In-silico screening to identify phytochemical inhibitor for hP2X7: A crucial inflammatory cell death mediator in Parkinson’s disease

IF 2.6 4区 生物学 Q2 BIOLOGY
Sabiya Khan , Dharmendra Kumar Khatri
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引用次数: 0

Abstract

The second most prevalent neurological disease among the elderly is Parkinson’s disease, where neuroinflammation plays a significant role in its pathology. Purinergic signaling mediated by P2X7 plays a significant role in neuroinflammation and pyroptotic cell death pathways through mediators like NLRP3, Caspase-1, and Caspase-3, instigating pyroptotic cell death. No synthetic agent advanced in late-stage clinical trials due to their inefficacy and toxicity. Hence, in this study, we aimed to identify a phytoconstituent inhibitor against the hP2X7 receptor to ameliorate the inflammatory processes involved. To achieve this aim, we performed homology modeling of the receptor and screened phytoconstituents from a library of over 3500 commercially available phytoconstituents. Molecular docking through the Maestro program of the Schrödinger suite was performed considering evaluation parameters like docking score, docking pose and spatial arrangement, and MMGBSA binding free energy. Predictive pharmacokinetic and toxicity profiling was done using tools like QikProp, ADMETLab 2.0, SwissADME, and Protox-II. Molecular dynamic simulation was performed using Schrödinger’s Desmond tool for the top 10 phytoconstituents. The complex stability was evaluated based on the ligand- and protein-RMSD, protein-ligand contact stability over a simulation period of 100 ns, protein RMSF, and ligand properties like RMSF, radius of gyration, intramolecular hydrogen bonding, and SASA. Based on the studies' results, silychristin, silybin, rosmarinic acid, nordihydroguaiaretic acid, and aurantiamide were shortlisted as the top 5 phytoconstituents against hP2X7. Further in-vitro and in-vivo studies would offer better clarity on the mechanism of action of these agents specifically related to pyroptotic cell death in various disease models.
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来源期刊
Computational Biology and Chemistry
Computational Biology and Chemistry 生物-计算机:跨学科应用
CiteScore
6.10
自引率
3.20%
发文量
142
审稿时长
24 days
期刊介绍: Computational Biology and Chemistry publishes original research papers and review articles in all areas of computational life sciences. High quality research contributions with a major computational component in the areas of nucleic acid and protein sequence research, molecular evolution, molecular genetics (functional genomics and proteomics), theory and practice of either biology-specific or chemical-biology-specific modeling, and structural biology of nucleic acids and proteins are particularly welcome. Exceptionally high quality research work in bioinformatics, systems biology, ecology, computational pharmacology, metabolism, biomedical engineering, epidemiology, and statistical genetics will also be considered. Given their inherent uncertainty, protein modeling and molecular docking studies should be thoroughly validated. In the absence of experimental results for validation, the use of molecular dynamics simulations along with detailed free energy calculations, for example, should be used as complementary techniques to support the major conclusions. Submissions of premature modeling exercises without additional biological insights will not be considered. Review articles will generally be commissioned by the editors and should not be submitted to the journal without explicit invitation. However prospective authors are welcome to send a brief (one to three pages) synopsis, which will be evaluated by the editors.
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