Gaining insight into a small molecule’s polypharmacology through target deconvolution approaches enables the elucidation of drug repositioning opportunities, supports critical drug optimization exercises, and also informs on safety by identifying off-target interactions which may result in deleterious side effects. We compared our in-house in silico MatchMaker Proteome Screening technology to three different Mass Spectrometry (MS) based deconvolution approaches. MatchMaker is a deep learning approach capable of assessing small molecule-protein interactions across the proteome. Known interactors (those with IC50 values &lt;10µM) were cross referenced against both the MS-based and MatchMaker Proteome Screening results. We evaluated approaches by how highly the known interactors ranked in the respective lists. MatchMaker identifies a greater proportion of known interactors, demonstrating that an in silico technology can provide useful insights into a drug’s polypharmacology.

MatchMaker proteome screening identifies more drug-target interactions that MS-based approaches

ACS Spring Meeting 2021

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