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Refinement of the ProMOL Algorithm and Determination of Function Based on Homology
Author(s) -
Madha Shariq,
Lambrecht Mitchell,
Mills Jeffrey L.,
Bernstein Herbert J.,
Craig Paul A.
Publication year - 2016
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.30.1_supplement.1077.1
Subject(s) - protein data bank (rcsb pdb) , template , computer science , visualization , plug in , homology modeling , homology (biology) , protein data bank , function (biology) , data mining , computational biology , sequence alignment , algorithm , protein structure , bioinformatics , peptide sequence , biology , programming language , genetics , amino acid , biochemistry , enzyme , gene
ProMOL is a plugin for the molecular visualization program PyMOL and is designed to align proposed catalytic residues from proteins of unknown function to those of known and catalogued functions. Roughly 4% of the structures in the Protein Data Bank (PDB) are proteins with unknown functions. The focus of this study is a test of the reliability of function prediction by ProMOL, based on analysis of several thousand structures of known function. Initial structural alignments using standard settings within ProMOL found that approximately 44% of these 10,000 structures of known function were properly identified using 296 motif templates in the ProMOL library if homologs are selected solely by EC class. However, we found that if we define homologs as those structures that share both EC class and Pfam family, the identification rate improved significantly from 44% to 66%. We are further refining the algorithm in ProMOL to include sequence alignment to further improve the true positive rate. Support or Funding Information This work was supported in part by NIH GM078077.