Investigating small molecule compounds targeting psoriasis based on cMAP database and molecular dynamics simulation

OBJECTIVE: Psoriasis (PSO) is a chronic inflammatory skin disease that severely affects the physical and mental health of patients. Drug resistance has been developed upon current drug treatments, and there is no specific therapy. The aim of this study was to screen promising novel drug candidates for PSO using molecular dynamics (MD) simulations. METHODS: The data of PSO were downloaded from gene expression omnibus (GEO) database and subjected to variance analysis. Target proteins and small molecule compounds targeting PSO were predicted in the connective map (cMAP) database. Molecular docking, MD simulation, and trajectory analysis were conducted to predict the binding of target proteins to compounds. RESULTS: 1999 differentially expressed genes in PSO were obtained by differential analysis. Through cMAP database prediction, a low Score value of −45.69 for lymphocyte cell‐specific protein‐tyrosine kinase (LCK) was revealed, and aminogenistein was identified as the compound targeting LCK, and LCK was notably highly expressed in the PSO samples. The drugScore of the binding pocket P_0 was 0.814656, which was docked with aminogenistein. The results showed that there were more than one binding site between LCK and aminogenistein with binding energy less than −7.0 kJ/mol, and the docking was relatively stable. The results of root‐mean‐square deviation (RMSD), root‐mean‐square fluctuation (RMSF), Gyrate, number of hydrogen bonds and total free binding energy in MD simulations showed that the binding of aminogenistein to LCK was relatively solid. CONCLUSION: Aminogenistein has good protein‐ligand interaction and stability with LCK, a target of PSO, and is a novel drug candidate for PSO.