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.

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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
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article

DTA Atlas: A massive-scale drug repurposing database

Ferdinand Molnár, Siamac Fazli, Alisher Amantay, E. B. Vinogradova et al.
2 citations
Artificial Intelligence in the Life Sciences
Computational Drug Discovery Methods
0.72
article

DTA Atlas: A massive-scale drug repurposing database

Ferdinand Molnár, Siamac Fazli, Alisher Amantay, E. B. Vinogradova, Madina Sultanova
article en
2 citations

Abstract

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.

Artificial Intelligence in the Life SciencesVol. 6
Nazarbayev University (KZ)
Openalex Percentile: Top 25%
Computational Drug Discovery Methods
0.72
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DTA Atlas: A massive-scale drug repurposing database — Ferdinand Molnár, Siamac Fazli, et al. · Artificial Intelligence in the Life Sciences (2024) | TGRS Research Map | TGRS