AUTHOR=Khan Mohd Imran , Park Taehwan , Imran Mohammad Azhar , Gowda Saralamma Venu Venkatarame , Lee Duk Chul , Choi Jaehyuk , Baig Mohammad Hassan , Dong Jae-June TITLE=Development of machine learning models for the screening of potential HSP90 inhibitors JOURNAL=Frontiers in Molecular Biosciences VOLUME=9 YEAR=2022 URL=https://www.frontiersin.org/journals/molecular-biosciences/articles/10.3389/fmolb.2022.967510 DOI=10.3389/fmolb.2022.967510 ISSN=2296-889X ABSTRACT=

Heat shock protein 90 (Hsp90) is a molecular chaperone playing a significant role in the folding of client proteins. This cellular protein is linked to the progression of several cancer types, including breast cancer, lung cancer, and gastrointestinal stromal tumors. Several oncogenic kinases are Hsp90 clients and their activity depends on this molecular chaperone. This makes HSP90 a prominent therapeutic target for cancer treatment. Studies have confirmed the inhibition of HSP90 as a striking therapeutic treatment for cancer management. In this study, we have utilized machine learning and different in silico approaches to screen the KCB database to identify the potential HSP90 inhibitors. Further evaluation of these inhibitors on various cancer cell lines showed favorable inhibitory activity. These inhibitors could serve as a basis for future development of effective HSP90 inhibitors.