MT-MAMS: protein methyltransferase motif analysis by mass spectrometry.

Protein methyltransferases often recognize their substrates through linear sequence motifs. The determination of these motifs is critical to understand methyltransferase mechanism, function, and drug targeting. Here we describe MT-MAMS (methyltransferase motif analysis by mass spectrometry), a quantitative approach to characterize methyltransferase sets are synthesized which contain all amino acid substrate recognition motifs. In MT-MAMS, Peptide sets substitutions at single positions within a template sequence. These are then incubated with the methyltransferase of interest in the presence of deuterated S-adenosyl methionine (D-3-AdoMet). The use of this heavy methyl donor gives unique mass shifts to methylated peptides, allowing their unambiguous quantification by mass spectrometry. The stoichiometry of methylation resulting from each substitution is then derived, and finally the methyltransferase substrate recognition motif is generated. We validated MT-MAMS by application to lysine methyltransferase G9a, generating the substrate recognition motif (TKRN)-(A > RS > G)-(R >> K)-(K) under bar-(STRCKMAQHG)-Phi; this is highly similar to that previously determined by peptide arrays. We then determined the recognition motif of yeast lysine elongation factor methyltransferase 1 (Efm1) to be (Y > FW)-(K) under bar-boolean AND P-G-G-Phi. This is a new type of lysine methyltransferase recognition motif that only contains noncharged residues, excluding the target lysine. We further determined recognition motifs of major yeast and human arginine methyltransferases Hmt1 and PRMT1, revealing them to be boolean AND(DE)-boolean AND(DE)-(R) under bar-(G >> A)-(GN > RAW)-(FYW > ILKHM) and boolean AND(DE) -boolean AND(DE)-(R) under bar-(G >> N)-(GR > ANK)-(K > YHMFILW), respectively. These motifs expand significantly on the canonical RGG recognition motif and include the negative specificity of these enzymes, a feature unique to MT-MAMS. Finally, we show that MT-MAMS can be used to generate insights into the processivity of protein methyltransferases.