In silico insights into design of novel VEGFR-2 inhibitors: SMILES-based QSAR modelling, and docking studies on substituted benzo-fused heteronuclear derivatives

ABSTRACT

Eight QSAR models (M1–M8) were developed from a dataset of 118 benzo-fused heteronuclear derivatives targeting VEGFR-2 by Monte Carlo optimization method of CORALSEA 2023 software. Models were generated with hybrid optimal descriptors using both SMILES and Graphs with zero- and first-order Morgan extended connectivity index from a training set of 103 derivatives. All statistical parameters for model validation were within the prescribed limits, establishing the models to be robust and of excellent quality. Among all models, split-2 of M5 was the best-fit as reflected by $\mathit{\hspace{0.17em}}{r}_{\mathrm{v}\mathrm{a}\mathrm{lidation}}^2$, $\mathit{\hspace{0.17em}}{Q}_{\mathrm{v}\mathrm{a}\mathrm{lidation}}^2$ and $\mathrm{MAE}$. Mechanistic interpretation of this model assisted the identification of structural descriptors as promoters and hinderers for VEGFR-2 inhibition. These descriptors were utilized to design novel VEGFR-2 inhibitors (YS01-YS07) by bringing modifications in compound MS90 in the dataset. Docking of all designed compounds, MS90 and sorafenib with VEGFR-2 binding site revealed favourable binding interactions. Docking score of YS07 was higher than that of MS90 and sorafenib. Molecular dynamics simulation study revealed sustained interactions of YS07 with key amino acids of VEGFR-2 at a run time of 100 ns. This study concludes the development of a best fit QSAR model which can assist the design of new anticancer agents targeting VEGFR-2.

KEYWORDS:

• VEGFR-2 inhibitor
• QSAR
• Monte-Carlo
• benzimidazole
• benzoxazole
• benzothiazole

Acknowledgements

The authors would like to record their deep sense of gratitude and profound thanks to Dr. Andrey A. Toropov and Dr. Alla P. Toropov for providing the CORAL software.

Disclosure statement

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

Supplementary material

Supplemental data for this article can be accessed at: https://doi.org/10.1080/1062936X.2024.2332203.

Additional information

Funding

The authors report that there is no funding associated with the work featured in this article.