ArticleBiophysical journal2008
Generalized pattern search algorithm for Peptide structure prediction.
Article in Biophysical journal, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Structural information in therapeutic peptides: Emerging applications in biomedicine.FEBS open bio · 2025Review
- Revealing innovative JAK1 and JAK3 inhibitors: a comprehensive study utilizing QSAR, 3D-Pharmacophore screening, molecular docking, molecular dynamics, and MM/GBSA analyses.Frontiers in molecular biosciences · 2024Article
- APPTEST is a novel protocol for the automatic prediction of peptide tertiary structures.Briefings in bioinformatics · 2021Article
- PEPstrMOD: structure prediction of peptides containing natural, non-natural and modified residues.Biology direct · 2015Article
- Article
- A versatile method for systematic conformational searches: application to CheY.Journal of computational chemistry · 2011Article
- Article
- ASPDock: protein-protein docking algorithm using atomic solvation parameters model.BMC bioinformatics · 2011Article
- PEP-FOLD: an online resource for de novo peptide structure prediction.Nucleic acids research · 2009Article
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2 authors.
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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 C(alpha).
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