An Integrated Multi-QSAR Modeling Approach for Designing Knoevenagel- Type Indoles with Enhancing Cytotoxic Profiles

Title:An Integrated Multi-QSAR Modeling Approach for Designing Knoevenagel- Type Indoles with Enhancing Cytotoxic Profiles

Volume: 13 Issue: 4

Author(s): Sk. Abdul Amin, Nilanjan Adhikari, Tarun Jha*Shovanlal Gayen*

Affiliation:

• Natural Science Laboratory, Division of Medicinal and Pharmaceutical Chemistry, Department of Pharmaceutical Technology, P.O. Box 17020, Jadavpur University, Kolkata 700032, (WB),India

• Laboratory of Drug Design and Discovery, Department of Pharmaceutical Sciences, Dr. Harisingh Gour University (A Central University), Sagar 470003, (MP),India

Keywords: Knoevenagel-type indoles, cytotoxic agents, ANN, SVM, Bayesian classification model, HQSAR, Topomer CoMFA, molecular docking.

Abstract: Background: Unconventional Knoevenagel-type indoles have been the topic of interest of many synthetic chemists because of its promising efficacy in different diseases including cancer.

Objective: To explore the structural requirements of Knoevenagel-type cytotoxic indoles for higher efficacy.

Methods: Multi-QSAR modeling (MLR, ANN, SVM, Bayesian classification, HQSAR and Topomer CoMFA) was performed on these analogs.

Results: All these modeling techniques were validated individually and interpreted with the experimental SAR observations. Phenyl or p-methoxyphenyl substitution at 2nd position, electron withdrawing groups (such as sulphonyl, cyano etc.) at 3rd position and methoxy substation at 5th position of the indole scaffold may favor cytotoxicity. Eight new indole molecules were predicted from the developed QSAR models.

Conclusion: These newly designed compounds may bind to the colchicine binding site of the tubulin protein as suggested by the molecular docking study.

Cite this article as:

Amin Abdul Sk. , Adhikari Nilanjan , Jha Tarun *, Gayen Shovanlal *, An Integrated Multi-QSAR Modeling Approach for Designing Knoevenagel- Type Indoles with Enhancing Cytotoxic Profiles, Current Computer-Aided Drug Design 2017; 13 (4) . https://dx.doi.org/10.2174/1573409913666170309150014