Multimodal data fusion for supervised learning-based identification of USP7 inhibitors: a systematic comparison.

ABSTRACT: Ubiquitin-specific-processing protease 7 (USP7) is a promising target protein for cancer therapy, and great attention has been given to the identification of USP7 inhibitors. Traditional virtual screening methods have now been successfully applied to discover USP7 inhibitors aiming at reducing costs and speeding up time in several studies. However, due to their unsatisfactory accuracy, it is still a difficult task to develop USP7 inhibitors. In this study, multiple supervised learning classifiers were built to distinguish active USP7 inhibitors from inactive ligands. Physicochemical descriptors, MACCS keys, ECFP4 fingerprints and SMILES were first calculated to represent the compounds in our in-house dataset. Two deep learning (DL) models and nine classical machine learning (ML) models wer

SUBMITTER: Shen WF 

PROVIDER: S-EPMC9835315 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature