Integrated Computational Approach for the Discovery of Novel Tropomyosin Receptor Kinase (TRKs) Inhibitors as Anticancer Agents

Abstract TRK fusion proteins, encoded by gene fusions in NTRK family of genes are responsible for different types of cancers. Resistance and adverse effects of available TRK inhibitors viz., larotrectinib and entrectinib necessitate the search for safer alternatives. This study was aimed to identify novel TRK inhibitors from a series of pyrazolo‐pyridine derivatives based on advanced computational approaches. 3D‐QSAR modelling, Virtual screening, ADMET analysis and Molecular Docking helped to identify novel TRK inhibitors. Results were validated based on MM‐GBSA, MD simulations and DFT analysis. The 3D‐QSAR modeling showed strong predictability (R 2 = 0.9080; Q 2 = 0.672), resulted in identification of compound E7, while compound DB4093 emerged as a top candidate from virtual screening. Favourable pharmacokinetic profile was indicated by ADMET studies. Both compounds, E7 and DB4093 have demonstrated strong binding affinity viz., −10.39 Kcal/mol and −12.05 Kcal/mol respectively with the TRK receptor, forming multiple stable hydrogen bonds with key active site residues. MM‐GBSA analysis has shown favourable binding free energies as compared to (Entrectinib −32.419 kcal/mol). Stable bindings were confirmed by MD simulations and DFT analysis. Our research work has led to the identification of E7 and DB4093 as promising TRK inhibitors warranting further experimental validation.