canSAR: update to the cancer translational research and drug discovery knowledgebase.
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Authors
di Micco, P
Antolin, AA
Mitsopoulos, C
Villasclaras-Fernandez, E
Sanfelice, D
Dolciami, D
Ramagiri, P
Mica, IL
Tym, JE
Gingrich, PW
Hu, H
Workman, P
Al-Lazikani, B
Antolin, AA
Mitsopoulos, C
Villasclaras-Fernandez, E
Sanfelice, D
Dolciami, D
Ramagiri, P
Mica, IL
Tym, JE
Gingrich, PW
Hu, H
Workman, P
Al-Lazikani, B
Document Type
Journal Article
Date
2023-01-06
Date Accepted
2022-11-28
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.
Citation
Nucleic Acids Research, 2023, 51 (D1), pp. D1212 - D1219
Source Title
Nucleic Acids Research
Publisher
OXFORD UNIV PRESS
ISSN
0305-1048
eISSN
1362-4962
1362-4962
1362-4962
Collections
Research Team
Computational Biology
Signal Trans & Mol Pharma
Signal Trans & Mol Pharma