Articulating target-mining techniques to disinter Alzheimer's specific targets for drug repurposing. (July 2022)

• Record Type: Journal Article
• Authors: G N S, Hema Sree; Marise, V Lakshmi Prasanna; Rajalekshmi, Saraswathy Ganesan; Burri, Raghunadha R; Krishna Murthy, T.P.
• Is Part Of: Computer methods and programs in biomedicine. Volume 222(2022)
• Publication Date: 2022-07
• Subjects: Alzheimer's disease -- Target identification -- Drug repurposing -- RGS4 -- Molecular dynamics -- Homology modeling; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2022.106931
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: RGS4 downregulation in Alzheimer's disease was unveiled via GEO dataset analysis. Homology model was built for RGS4 through I-TASSER. Molecular dynamic simulations revealed good stability of the built model. Drug libraries were created for five literature derived potential RGS4 agonists. Ziprasidone, Melfoquine and Metaxalone exhibited good affinity towards RGS4. Abstract: Background and objectives: Alzheimer's Disease (AD), an extremely progressive neurodegenerative disorder is an amalgamation of numerous intricate pathological networks. This century old disease is still an unmet medical condition owing to the modest efficacy of existing therapeutic agents in antagonizing the multi-targeted pathological pathways underlying AD. Given the paucity in AD specific drugs, fabricating comprehensive research strategies to envision disease specific targets to channelize and expedite drug discovery are mandated. However, the dwindling approval rates and stringent regulatory constraints concerning the approval of a new chemical entity is daunting the pharmaceutical industries from effectuating de novo research. To bridge the existing gaps in AD drug research, a promising contemporary way out could be drug repurposing. This drug repurposing investigation is intended to envisage AD specific targets and create drug libraries pertinent to the shortlisted targets via a series of avant-garde bioinformatics and computational strategies. Methods: Transcriptomic analysis of three AD specific datasets viz., GSE122063, GSE15222 and GSE5281 revealed significant Differentially Expressed Genes (DEGs) and subsequent Protein-Protein Interactions (PPI) network analysis captured crucial AD targets. Later, homology model was constructed through I-TASSER for a shortlisted target protein which lacked X-ray crystallographic structure and the built protein model was validated by molecular dynamic simulations. Further, drug library was created for the shortlisted target based on structural and side effect similarity with respective standard drugs. Finally, molecular docking, binding energy calculations and molecular dynamics studies were carried out to unravel the interactions exhibited by drugs from the created library with amino acids in active binding pocket of RGS4. Results: SST and RGS4 were shortlisted as potentially significant AD specific targets, however, the less explored target RGS4 was considered for further sequential analysis. Homology model constructed for RGS4 displayed best quality when validated through Ramachandran plot and ERRAT plot. Subsequent docking and molecular dynamics studies showcased substantial affinity demonstrated by three drugs viz., Ziprasidone, Melfoquine and Metaxalone from the created drug libraries, towards RGS4. Conclusion: This virtual analysis forecasted the repurposable potential of Ziprasidone, Melfoquine and Metaxalone against AD based on their affinity towards RGS4, a key AD-specific target.