Generation of Chemical Space of Compounds for Prostate Cancer Treatment: Biological Activity Prediction, Clustering, and Visualization of Chemical Space.

ABSTRACT: Designing molecules for pharmaceutical purposes has been a significant focus for several decades. The pursuit of novel drugs is an arduous and financially demanding undertaking. Nevertheless, the integration of computer-assisted frameworks presents a swift avenue for designing and screening drug-like compounds. Within the context of this research, we introduce a comprehensive approach for the design and screening of compounds tailored to the treatment of prostate cancer. To forecast the biological activity of these compounds, we employed machine learning (ML) models. Additionally, an automated process involving the deconstruction and reconstruction of molecular building blocks leads to the generation of novel compounds. Subsequently, the ML models were utilized to predict the biological ac

SUBMITTER: Ishfaq M 

PROVIDER: S-EPMC10600879 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature