Neuro-swarm hybridization for protein tertiary structure prediction

Issue title: Recent Advances in Intelligent Paradigms Fusion and Their Applications

Guest editors: L.C. Jain, C.P. Lim and N.T. Nguyen

Article type: Research Article

Authors: Datta, Ayan^{a; *} | Talukdar, Veera^b | Konar, Amit^a | Jain, Lakhmi C.^c

Affiliations: [a] Department of Electronics and Telecommunication Engineering, Jadavpur University, Kolkata 700032, India | [b] Indian Institute of Social Welfare and Buisness, Management, College Square West, Kolkata-700073, India | [c] Knowledge-Based Intelligent Engineering Systems Centre, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia

Correspondence: [*] Corresponding author. E-mail: ayandatta_ece@yahoo.co.in

Abstract: This paper describes a new approach for predicting tertiary structure of protein using artificial neural network and particle swarm optimization technique. The paper is concetrated around the well known Ab-initio approach for global minimisation of energy function. It predicts the native structure of protein by finding the main chain dihedral angles; through the optimization of CHARMM energy function, using particle swarm optimization algorithm. Side chain dihedral angle are predicted using three layered artificial neural network, realised with back propagation algorithm. This approach has merit as it reduces the dimensionality of the search space and computationally outperforms all other classical technique in atleast 80% cases.

Keywords: Bioinformatics, molecular biology, bio-computing, Evolutionary algorithm, soft computing, swarm intelligence, artificial neural network, protein folding and protein structure prediction

DOI: 10.3233/HIS-2008-5305

Journal: International Journal of Hybrid Intelligent Systems, vol. 5, no. 3, pp. 153-159, 2008