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Generalized pattern search algorithm for peptide structure prediction

Nicosia, G and Stracquadanio, G (2008) 'Generalized pattern search algorithm for peptide structure prediction.' Biophysical Journal, 95 (10). 4988 - 4999. ISSN 0006-3495

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Abstract

Finding the near-native structure of a protein is one of the most important open problems in structural biology and biological physics. The problem becomes dramatically more difficult when a given protein has no regular secondary structure or it does not show a fold similar to structures already known. This situation occurs frequently when we need to predict the tertiary structure of small molecules, called peptides. In this research work, we propose a new ab initio algorithm, the generalized pattern search algorithm, based on the well-known class of Search-and-Poll algorithms. We performed an extensive set of simulations over a well-known set of 44 peptides to investigate the robustness and reliability of the proposed algorithm, and we compared the peptide conformation with a state-of-the-art algorithm for peptide structure prediction known as PEPstr. In particular, we tested the algorithm on the instances proposed by the originators of PEPstr, to validate the proposed algorithm; the experimental results confirm that the generalized pattern search algorithm outperforms PEPstr by 21.17% in terms of average root mean-square deviation, RMSD Cα. © 2008 by the Biophysical Society.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Giovanni Stracquadanio
Date Deposited: 13 Feb 2017 11:00
Last Modified: 30 Jan 2019 16:16
URI: http://repository.essex.ac.uk/id/eprint/18705

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