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can SAR .ai

The integrated knowledge-base that brings together multidisciplinary data across biology, chemistry, pharmacology, structural biology, cellular networks and clinical annotations, and applies machine learning approaches to provide drug-discovery useful predictions.

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Substructure and similarity searches against
the canSAR.ai chemical database
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SUPPORTERS

canSAR.ai is made possible through the help of:

MD Anderson Cancer Center LydaHill Philanthropies Foundation CRUK

DATA PARTNERS

Organizations that help canSAR.ai with data:

DepMap PDBe DataBank ChEMBL Chemical Probes Portal

CITE CANSAR

Kindly cite canSAR:

canSAR: update to the cancer translational research and drug discovery knowledgebase, Costas Mitsopoulos, Patrizio Di Micco, Eloy Villasclaras Fernandez, Daniela Dolciami, Esty Holt, Ioan L. Mica, Elizabeth A. Coker, Joseph E. Tym, James Campbell, Ka Hing Che, Bugra Ozer, Christos Kannas, Albert A. Antolin, Paul Workman, Bissan Al-Lazikani, Nucl. Acids Res. 2021 Jan 8;49(D1):D1074-D1082. doi: 10.1093/nar/gkaa1059

Latest data release for canSAR.ai

Release date: Nov 9, 2022

3D Structures: 183,564 (added 301)
PDB bioassemblies: 1,457,753 (added 2,290)
PDB Chains: 512,629 (added 1,109)
Cavities in PDB chains: 5,492,240 (added 11,207)
Druggable Cavities: 220,171 (added 580)
Protein families: 7,182 (added 14)

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