Neuro-swarm hybridization for protein tertiary structure prediction

Authors:
Ayan Datta;Veera Talukdar;Amit Konar;Lakhmi C. Jain
Affiliations:
(Correspd. E-mail: ayandatta_ece@yahoo.co.in) Department of Electronics and Telecommunication Engineering, Jadavpur University, Kolkata 700032, India;Indian Institute of Social Welfare and Buisness, Management, College Square West, Kolkata-700073, India;Department of Electronics and Telecommunication Engineering, Jadavpur University, Kolkata 700032, India;Knowledge-Based Intelligent Engineering Systems Centre, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia
Venue:
International Journal of Hybrid Intelligent Systems - Recent Advances in Intelligent Paradigms Fusion and Their Applications
Year:
2008

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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.