capture the behaviour of the actual energy function than a low resolution energy model such as hydrophobic polar. However, the fine grained details of the high resolution interaction energy matrix are often not very informative for guiding the search. In contrast, a low resolution energy model could effectively bias the search towards certain promising directions. In this paper, we develop a genetic algorithm that mainly uses a high resolution energy model for protein structure evaluation but uses a low resolution HP energy model in focussing the search towards exploring structures that have hydrophobic cores. We experimentally show that this mixing of energy models leads to significant lower energy structures compared to the state-of-the-art results.
Year
DOI
Venue
2013
10.1155/2013/924137
BIOMED RESEARCH INTERNATIONAL
Keywords
Field
DocType
amino acid sequence,computational biology,proteins,protein folding,protein conformation,algorithms
Protein structure prediction,Protein folding,Biology,Biological system,Matrix (mathematics),Biochemistry,Lattice protein,Interaction energy,Polar,Genetic algorithm,Protein structure
Journal
Volume
ISSN
Citations 
2013
2314-6133
3
PageRank 
References 
Authors
0.37
28
4
Name
Order
Citations
PageRank
Mahmood A. Rashid1818.69
M. A. Hakim Newton212017.81
Md. Tamjidul Hoque3415.44
abdul sattar41389185.70