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A Scoring Function for Motif Template Alignments with ProMOL
Author(s) -
Madha Shariq,
Kovuri Venkata Aditya,
Bryan Michael,
Craig Paul,
Bernstein Herbert
Publication year - 2015
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.29.1_supplement.567.8
Subject(s) - false positive paradox , computer science , discriminant function analysis , plug in , visualization , true positive rate , pattern recognition (psychology) , protein data bank (rcsb pdb) , motif (music) , computational biology , artificial intelligence , function (biology) , distance matrix , protein function , data mining , algorithm , biology , machine learning , genetics , biochemistry , physics , acoustics , programming language , gene
ProMOL is a 3D motif alignment plugin for PyMol, the molecular visualization tool. The tool compares the structures of proteins against a library of known motifs to attempt to assign function to the protein. By using a scoring function to compare the results, it is possible to better discriminate between true and false positives. The scoring function uses a 3‐dimensional matrix to score how likely residues are to be a certain distance from the each other. This matrix was developed using empirical data retrieved from multiple pdb files determining the frequencies of residues distances. It was shown using discriminant analysis that the scoring function was able to accurately rank the obtained matches found by ProMOL. Funding was provided by RIT, Dowling College, and NIGMS 2R15GM078077‐02, 3R15GM078077‐02S1, and 3R15GM078077‐02S2.