Computational Screening of Lichen Derived Biopotents as an Antiviral Drug Against Infectious Proteins of SARS CoV-2

SARS CoV-2 is a contagious disease which emerged as a global pandemic causing several deaths. The current research aims to unveil the novel antiviral drug design utilising the authentic natural bioactives derived from lichens, as there is a demand for natural drug than synthetic since it triggers the adverse conditions on human health. The ten core proteins causing infection such as Spike proteins, Main Protease and Glycoproteins were targeted for suppressing the replicating process in virus. Insilico screening have been performed to analyze the linkage of SARS protein against seven lichen compounds L (1-7) (Methyl-γ-oresellinate, Roccellatol, Atranorin, Usnic acid, Oresellinate, 2-Hydroxy- [1], [4] naphthoquinone and N-Benzoyl-2-hydroxy-benzamide) through docking. The docked scores reveals the higher binding affinity of 5RE9 with L-7 (-8.2), L-3&4 (-8.1) and 5REA with L4 (-8), L-3 (-8.1) proves that the natural ligand compounds are effective than the standard drug. The Drug likeness and Pharmacokinetic factors of the compounds had been validated through SWISS ADME tool which satisified the criteria with bioavailabilty score (0.55), indicating favourable characteristics for a drug candidate. These results exemplifies that the naturally derived lichen compounds could be a better alternative Pharmaceuticals for SARS CoV-2 than the synthetic medicines.

Authors

Publication Details

Published
2025-04-29
DOI
https://doi.org/10.1109/aimla63829.2025.11040652
Primary Topic
Lichen and fungal ecology
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Computational Screening of Lichen Derived Biopotents as an Antiviral Drug Against Infectious Proteins of SARS CoV-2

Syed Zameer Ahmed Khader, Preethi Rajan, Sidhra Syed Zameer Ahmed, P. Saravanan et al.
Lichen and fungal ecology
article

Computational Screening of Lichen Derived Biopotents as an Antiviral Drug Against Infectious Proteins of SARS CoV-2

Syed Zameer Ahmed Khader, Preethi Rajan, Sidhra Syed Zameer Ahmed, P. Saravanan, M. Muthukumar, Moovin Sugavaneswaran
article en

Abstract

SARS CoV-2 is a contagious disease which emerged as a global pandemic causing several deaths. The current research aims to unveil the novel antiviral drug design utilising the authentic natural bioactives derived from lichens, as there is a demand for natural drug than synthetic since it triggers the adverse conditions on human health. The ten core proteins causing infection such as Spike proteins, Main Protease and Glycoproteins were targeted for suppressing the replicating process in virus. Insilico screening have been performed to analyze the linkage of SARS protein against seven lichen compounds L (1-7) (Methyl-γ-oresellinate, Roccellatol, Atranorin, Usnic acid, Oresellinate, 2-Hydroxy- [1], [4] naphthoquinone and N-Benzoyl-2-hydroxy-benzamide) through docking. The docked scores reveals the higher binding affinity of 5RE9 with L-7 (-8.2), L-3&4 (-8.1) and 5REA with L4 (-8), L-3 (-8.1) proves that the natural ligand compounds are effective than the standard drug. The Drug likeness and Pharmacokinetic factors of the compounds had been validated through SWISS ADME tool which satisified the criteria with bioavailabilty score (0.55), indicating favourable characteristics for a drug candidate. These results exemplifies that the naturally derived lichen compounds could be a better alternative Pharmaceuticals for SARS CoV-2 than the synthetic medicines.

Good health and well-being
Openalex Percentile: Top 88%
Lichen and fungal ecology
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.