Small Molecular Drug Screening Based on Clinical Therapeutic Effect.

ABSTRACT: Virtual screening can significantly save experimental time and costs for early drug discovery. Drug multi-classification can speed up virtual screening and quickly predict the most likely class for a drug. In this study, 1019 drug molecules with actual therapeutic effects are collected from multiple databases and documents, and molecular sets are grouped according to therapeutic effect and mechanism of action. Molecular descriptors and molecular fingerprints are obtained through SMILES to quantify molecular structures. After using the Kennard-Stone method to divide the data set, a better combination can be obtained by comparing the combined results of five classification algorithms and a fusion method. Furthermore, for a specific data set, the model with the best performance is used to pre

SUBMITTER: Zhong C 

PROVIDER: S-EPMC9369618 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature