Multistage in silico approach to identify novel quinoline derivatives as potential c-kit kinase inhibitors

Abstract

The type II-C-KIT signaling network has been extensively studied for its potential as a target for cancer treatment, leading to the investigation of quinoline derivatives as compounds with inhibitory effects on c-Kit kinase. In this study, a multistage approach was employed, including the creation of pharmacophore models, 3D QSAR analysis, virtual screening, docking investigations, and molecular dynamics stimulation. The pharmacophore evaluation included a data set of 29 ligands, which resulted in the generation of the ADDHR_1pharmacophore model as the most promising, with a survival score of 5.6812. The main objective was to utilize the atom-based 3D-QSAR approach for generating robust 3D-QSAR models aimed at identifying new TypeII-C-kit kinase inhibitors. The evaluations of these models have convincingly demonstrated their high predictive power (Q2 = 0.6547, R2 = 0.9947). Using atom-based 3D-QSAR data, a total of 7564 novel compounds were generated from R-group enumeration. Molecular docking and MM-GBSA study revealed that compound A1 exhibited the highest binding score of −9.30 kcal/mol and a Δ GBind value of −90.56 kcal/mol. The ZINC compounds were then screened using the pharmacophore model, followed by virtual screening, which identified ZINC65798256, ZINC09317958, ZINC73187176, and ZINC76176670 as potential candidates with promising docking scores. Among these, ZINC65798256 demonstrated the best binding interactions with amino acid residues, ASP810, LYS623, CYS673, and THR670 (PDB ID: 1T46). To further analyze the structural features and molecular interactions, molecular dynamics simulation was conducted for a time scale of 100 ns.

Communicated by Ramaswamy H. Sarma

Keywords:

• cKIT kinase inhibitors
• pharmacophore model
• 3D-QSAR model
• virtual screening
• quinoline derivatives
• R-group enumeration

Acknowledgments

The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through Larg Groups Project under grant number RGP.2/3/44.

Ethical Approval

The ethical approval is not applicable for this project.

Conflicts of interest/Competing interests

The authors declare no conflict of interest.

Authors’ contributions

The authors Shankar Gupta, Moumita Saha and Vivek Asati have done the data curation, writing—original draft preparation, visualization, and investigation. Samia Ben Ahmed has included the figures in the manuscript. The author Rajveer Singh has done molecular dynamics simulation, PCA and writing of the study.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Declarations

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Availability of data and material

Supplementary files are attached to the manuscript.

Additional information

Funding

The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through Larg Groups Project under grant number RGP.2/3/44.