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Title: A computational design strategy for discovering the protein targets of histone lysine methyltransferases
Author: Alonso Martínez, Diego
ISNI:       0000 0004 7657 7578
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2018
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The activity of lysine methyltransferases (KMTs) is crucial for the regulation of chromatin-related processes, such as gene expression. Since all KMTs catalyse the transfer of a methyl group from the same SAM cofactor, no current technology is able to directly assess which KMT has performed each observed methylation in a cellular context. This information would be particularly informative in the development of more specific treatments for epigenetically-regulated diseases, such as cancer. To address this technology gap, this work aims at developing a "methylome" profiling assay based on engineering synthetic SAM cofactors specific towards a given KMT. Our proposed computational design strategy takes aligned crystal structures of KMTs as input to identify unique cavities in wild type KMTs that could accommodate complementary synthetic "bumps" on SAM. SAM analogues with sterically matching "bumps" are then designed, and molecular dynamics simulations are utilised to predict their binding mode and affinity with the target KMT to rank the designs. The highest-ranked SAM analogues are synthesised and include an isotopically-heavy methyl donor group (CD3), which retains the biological-consistency of cellular methylation and renders new methylation events detectable via MS. The ability of the KMT to utilise the synthesised SAM analogues as a cofactor for methylation is finally assessed using in vitro assays and quantified via LC-MS/MS proteomics. The results of this work identified bumped SAM analogues that were selective to certain KMTs lacking a post-SET domain. Specifically, a natural pocket was identified in the SET domain of SETD7 that does not exist in post-SET containing KMTs, such as G9a. Complementary bumped SAM analogues were designed and synthesised for experimental validation. A computational screening approach using docking, molecular dynamics and binding affinity estimation revealed that the binding mode and affinity for some of these bumped SAM analogues were comparable to the one of native SAM for SETD7, but not for G9a. Subsequent in vitro experiments using recombinant G9a and SETD7 with our engineered SAM analogues and nucleosome substrates revealed cofactor selectivity towards SETD7. These results were consistent with the predictions of the computational screening approach, which supports the feasibility of our proposed design methodology.
Supervisor: DiMaggio, Peter Sponsor: Imperial College London
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral