bioRxivBioinformaticsPreprint
Leveraging AI and structural proteomics for rational design of a KAT6A degrader
Gali AradiD, Nitzan SimchiiD, Sagie Brodsky, Alon ShtrikmaniD, Yonatan Kedem, Iris Alchanati, Galina Otonin, Anjana ShenoyiD, Dimitri KovalerchikiD, Michal Ran Shchory, Yaron Ben Shoshan-Galeczki, Noam Cohen, Katharina Lange, Eran Seger, Kirill Pevzner
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Abstract
While targeted protein degraders such as PROTACs are a clinically proven therapeutic strategy, the discovery of novel degraders remains hampered by trial-and-error process. To address this challenge, we developed the AIMS platform, which combines structural proteomics with AI models for rational PROTAC design. AIMS is an end-to-end toolkit for PROTAC optimization, encompassing structure solving using proteomics and AI, prediction of ADME and degradation properties, and prospective ranking of compound design ideas. Altogether, this integrated platform successfully enabled the multi-parameter optimization of a potent and bioavailable in vivo validated KAT6A degrader, establishing a versatile framework for PROTAC development across various targets. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=71 SRC="FIGDIR/small/727609v1_ufig1.gif" ALT="Figure 1"> View larger version (17K): org.highwire.dtl.DTLVardef@13596d0org.highwire.dtl.DTLVardef@140500eorg.highwire.dtl.DTLVardef@147e585org.highwire.dtl.DTLVardef@12dbdfe_HPS_FORMAT_FIGEXP M_FIG C_FIG
- organism: human
- assay: proteomics
- research focus: drug response / drug discovery
- approach: machine learning (classical)
- approach: statistical model
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