Bioinformatics-Driven Structural and Pharmacological Analysis of SLITRK1 in Tourette Syndrome: Impact of S656M Mutation Using Molecular Dynamics, Docking, and Reinforcement Learning

Abstract

SLITRK1 is a critical protein involved in neural development and is associated with various neurological disorders, including Tourette Syndrome. This study investigates the structural dynamics, intrinsic disorder propensity, and pharmacological interactions of SLITRK1, with a particular focus on amino acid substitutions and their pathological implications. A comprehensive computational framework was employed, including intrinsic disorder region analysis, transmembrane topology predictions, and stability assessments of SLITRK1 variants. Integrated with reinforcement learning (RL), molecular docking and dynamics simulations were used to evaluate the pharmacotherapeutic potential of drugs commonly prescribed for Tourette Syndrome, such as Pimozide, Aripiprazole, Risperidone, and Haloperidol. Structural analyses revealed that the S656M mutation significantly alters SLITRK1's 3D conformation, biological functions, and drug binding profiles. Among the tested drugs, Aripiprazole exhibited the highest binding affinity across various SLITRK1 variants, with reinforcement learning highlighting a notable interaction with the S659K mutation. These findings were supported by Ramachandran plot and molecular dynamics analyses, which identified mutation-induced structural and dynamic changes. This study provides an integrative analysis of SLITRK1, offering insights into its role in Tourette Syndrome and laying a foundation for targeted therapeutic strategies to mitigate SLITRK1-related neurological disorders.