RoFDT: Identification of Drug-Target Interactions from Protein Sequence and Drug Molecular Structure Using Rotation Forest.

ABSTRACT: As the basis for screening drug candidates, the identification of drug-target interactions (DTIs) plays a crucial role in the innovative drugs research. However, due to the inherent constraints of small-scale and time-consuming wet experiments, DTI recognition is usually difficult to carry out. In the present study, we developed a computational approach called RoFDT to predict DTIs by combining feature-weighted Rotation Forest (FwRF) with a protein sequence. In particular, we first encode protein sequences as numerical matrices by Position-Specific Score Matrix (PSSM), then extract their features utilize Pseudo Position-Specific Score Matrix (PsePSSM) and combine them with drug structure information-molecular fingerprints and finally feed them into the FwRF classifier and validate the perf

SUBMITTER: Wang Y 

PROVIDER: S-EPMC9138819 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature