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37 METHYLATION PHARMACOGENOMICS: DATABASE MINING TO IDENTIFY NOVEL HUMAN SMALL MOLECULE AND PROTEIN METHYLTRANSFERASES
  1. O. E. Salavaggione,
  2. M. Wiepert,
  3. R. Reddy,
  4. C. G. Chute,
  5. R. M. Weinshilboum
  1. Rochester, MN

Abstract

S-Adenosyl-L-methionine (AdoMet)-dependent methylation is an important pathway in the methylation of many drugs, other xenobiotics, neurotransmitters and hormones. Macromolecules such as proteins, RNA and DNA can also be methylated. It has been estimated that from 1 to 3% of human genes encode methyltransferase (MT) enzymes. In the present study, we set out to use a database mining strategy to identify human genes encoding small molecule and protein MTs. Our first step was to search human genome databases with amino acid sequences for 18 known and 17 putative human MTs. Specifically, we performed tBLASTN searches with these 35 protein sequences against 25 refseq databases (Chr1-22, X, Y, and Un). That process resulted in 18,499 hits. A series of filters was then applied for E-values of<30, query length ≥ 50, and percentage identity with the query sequence of 25% or greater. At the end of that process, 10,791 hits remained, 5,425 forward and 5,366 reverse. We then removed sequences that were more than 500 or less than 100 amino acids in length, leaving 2,196 protein sequences. Since MTs contain 2 conserved regions, referred to as regions I and III, that are involved in AdoMet binding, we also performed local alignments with regions I and III from 23 of the query MTs with the 2196 remaining proteins. That process left 553 unique proteins, including 167 that were thought to be likely small molecule and protein MTs. Of those 167 proteins, 140 had not previously been characterized as MTs. Sequence identity and gene structure similarity among these 167 proteins were then compared. These 140 novel putative human MTs are now candidates for functional and pharmacogenomic study and characterization. Supported in part by NIH grants R01 GM28157 and U01 GM61388.

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