CanSAR: update to the cancer translational research and drug discovery knowledgebase. Issue Volume 51:Issue D1(2023) (29th November 2022)

• Record Type: Journal Article
• Authors: di Micco, Patrizio; Antolin, Albert A; Mitsopoulos, Costas; Villasclaras-Fernandez, Eloy; Sanfelice, Domenico; Dolciami, Daniela; Ramagiri, Pradeep; Mica, Ioan L; Tym, Joseph E; Gingrich, Philip W; Hu, Huabin; Workman, Paul; Al-Lazikani, Bissan
• Is Part Of: Nucleic acids research. Volume 51:Issue D1(2023)
• Page Start: D1212
• Page End: D1219
• Publication Date: 2022-11-29
• Subjects: Nucleic acids -- Periodicals; Molecular biology -- Periodicals; 572.805
• DOI: 10.1093/nar/gkac1004
• Languages: English
• ISSNs: 0305-1048

Abstract

Abstract: canSAR (https://cansar.ai ) is the largest public cancer drug discovery and translational research knowledgebase. Now hosted in its new home at MD Anderson Cancer Center, canSAR integrates billions of experimental measurements from across molecular profiling, pharmacology, chemistry, structural and systems biology. Moreover, canSAR applies a unique suite of machine learning algorithms designed to inform drug discovery. Here, we describe the latest updates to the knowledgebase, including a focus on significant novel data. These include canSAR's ligandability assessment of AlphaFold; mapping of fragment-based screening data; and new chemical bioactivity data for novel targets. We also describe enhancements to the data and interface.