School of Biotechnology and Biomolecular Sciences , University of New South Wales , New South Wales , 2052 , Australia.
J Proteome Res. 2018 Oct 5;17(10):3485-3491. doi: 10.1021/acs.jproteome.8b00396. Epub 2018 Sep 6.
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 substrate recognition motifs. In MT-MAMS, peptide sets are synthesized which contain all amino acid 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-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-(STRCKMAQHG)-Φ; 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-^P-G-G-Φ. 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 ^(DE)-^(DE)-R-(G ≫ A)-(GN > RAW)-(FYW > ILKHM) and ^(DE)-^(DE)-R-(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.
蛋白质甲基转移酶通常通过线性序列基序识别其底物。确定这些基序对于了解甲基转移酶的机制、功能和药物靶向至关重要。在这里,我们描述了 MT-MAMS(通过质谱分析甲基转移酶基序),这是一种用于表征甲基转移酶底物识别基序的定量方法。在 MT-MAMS 中,合成了包含模板序列中单个位置处所有氨基酸取代的肽集。然后,将这些肽与感兴趣的甲基转移酶在氘化 S-腺苷甲硫氨酸(D-AdoMet)的存在下孵育。使用这种重甲基供体可使甲基化肽产生独特的质量位移,从而通过质谱法对其进行明确的定量。然后得出每个取代产生的甲基化的化学计量,最后生成甲基转移酶底物识别基序。我们通过应用于赖氨酸甲基转移酶 G9a 来验证 MT-MAMS,生成了底物识别基序(TKRN)-(A > RS > G)-(R ≫ K)-K-(STRCKMAQHG)-Φ;这与先前通过肽阵列确定的高度相似。然后,我们确定了酵母赖氨酸延伸因子甲基转移酶 1(Efm1)的识别基序为(Y > FW)-K-^P-G-G-Φ。这是一种新的赖氨酸甲基转移酶识别基序,仅包含非带电残基,不包括靶赖氨酸。我们进一步确定了主要的酵母和人类精氨酸甲基转移酶 Hmt1 和 PRMT1 的识别基序,分别揭示为^(DE)-^(DE)-R-(G ≫ A)-(GN > RAW)-(FYW > ILKHM)和^(DE)-^(DE)-R-(G ≫ N)-(GR > ANK)-(K > YHMFILW)。这些基序大大扩展了经典的 RGG 识别基序,并包括这些酶的负特异性,这是 MT-MAMS 独有的特征。最后,我们表明 MT-MAMS 可用于深入了解蛋白质甲基转移酶的连续性。