Abstract
Background: Amyotrophic lateral sclerosis (ALS) is an uncommon and progressive neurological illness that predominantly includes the neurons liable for voluntary muscular activities. Starting from weakness or stiffness in muscles, this gradually exploits the strength and ability to speak, eat, move, and even breathe. Its exact mechanism is still not clear, but mutations in the SOD1 gene have been reported to cause ALS, and some studies also found involvement of SOD1 overexpression in the pathogenesis of ALS. As of now, there is no remedy available for its cure.
Objective: The objective of this study is to identify the potential inhibitors for wild type 1HL5, l113T mutant, and A4V mutant of SOD1 (Superoxide Dismutase 1) protein.
Methods: In this study, in silico approaches like virtual screening, molecular docking, pharmacokinetic parameters study, and molecular dynamics simulation were used to identify the best potential inhibitors against wild type and mutant SOD1 protein.
Results: On the basis of binding affinity and binding energy, the top three compounds ZINC000095486263, ZINC000095485989, and ZINC000028462577 were observed as the best compounds. In the case of 1HL5, ZINC000095486263 had the highest binding affinity with docking score - 10.62 Kcal/mol, 1UXM with ZINC000095485989 had the highest docking score -12.03 Kcal/mol, and 4A7V with ZINC000028462577 was found -11.72 Kcal/mol. Further, Molecular Dynamic Simulations (MDS) results showed that the ZINC000095486263, ZINC000095485989, and ZINC000095485956 compounds were formed a stable complex with 1HL5, 1UXM, and 4A7V respectively.
Conclusion: After analyzing the results, we hereby conclude that natural compounds such as ZINC000095486263, ZINC000095485989, and ZINC000095485956 could be used as a potential inhibitor of 1HL5, 1UXM, and 4A7V respectively for ALS treatment and could be used as a drug. Further, In vivo/vitro study of these compounds could be a future direction in the field of drug discovery.
Keywords: Virtual Screening, neurodegenerative disease, molecular docking, ADMET, molecular dynamic simulation, amyotrophic lateral sclerosis
Graphical Abstract
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