Lassa fever is an animal-borne, or zoonotic, acute viral hemorrhagic illness caused by Lassa virus, a member of the arenavirus family of viruses. There is currently no licensed vaccine for Lassa fever, but several potential vaccines are in development. However, there is still a need for a safe treatment with proven efficacy and a range of potential treatments. In both viral RNA synthesis and immunological suppression, the Lassa virus' nucleoprotein (NP) plays a crucial roles. An arenaviral NP that demonstrates surprising capabilities and suggests particular mechanisms for immune evasion and cap binding. These discoveries have a lot of potential for therapeutic development. Based on chemoinformatics approach, we focused on designing a computational drug for the targeting of viral nucleoprotein of human pathogenic Lassa fever virus. We accomplished several vital steps including target protein and ligand identification and refinement, active site analysis, ADMET analysis, molecular docking, protein-ligand interaction analysis, etc. We retrieved Lassa viral nucleoprotein receptor from widely used RSCB PDB website as well as control ligand molecules includings Arbidol, Ribavirin, Favipiravir, UTP (Uridine 5'-Triphosphate) from significant chemical database Pubchem. ADMET property analysis by SwissAdme and pkCSM server, molecular docking study done by PyRx virtual screening tools, and Discovery studio used for further protein-ligand interaction analysis. We found a very significant molecular binding affinity score that promises the designed drug is more stable and reliable. However, it will demand to be considered considerably in vivo and in vitro experimental drug design models.
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Pharmacoinformatics based drug design for the blocking of deadly nucleoprotein of Lassa pathogenic virus.
Published:
15 November 2023
by MDPI
in The 27th International Electronic Conference on Synthetic Organic Chemistry
session Computational Chemistry
https://doi.org/10.3390/ecsoc-27-16063
(registering DOI)
Abstract:
Keywords: Lassa virus; Viral nucleoprotein; Molecular Docking; In Silico drug design; Pharmacoinformatics