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Real Valued Genetic Algorithm Based Approach for Protein Structure Prediction - Role of Biophysical Filters for reduction of Conformational Search SpaceAuthors: Madhu Smitha,Abhijit Mitra,Harjinder Singh Conference: (2008) Third IAPR International Conference on Pattern Recognition in Bioinformatics PRIB 2008, October 15- 17 2008. Novotel St Kilda. Melbourne, Australia. (Accepted) Date: 2008-06-06 Report no: IIIT/TR/2008/16 AbstractPredicting the 3D native conformation of a protein given the amino acid sequence is known as protein structure prediction (PSP)problem and is one of the greatest challenge of computational biology. The current work uses a real valued Genetic Algorithm (GA), a powerful variant of conventional GA to simulate the PSP problem. It consists of three evolutionary operators to manipulate the genes and a fitness function based on a simple force field. The individuals of the population correspond to different conformations of the same polypeptide chain, represented by a string of (phi,psi)torsion angles. The conformations are generated under the constraints of Ramachandran plot along with secondary structure information, which are then screened through a set of knowledge based biophysical filters, viz. persistence length and radius of gyration. Only the structures satisfying the filtering criteria are considered for energy minimization using GA. The algorithm has been validated on a set of known globular protein containing 2-4 secondary structure elements. For all the test proteins the algorithm converges rapidly ad the converged structure shows a backbone RMSD (root mean square deviation) or 3-6A as compared to the native structure. Full paper: pdf Centre for Computational Natural Sciences and Bioinformatics |
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