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Whole proteome mapping of compound-protein interactions.

ABSTRACT: Off-target binding is one of the primary causes of toxic side effects of drugs in clinical development, resulting in failures of clinical trials. While off-target drug binding is a known phenomenon, experimental identification of the undesired protein binders can be prohibitively expensive due to the large pool of possible biological targets. Here, we propose a new strategy combining chemical similarity principle and deep learning to enable proteome-wide mapping of compound-protein interactions. We have developed a pipeline to identify the targets of bioactive molecules by matching them with chemically similar annotated "bait" compounds and ranking them with deep learning. We have constructed a user-friendly web server for drug-target identification based on chemical similarity (DRIFT) to perform searches across annotated bioactive compound datasets, thus enabling high-throughput, multi-ligand target identification, as well as chemical fragmentation of target-binding moieties.

SUBMITTER: Chirasani VR

PROVIDER: S-EPMC10732549 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Whole proteome mapping of compound-protein interactions.

Chirasani Venkat R VR Wang Jian J Sha Congzhou C Raup-Konsavage Wesley W Vrana Kent K Dokholyan Nikolay V NV

Current research in chemical biology 20220912

Off-target binding is one of the primary causes of toxic side effects of drugs in clinical development, resulting in failures of clinical trials. While off-target drug binding is a known phenomenon, experimental identification of the undesired protein binders can be prohibitively expensive due to the large pool of possible biological targets. Here, we propose a new strategy combining chemical similarity principle and deep learning to enable proteome-wide mapping of compound-protein interactions. ...[more]

PMID: 38125869

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