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Molecular & Cellular Proteomics 8:1516-1526, 2009.
© 2009 by The American Society for Biochemistry and Molecular Biology, Inc.

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Research

Multiple Motif Scanning to Identify Methyltransferases from the Yeast Proteome^*,

Tanya C. Petrossian and Steven G. Clarke

From the Department of Chemistry and Biochemistry and the Molecular Biology Institute, University of California, Los Angeles, California 90095

A new program (Multiple Motif Scanning) was developed to scan the Saccharomyces cerevisiae proteome for Class I S-adenosylmethionine-dependent methyltransferases. Conserved Motifs I, Post I, II, and III were identified and expanded in known methyltransferases by primary sequence and secondary structural analysis through hidden Markov model profiling of both a yeast reference database and a reference database of methyltransferases with solved three-dimensional structures. The roles of the conserved amino acids in the four motifs of the methyltransferase structure and function were then analyzed to expand the previously defined motifs. Fisher-based negative log statistical matrix sets were developed from the prevalence of amino acids in the motifs. Multiple Motif Scanning is able to scan the proteome and score different combinations of the top fitting sequences for each motif. In addition, the program takes into account the conserved number of amino acids between the motifs. The output of the program is a ranked list of proteins that can be used to identify new methyltransferases and to reevaluate the assignment of previously identified putative methyltransferases. The Multiple Motif Scanning program can be used to develop a putative list of enzymes for any type of protein that has one or more motifs conserved at variable spacings and is freely available (www.chem.ucla.edu/files/MotifSetup.Zip). Finally hidden Markov model profile clustering analysis was used to subgroup Class I methyltransferases into groups that reflect their methyl-accepting substrate specificity.

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