Protein domain-based prediction of drug/compound-target interactions and experimental validation on LIM kinases.

ABSTRACT: Predictive approaches such as virtual screening have been used in drug discovery with the objective of reducing developmental time and costs. Current machine learning and network-based approaches have issues related to generalization, usability, or model interpretability, especially due to the complexity of target proteins' structure/function, and bias in system training datasets. Here, we propose a new method "DRUIDom" (DRUg Interacting Domain prediction) to identify bio-interactions between drug candidate compounds and targets by utilizing the domain modularity of proteins, to overcome problems associated with current approaches. DRUIDom is composed of two methodological steps. First, ligands/compounds are statistically mapped to structural domains of their target proteins, with the aim

SUBMITTER: Dogan T 

PROVIDER: S-EPMC8659301 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature