Design of novel anti-cancer drugs targeting TRKs inhibitors based 3D QSAR, molecular docking and molecular dynamics simulation

Abstract

Tropomyosin receptor kinase (TRK) enzymes are responsible for different types of tumors caused by neurotrophic tyrosine receptor kinase gene fusion and have been identified as an effective target for anticancer therapy. The study of the mechanism between polo-like kinase (PLKs) and pyrazol inhibitors was performed using 3D-QSAR modeling, molecular docking, and MD simulations in order to design high-activity inhibitors. The HQSAR (Q² = 0.793, R² = 0.917, R²_ext = 0.961), CoMFA (Q² = 0.582, R² = 0.722, R²_ext = 0.951), CoMSIA/SE (Q² = 0.603, R² = 0.801, R²_ext = 0.849), and Topomer CoMFA (Q² = 0.726, R² = 0.992, R²_ext = 0.717) showed good reliability and predictability. All models have been successfully tested by external validation, so all five established models are reliable. The analysis of the different contour maps of different models gives structural information to improve the inhibitory function. Molecular docking results show that the amino acids Met 592, GLU 590, LEU 657, VAL 524, and PHE 589 are the active sites of the tropomyosin receptor TRKs. The results obtained by MD showed that compound 19i could form a more stable complex protein (PDB id: 5KVT). Based on these results, we developed new compounds and their expected inhibitory activities. The results of physicochemical and ADME-Tox properties showed that the four proposed molecules are orally bioavailable, and they are not toxic in the Ames test. Thus, these results would provide modeling information that could help experimental researchers find TRK type I inhibitors more efficiently.

Communicated by Ramaswamy H. Sarma

Keywords:

• 2/3D-QSAR
• TRKs inhibitors
• molecular docking
• dynamic molecular
• drug design
• pharmacokinetics proprieties

Disclosure statement

No potential conflict of interest was reported by the authors.

Authors’ contributions

Mohammed Er-Rajy contributed to data curation, formal analysis, methodology, resources, software, writing – original draft and writing – review editing. Mohamed el Fadili contributed to investigation and methodology. Somdutt Mujwar contributed to MD simulation, docking analysis, manuscript review and editing. Sara Zarougui contributed to supervision and visualization. Menana Elhallaoui contributed to conceptualization, methodology, project administration, supervision, validation, visualization and writing – review and editing.

Data availability statement

Yes.

Additional information

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.