Mining the protein data bank with CReF to predict approximate 3-D structures of polypeptides.
n this paper we describe CReF, a Central Residue Fragment-based method to predict approximate 3-D structures of polypeptides by mining the Protein Data Bank (PDB). The approximate predicted structures are good enough to be used as starting conformations in refinement procedures employing state-of-the-art molecular mechanics methods such as molecular dynamics simulations. CReF is very fast and we illustrate its efficacy in three case studies of polypeptides whose sizes vary from 34 to 70 amino acids. As indicated by the RMSD values, our initial results show that the predicted structures adopt the expected fold, similar to the experimental ones.
Dorn
Márcio
M
Laboratório de Bioinformática, Modelagem e Simulação de Biossistemas--LABIO, Programa de Pós-Graduação em Ciência da Computação, Faculdade de Informática, Pontificia Universidade Católica do Rio Grande do Sul, Porto Alegre, RS, Brazil. marcio.dorn@pucrs.br
de Souza
Osmar Norberto
ON
D057225:Data Mining / Q000379:methods*; D030562:Databases, Protein; D056004:Molecular Dynamics Simulation; D010455:Peptides / Q000737:chemistry*; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry
D010455:Peptides; D011506:Proteins