biostudies-literatureThafar MAKing Abdullah University of Science and Technology4751https://www.ebi.ac.uk/biostudies/studies/S-EPMC8934358biostudies-literatureUnknown12(1)Drug-target interaction (DTI) prediction plays a crucial role in drug repositioning and virtual drug screening. Most DTI prediction methods cast the problem as a binary classification task to predict if interactions exist or as a regression task to predict continuous values that indicate a drug's ability to bind to a specific target. The regression-based methods provide insight beyond the binary relationship. However, most of these methods require the three-dimensional (3D) structural information of targets which are still not generally available to the targets. Despite this bottleneck, only a few methods address the drug-target binding affinity (DTBA) problem from a non-structure-based approach to avoid the 3D structure limitations. Here we propose Affinity2Vec, as a novel regression-baseScientific reportsAffinity2Vec: drug-target binding affinity prediction through representation learning, graph mining, and machine learning.PMC8934358BAS/1/1059-01-01URF/1/4098-01-01FCC/1/1976-20-01REI/1/4216-01-01REI/1/4473- 01-01BAS/1/1624-01-01REI/1/4437-01-01FCC/1/1976-26-01URF/1/3450-01-01Alshahrani MEssack MGojobori TGao XAlbaradei SThafar MAfalseAffinity2Vec: drug-target binding affinity prediction through representation learning, graph mining, and machine learning.Drug-target interaction (DTI) prediction plays a crucial role in drug repositioning and virtual drug screening. Most DTI prediction methods cast the problem as a binary classification task to predict if interactions exist or as a regression task to predict continuous values that indicate a drug's ability to bind to a specific target. The regression-based methods provide insight beyond the binary relationship. However, most of these methods require the three-dimensional (3D) structural information of targets which are still not generally available to the targets. Despite this bottleneck, only a few methods address the drug-target binding affinity (DTBA) problem from a non-structure-based approach to avoid the 3D structure limitations. Here we propose Affinity2Vec, as a novel regression-base2022-01-01T00:00:00Z2022 Mar2026-07-14T14:45:37.048Z2025-04-04T22:04:12.286ZS-EPMC89343583530652510.1038/s41598-022-08787-9