TY - JOUR
T1 - DTA Atlas
T2 - A massive-scale drug repurposing database
AU - Sultanova, Madina
AU - Vinogradova, Elizaveta
AU - Amantay, Alisher
AU - Molnár, Ferdinand
AU - Fazli, Siamac
N1 - Publisher Copyright:
© 2024
PY - 2024/12
Y1 - 2024/12
N2 - 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.
AB - 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.
KW - Drug discovery
KW - Drug repurposing database
KW - Drug target affinity prediction
KW - Drugbank
KW - Machine learning
KW - Uniprot
UR - http://www.scopus.com/inward/record.url?scp=85207000926&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85207000926&partnerID=8YFLogxK
U2 - 10.1016/j.ailsci.2024.100115
DO - 10.1016/j.ailsci.2024.100115
M3 - Article
AN - SCOPUS:85207000926
SN - 2667-3185
VL - 6
JO - Artificial Intelligence in the Life Sciences
JF - Artificial Intelligence in the Life Sciences
M1 - 100115
ER -