MTAF-DTA: multi-type attention fusion network for drug-target affinity prediction.

ABSTRACT:

Background

The development of drug-target binding affinity (DTA) prediction tasks significantly drives the drug discovery process forward. Leveraging the rapid advancement of artificial intelligence, DTA prediction tasks have undergone a transformative shift from wet lab experimentation to machine learning-based prediction. This transition enables a more expedient exploration of potential interactions between drugs and targets, leading to substantial savings in time and funding resources. However, existing methods still face several challenges, such as drug information loss, lack of calculation of the contribution of each modality, and lack of simulation regarding the drug-target binding mechanisms.

Results

We propose MTAF-DTA, a method for drug-target binding affinity predi

SUBMITTER: Sun J 

PROVIDER: S-EPMC11622562 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature