DTA Atlas: A massive-scale drug repurposing database
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.
Authors
- Ferdinand Molnár (ORCID: https://orcid.org/0000-0001-9008-4233)
- Siamac Fazli (ORCID: https://orcid.org/0000-0003-3397-0647)
- Alisher Amantay
- E. B. Vinogradova (ORCID: https://orcid.org/0009-0003-1845-2726)
- Madina Sultanova
Institutions
- Nazarbayev University (KZ)
Publication Details
- Journal
- Artificial Intelligence in the Life Sciences
- Published
- 2024-10-18
- DOI
- https://doi.org/10.1016/j.ailsci.2024.100115
- Citations
- 2
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.72