Motif-based fold assignment.

L Salwinski; D Eisenberg

doi:10.1110/ps.14401

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Motif-based fold assignment.

L Salwinski·D Eisenberg

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Abstract

Conventional fold recognition techniques rely mainly on the analysis of the entire sequence of a protein. We present an MBA method to improve performance of any conventional sequence-based fold assignment. The method uses sequence motifs, such as those defined in the Prosite database, and the SwissProt annotation of the fold library. When combined with a simple SDP method, the coverage of MBA is comparable to the results obtained with PSI-BLAST. However, the set of the MBA predictions is significantly different from that of PSI-BLAST, leading to a 40% increase of the coverage for the combined MBA/PSI-BLAST method. The MBA approach can be easily adopted to include the results of sequence-independent function prediction methods and alternative motif and annotation databases. The method is available through the web server localized at http://www.doe-mbi.ucla.edu/mba.

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Algorithms Amino Acid Motifs Animals Databases as Topic Humans Models, Biological Models, Statistical Models, Theoretical Protein Conformation Protein Folding Protein Structure, Secondary Software Journal Article Research Support, U.S. Gov't, Non-P.H.S.Research Support, U.S. Gov't, P.H.S.

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L Salwinski, D Eisenberg. 2001. Motif-based fold assignment.. https://doi.org/10.1110/ps.14401

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