An Integrated Network Biology and Molecular Dynamics Approach Identifies CD44 as a Promising Therapeutic Target in Multiple Sclerosis

TL;DR

This study uses network biology and molecular simulations to identify CD44 as a potential treatment target for multiple sclerosis, with Obeticholic acid showing strong binding potential.

Contribution

The novel integration of network-based gene profiling and molecular dynamics simulations identifies CD44 as a therapeutic target in MS.

Findings

CD44 had the highest degree score (15) among differentially expressed genes in MS.

Obeticholic acid showed the best docking score (-6.3 kcal/mol) and stability in MD simulations.

MD simulations confirmed structural stability and flexibility consistency for Obeticholic acid.

Abstract

Background: Multiple sclerosis (MS) is a neuroinflammatory disease characterized by autoimmune-driven inflammation in the central nervous system that damages axons and destroys myelin. It is difficult to diagnose multiple sclerosis due to its complexity, and different people may react differently to different treatments. While the exact cause of multiple sclerosis (MS) and the reasons for its increasing prevalence remain unclear, it is widely believed that a combination of genetic predisposition and environmental influences plays a significant role. Methods: Finding biomarkers for complicated diseases like multiple sclerosis (MS) is made more promising by the emergence of network and system biology technologies. Currently, using tools like Network Analyst to apply network-based gene expression profiling provides a novel approach to finding potential medication targets followed by molecular docking and MD Simulations. Results: There were 1200 genes found to be differentially expressed, with CD44 showing the highest degree score of 15, followed by CDC42 and SNAP25 genes, each with a degree score of 14. To explore the regulatory kinases involved in the protein–protein interaction network, we utilized the X2K online tool. The present study examines the binding interactions and the dynamic stability of four ligands (Obeticholic acid, Chlordiazepoxide, Dextromethorphan, and Hyaluronic acid) in the Hyaluronan binding site of the human CD44 receptor using molecular docking and molecular dynamics (MD) simulations. Docking studies demonstrated a significant docking score for Obeticholic acid (−6.3 kcal/mol), underscoring its medicinal potential. MD simulations conducted over a 100 ns period corroborated these results, revealing negligible structural aberrations (RMSD 1.3 Å) and consistent residue flexibility (RMSF 0.7 Å). Comparative examinations of RMSD, RMSF, Rg, and β-factor indicated that Obeticholic acid exhibited enhanced stability and compactness, establishing it as the most promising choice. Conclusions: This integrated method underscores the significance of dynamic validations for dependable drug design aimed at CD44 receptor-mediated pathways. Future experimental techniques are anticipated to further hone these findings, which further advance our understanding of putative biomarkers in multiple sclerosis (MS).

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