Platinum(IV) compounds as potential drugs: a quantitative structure-activity relationship study.

ABSTRACT:

Introduction

Machine learning methods, coupled with a tremendous increase in computer power in recent years, are promising tools in modern drug design and drug repurposing.

Methods

Machine learning predictive models, publicly available at chemosophia.com, were used to predict the bioactivity of recently synthesized platinum(IV) complexes against different kinds of diseases and medical conditions. Two novel QSAR models based on the BiS algorithm are developed and validated, capable to predict activities against the SARS-CoV virus and its RNA dependent RNA polymerase.

Results

The internal predictive power of the QSAR models was tested by 10-fold cross-validation, giving cross-R² from 0.863 to 0.903. 38 different activities, ranging from antioxidant, antibacte

SUBMITTER: Novak J 

PROVIDER: S-EPMC10509740 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature