In silico development of potential therapeutic for the pain treatment by inhibiting voltage-gated sodium channel 1.7

The voltage-gated sodium channel Nav1.7 can be considered as a promising target for the treatment of pain. This research presents conformational-independent and 3D field-based QSAR modeling for a series of aryl sulfonamide acting as Nav1.7 inhibitors. As descriptors used for building conformation-independent QSAR models, SMILES notation and local invariants of the molecular graph were used with the Monte Carlo optimization method as a model developer. Different statistical methods, including the index of ideality of correlation, were used to test the quality of the developed models, robustness and predictability and obtained results were good. Obtained results indicate that there is a very good correlation between 3D QSAR and conformation-independent models. Molecular fragments that account for the increase/decrease of a studied activity were defined and used for the computer-aided design of new compounds as potential analgesics. The final evaluation of the developed QSAR models and designed inhibitors were carried out using molecular docking studies, bringing to light an excellent correlation with the QSAR modeling results.

Automated summary

This study developed a conformation-independent and 3D field-based QSAR modeling approach for designing Nav1.7 inhibitors for pain treatment, and verified the model quality and predictability through various statistical methods. The results showed a strong correlation between 3D QSAR and conformation-independent models, facilitating computer-aided design of new compounds as potential analgesics.