DTI-LM: language model powered drug-target interaction prediction.

ABSTRACT:

Motivation

The identification and understanding of drug-target interactions (DTIs) play a pivotal role in the drug discovery and development process. Sequence representations of drugs and proteins in computational model offer advantages such as their widespread availability, easier input quality control, and reduced computational resource requirements. These make them an efficient and accessible tools for various computational biology and drug discovery applications. Many sequence-based DTI prediction methods have been developed over the years. Despite the advancement in methodology, cold start DTI prediction involving unknown drug or protein remains a challenging task, particularly for sequence-based models. Introducing DTI-LM, a novel framework leveraging advanced pretrained lang

SUBMITTER: Ahmed KT 

PROVIDER: S-EPMC11520403 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature