# Structure-Guided Discovery of Benzoic-Acid-Based TRPC6 Ligands: An Integrated Docking, MD, and MM-GBSA SAR Study: Potential Therapeutic Molecules for Autism Spectrum Disorder

## TL;DR

This study identifies benzoic-acid-based molecules that may act as TRPC6 ligands, potentially offering new therapeutic options for autism spectrum disorder.

## Contribution

The study introduces a novel structure-guided computational workflow to discover and prioritize TRPC6 ligands for autism treatment.

## Key findings

- Compound BT11 showed strong interactions with TRPC6, including hydrogen bonds and π–π stacking.
- BT11 had a favorable docking score and lower RMSD during MD simulations compared to the reference compound.
- MM-GBSA predicted the most favorable binding energy for BT11, suggesting it as a promising TRPC6 ligand.

## Abstract

Background: TRPC6 is recognized as a therapeutically relevant cation channel, whose activation is governed by specific ligand–pocket interactions. Methods: An integrated in silico workflow was employed, comprising structure-based docking, 100-nanosecond molecular dynamics (MD) simulations, and MM-GBSA calculations. Benzoic-acid–based compounds were designed and prioritized for binding to the TRPC6 pocket, using a known literature agonist as a reference for benchmarking. Results: Within the compound series, BT11 was found to exhibit a representative interaction profile, characterized by a key hydrogen bond with Trp680 (~64% occupancy), persistent salt-bridge interactions with Lys676 and Lys698, and π–π stacking with Phe675 and Phe679. A favorable docking score (−11.45 kcal/mol) was obtained for BT11, along with a lower complex RMSD during MD simulations (0.6–4.8 Å), compared with the reference compound (0.8–7.2 Å). A reduction in solvent-accessible surface area (SASA) after ~60 ns was also observed, suggesting decreased water penetration. The most favorable binding energy was predicted for BT11 by MM-GBSA (−67.72 kcal/mol), while SOH95 also ranked highly and slightly outperformed the reference. Conclusions: These convergent computational analyses support the identification of benzoic-acid–derived chemotypes as potential TRPC6 ligands. Testable hypotheses are proposed, along with structure–activity relationship (SAR) guidelines, to inform experimental validation and guide the design of next-generation analogs.