canSAR 2024-an update to the public drug discovery knowledgebase.

Autor:	Gingrich PW; Department of Genomic Medicine; Therapeutics Discovery Division; and The Institute for Data Science in Oncology; University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA., Chitsazi R; Department of Genomic Medicine; Therapeutics Discovery Division; and The Institute for Data Science in Oncology; University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA., Biswas A; Department of Genomic Medicine; Therapeutics Discovery Division; and The Institute for Data Science in Oncology; University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA., Jiang C; Department of Genomic Medicine; Therapeutics Discovery Division; and The Institute for Data Science in Oncology; University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA., Zhao L; Department of Genomic Medicine; Therapeutics Discovery Division; and The Institute for Data Science in Oncology; University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA., Tym JE; Enterprise Development and Integration, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA., Brammer KM; Enterprise Development and Integration, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA., Li J; Enterprise Development and Integration, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA., Shu Z; Enterprise Development and Integration, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA., Maxwell DS; Department of Genomic Medicine; Therapeutics Discovery Division; and The Institute for Data Science in Oncology; University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA., Tacy JA; Enterprise Development and Integration, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA., Mica IL; Enterprise Development and Integration, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA., Darkoh M; Department of Genomic Medicine; Therapeutics Discovery Division; and The Institute for Data Science in Oncology; University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA., di Micco P; Department of Genomic Medicine; Therapeutics Discovery Division; and The Institute for Data Science in Oncology; University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA., Russell KP; Department of Genomic Medicine; Therapeutics Discovery Division; and The Institute for Data Science in Oncology; University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA., Workman P; Centre for Cancer Drug Discovery, Division of Cancer Therapeutics, The Institute of Cancer Research, London SW7 3RP, UK., Al-Lazikani B; Department of Genomic Medicine; Therapeutics Discovery Division; and The Institute for Data Science in Oncology; University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Jazyk:	angličtina
Zdroj:	Nucleic acids research [Nucleic Acids Res] 2024 Nov 13. Date of Electronic Publication: 2024 Nov 13.
DOI:	10.1093/nar/gkae1050
Abstrakt:	canSAR (https://cansar.ai) continues to serve as the largest publicly available platform for cancer-focused drug discovery and translational research. It integrates multidisciplinary data from disparate and otherwise siloed public data sources as well as data curated uniquely for canSAR. In addition, canSAR deploys a suite of curation and standardization tools together with AI algorithms to generate new knowledge from these integrated data to inform hypothesis generation. Here we report the latest updates to canSAR. As well as increasing available data, we provide enhancements to our algorithms to improve the offering to the user. Notably, our enhancements include a revised ligandability classifier leveraging Positive Unlabeled Learning that finds twice as many ligandable opportunities across the pocketome, and our revised chemical standardization pipeline and hierarchy better enables the aggregation of structurally related molecular records. (© The Author(s) 2024. Published by Oxford University Press on behalf of Nucleic Acids Research.)
Databáze:	MEDLINE
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