Abstract
Myeloid cell leukemia (Mcl-1) protein, belonging to a large BCL2 family of proteins, is a significant target towards cancer chemotherapy. The over-expression of this protein is also responsible for the development and progression of severe multi-drug resistance in cancer patients. This present study has focused the attention towards unmasking of important structural fingerprints for promoting or hindering Mcl-1 inhibitory activity of some indole-based derivatives by using Monte Carlo optimization-based QSAR approach. Twenty-one robust classification models were generated. The best model (by using SMILES and HSG-based descriptors) was selected, and several important good and bad structural fingerprints for Mcl-1 inhibition were identified. Some of the fingerprints were matching with the earlier study (New J. Chem., 2020, 44, 17494-17506) and some new fingerprints were also generated. The modelling study will help the researchers in the lead optimization of some indole-based Mcl-1 inhibitors in the future.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Quantitative Structure-Property Relationships
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
