Journal of Chemical and Pharmaceutical Research (ISSN : 0975-7384)

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Original Articles: 2023 Vol: 15 Issue: 1

Computational Analysis for SARS Coronavirus and Pharmacoinformatics

Simonai Trinopy*

Department of Pharmacy, Sapienza University of Rome, Rome, Italy

Corresponding Author:
Simonai Trinopy
Department of Pharmacy, Sapienza University of Rome, Rome, Italy

Received: 06-Jan-2023, Manuscript No. JOCPR-23-87629; Editor assigned: 09-Jan-2023, PreQC No. JOCPR-23-87629(PQ); Reviewed: 23-Jan-2023, QC No. JOCPR-23-87629; Revised: 30-Jan-2023, Manuscript No. JOCPR-23-87629 (R); Published: 07-Feb-2023, DOI:10.37532/0975-7384.2023.15(1).50.



Due to difficulties surrounding current vaccinations, the hunt for effective therapy against new coronavirus (COVID-19) remains a global problem. The chembl database was used to gather data on SARS coronavirus 3C-Like Protease (3CLpro) inhibitors, a significant therapeutic target in the coronavirus genome. These 3CLpro inhibitors were used in Quantitative Structure-activity Relationship (QSAR) research, molecular docking, Absorption-Distribution-Metabolism-Excretion-Toxicity (ADMET), and molecular Dynamics Simulation (MDS). The data-driven QSAR model exhibited a correlation coefficient R2 of 0.907, a cross-validated correlation coefficient Q2 of 0.866, and a test set predicted correlation coefficient R2pred of 0.517. The Variance Inflation Factor (VIF) values for the model's descriptors ranged from 1.352 to 1.68, indicating that these descriptors were orthogonal to one another. As a result, the model proved statistically significant, and it may be used to screen and develop novel compounds for 3CLpro inhibitory action. Molecular docking revealed that seven of the compounds (inhibitors) utilised in the study exhibited a high affinity for 3CLpro (9.2 to 10.3 kcal/mol). The ADMET investigation demonstrated that five of the seven compounds with strong binding capacity (CHEMBL Accession IDs 19438, 196635, 377150, 208763, and 210097) followed Lipinski's rule of five. As a result, they have drug-like qualities. MDS analysis demonstrated that the complexes 3CLpro-compound 21, 3CLpro-compound 22, and 3CLpro-compound 40 are much more stable than the reference 3CLpro-X77 complex. As a result, our investigation found three strong 3CLpro inhibitors, CHEMBL194398, CHEMBL196635, and CHEMBL210097, which might be further investigated for the therapy of COVID-19. Coronavirus has recently resurfaced in the Wuhan region of China as a new coronavirus (CoVID-19) causing severe upper respiratory tract infection with symptoms such as fever, pneumonia, dyspnea, and asthenia, as reported by Wuhan residents. Since then, the virus has spread to practically every country in the world, causing governments to implement a number of lockdown measures in order to halt the spread of this sickness. Despite increased focus on vaccine research to reduce daily mortality, all efforts to date have been futile, with over 98.2 million reported illnesses and over 2.1 million fatalities globally.

Coronavirus is a positive-stranded RNA virus with the biggest genome of any known RNA virus, measuring around 26-32 kb. The coronavirus genome encodes four structural proteins that are required for the generation of a physically complete viral particle: the spike (S) protein, the nucleocapsid (N) protein, the membrane (M) protein, and the envelope (E) protein. A major portion of the coronavirus genome is transcribed and translated into a polypeptide, which encodes proteins required for viral replication and gene expression. The chymotrypsin-like protease is one of the best-studied therapeutic targets for coronaviruses (3CLpro). 3CLpro, in collaboration with the Papain-Like Protease (PLpro), is essential for digesting the translated polyproteins from viral RNA. The highly conserved 3CLpro enzyme, which has roughly 306 amino acids, is essential for coronavirus replication. As a result, it is a critical target for the Vaccine development against coronavirus.

The creation and development of pharmacological drugs for the prevention of coronavirus infections is critical in our world, and scientists are working tirelessly to achieve this goal. To that end, scientists are employing classic ways of acquiring novel medications, such as screening a large number of chemicals (either manufactured or extracted phytochemical agents) in non-living or simplified living systems, such as rats, until a viable lead is discovered. These procedures are the judge of truth in any scientific study, but they are time-consuming and expensive. Any process that can help save costs and time while maintaining scientific integrity is a good improvement. This is when computer-aided drug design approaches (quantitative structure-based design) come into play. QSAR, molecular docking, molecular dynamics modelling, and other techniques are used.


QSAR develops a mathematical link between the chemical structures of substances with known biological activities and their activities. This connection may be used to screen for and build novel compounds with improved biological activity. QSAR is a powerful technique for improving or connecting certain structural traits or molecular descriptors such as polarizability, lipophilicity, electronic and steric properties within a sequence of compounds with their biological activities. Furthermore, molecular docking clarifies the interaction of tiny substances (drugs or ligands) with a known macromolecular target (receptor). In this work, chemical compounds with inhibitory action against 3C-like protease that were deposited in the CHEMBL database were utilised to create a QSAR model. This will disclose the structural aspect of the molecules responsible for their inhibitory function. Furthermore, molecular docking was used to demonstrate the interaction of the chemicals and amino acids in the binding pocket of 3CLpro. To test the stability of the lead compounds, the compounds with the highest negative binding affinity were submitted to ADMET investigations followed by a 100 ns molecular dynamics simulation.