DTA Atlas: A massive-scale drug repurposing database
Sultanova M. Vinogradova E. Amantay A. Molnár F. Fazli S.
December 2024Elsevier B.V.
Artificial Intelligence in the Life Sciences
2024#6
The drug development process is costly and time-consuming. Repurposing existing approved drugs, an efficient and cost-effective strategy, involves assessing numerous drug-protein pairs to uncover new interactions. While modern in silico methods enhance scalability, an open database for projected drug-target interactions across the entire human proteome is still lacking. In this work, we introduce an open database of predicted drug-target interactions, termed DTA Atlas, covering the entire human proteome as well as a wide range of marketed drugs, resulting in over 220 million drug-target pairs. The database integrates 4 billion affinity predictions from advanced deep neural networks and offers a user-friendly web interface, enabling users to explore drug-target affinity predictions for the human proteome. To the best of our knowledge, DTA Atlas represents the first comprehensive collection of drug-target binding strength predictions. It is open-source and can serve as an important resource for drug development, drug repurposing, toxicity studies and more.
Drug discovery , Drug repurposing database , Drug target affinity prediction , Drugbank , Machine learning , Uniprot
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Department of Computer Sciences, School of Digital Sciences and Engineering, Nazarbayev University, Kabanbay batyr 53, Astana, Z05H0P9, Kazakhstan
Department of Biology, School of Sciences and Humanities, Nazarbayev University, Kabanbay batyr 53, Astana, Z05H0P9, Kazakhstan
Department of Computer Sciences
Department of Biology
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