Nicosia, Giuseppe and Stracquadanio, Giovanni (2008) Generalized Pattern Search Algorithm for Peptide Structure Prediction. Biophysical Journal, 95 (10). pp. 4988-4999. DOI https://doi.org/10.1529/biophysj.107.124016
Nicosia, Giuseppe and Stracquadanio, Giovanni (2008) Generalized Pattern Search Algorithm for Peptide Structure Prediction. Biophysical Journal, 95 (10). pp. 4988-4999. DOI https://doi.org/10.1529/biophysj.107.124016
Nicosia, Giuseppe and Stracquadanio, Giovanni (2008) Generalized Pattern Search Algorithm for Peptide Structure Prediction. Biophysical Journal, 95 (10). pp. 4988-4999. DOI https://doi.org/10.1529/biophysj.107.124016
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 |
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Uncontrolled Keywords: | Peptides; Sequence Alignment; Sequence Analysis, Protein; Amino Acid Sequence; Protein Conformation; Algorithms; Models, Chemical; Models, Molecular; Computer Simulation; Molecular Sequence Data; Pattern Recognition, Automated |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 13 Feb 2017 11:00 |
Last Modified: | 04 Dec 2024 06:37 |
URI: | http://repository.essex.ac.uk/id/eprint/18705 |