Identification of differentially expressed genes and drug targets in duchenne muscular dystrophy using in silico approach with RNA-Seq analysis and molecular dynamics simulations

Abstract

Duchenne muscular dystrophy (DMD), is the most severe because mutation of dystrophin gene damages skeletal and cardiac muscles. Combining the results of RNA-Seq on 4 GEO data sets, we searched for DEGs related to DMD with the condition of logFC2.5 and P< 0.05. There were 10 hub genes in the PPI network: ACTN2, TNNT1, MYL4, TTN, TNNI2, MYH7, NEB, TPM1, CSRP3, and TCAP; it may play an important role in DMD. Molecular docking of ten phytochemical against these DMD hub proteins identified five complexes 4DB1-Mn-amppnp (-9.9 kcal/mol), 2X4F-BMN-195 (-9.5 kcal/mol), 2JT0-BMN-195 (-9.1 kcal/mol), 8EFH-NG25 (-9 kcal/mol), and 7KAA5-NG25 (-8.8 kcal/mol) with favorable binding energies. The top 5 complexes stability and dynamic behavior were checked further by RMSD, RMSF, H-bond, Radius of Gyration using MD for 100ns. Based on RNA-Seq, network analysis, Docking and MD simulation approach is providing the framework for further experimental investigation and insight in to prospective therapeutic molecules for the treatment of DMD.