Title:Pharmacophore, 3D-QSAR Models and Dynamic Simulation of 1,4-Benzothiazines for Colorectal Cancer Treatment
VOLUME: 20 ISSUE: 8
Author(s):Amit Rai, Vinit Raj, Mohamed H. Aboumanei, Ashok K. Singh, Amit K. Keshari, Suraj P. Verma and Sudipta Saha*
Affiliation:Department of Pharmaceutical Sciences, Babasaheb Bhimrao Ambedkar University, Vidya Vihar, Rae Bareli Road, Lucknow 226025, Department of Pharmaceutical Sciences, Babasaheb Bhimrao Ambedkar University, Vidya Vihar, Rae Bareli Road, Lucknow 226025, Labeled Compound Department, Hot Lab Center, Egyptian Atomic Center Energy Authority, Cairo 11371, Department of Pharmaceutical Sciences, Babasaheb Bhimrao Ambedkar University, Vidya Vihar, Rae Bareli Road, Lucknow 226025, Department of Pharmaceutical Sciences, Babasaheb Bhimrao Ambedkar University, Vidya Vihar, Rae Bareli Road, Lucknow 226025, Department of Pharmaceutical Sciences, Kumaun University, Bhimtal Campus, Nainital Uttarakand, Department of Pharmaceutical Sciences, Babasaheb Bhimrao Ambedkar University, Vidya Vihar, Rae Bareli Road, Lucknow 226025
Keywords:1, 4-Benzothiazine, pharmacophore modeling, 3D-QSAR, interleukin-6, colon cancer, docking study and molecular
dynamic simulation.
Abstract:Aim and Objective: Interleukin-6 has become an attractive protein target. This is found in
the progression of colon cancer. It performs various functions in the colon cancer cells such as
inflammation, activates various cell types signaling and also promotes proliferation in colon cancer
cells. It is a valid target to develop anticolon cancer drug. The purpose of our study is to develop the
Three-dimensional Quantitative Structure-Activity Relationship (3D-QSAR) models,
pharmacophore modeling and docking study as well as MD simulation to find out the novel potent
inhibitors that bind with Interleukin-6 in colon cancer treatment.
Material and Methods: In this study, common pharmacophore models and atom-based 3D-QSAR
studies were carried out by using 1,4-benzothiazine derivatives with their experiential GI50values
towards HT-29 human colon cancer cell line.
Results: The common pharmacophore model (ADHR26) was developed and the survival score was
found to be 3.828. The generated pharmacophore-based alignment was used to develop a predictive
atom-based 3D-QSAR model by using Partial Least Square (PLS) method. Phase predictable activity
and LogGI50 also exhibited the most significant atomic position in the backbone structure of ligands
for anticolon cancer activity. Molecular dynamic and docking studies for the IL-6 target provide key
framework of ligand for the anticolon cancer activity.
Conclusion: Finally, results generated from the work data, that exhibited the pharmacophore models
and 3D-QSAR hypothesis might be a path of milestone in the area of medicinal chemistry to
researchers for further design of new and potent IL-6 inhibitors.
