canSAR: update to the cancer translational research and drug discovery knowledgebase

DOI: 10.1093/nar/gkac1004

Authors: Patrizio Di micco (Anderson Cancer Center; The Institute of Cancer Research) , Albert A. Antolin (The Institute of Cancer Research) , Costas Mitsopoulos (The Institute of Cancer Research) , Eloy Villasclaras-Fernandez (The Institute of Cancer Research) , Domenico Sanfelice (The Institute of Cancer Research) , Daniela Dolciami (The Institute of Cancer Research) , Pradeep Ramagiri (The Institute of Cancer Research) , Ioan l. Mica (Anderson Cancer Center; The Institute of Cancer Research) , Joseph e. Tym (The Institute of Cancer Research) , Philip w. Gingrich (Anderson Cancer Center) , Huabin Hu (The Institute of Cancer Research) , Paul Workman (The Institute of Cancer Research) , Bissan Al-Lazikani (Anderson Cancer Center)
Co-authored by industrial partner: No

Type: Journal Paper
Journal: Nucleic Acids Research , VOL 40

State: Published (Approved)
Published: November 2022

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.

Subject Areas: Medicine, Information and Communication Technology

Diamond Offline Facilities: XChem
Instruments: NONE-No attached Diamond beamline

Added On: 05/12/2022 10:33

Documents:
gkac1004.pdf

Discipline Tags:

Non-Communicable Diseases Health & Wellbeing Cancer Data management / presentation Information & Communication Technologies Drug Discovery Life Sciences & Biotech

Technical Tags:

Diffraction Macromolecular Crystallography (MX) Fragment Screening