Structural Insight Into the Viral 3C-Like Protease Inhibitors: Comparative SAR/QSAR Approaches

New Short RNA Motifs Potentially Relevant in the SARS-CoV-2 Genome

Background

The coronavirus disease has led to an exhaustive exploration of the SARS-CoV-2 genome. Despite the amount of information accumulated, the prediction of short RNA motifs encoding peptides mediating protein-protein or protein-drug interactions has received limited attention.

Objective

The study aims to predict short RNA motifs that are interspersed in the SARS-CoV-2 genome.

Methods

A method in which 14 trinucleotide families, each characterized by being composed of triplets with identical nucleotides in all possible configurations, was used to find short peptides with biological relevance. The novelty of the approach lies in using these families to search how they are distributed across genomes of different CoV genera and then to compare the distributions of these families with each other.

Results

We identified distributions of trinucleotide families in different CoV genera and also how they are related, using a selection criterion that identified short RNA motifs. The motifs were reported to be conserved in SARS-CoVs; in the remaining CoV genomes analysed, motifs contained, exclusively, different configurations of the trinucleotides A, T, G and A, C, G. Eighty-eight short RNA motifs, ranging in length from 12 to 49 nucleotides, were found: 50 motifs in the 1a polyprotein-encoding orf, 27 in the 1b polyprotein-encoding orf, 5 in the spike-encoding orf, and 6 in the nucleocapsid-encoding orf. Although some motifs (~27%) were found to be intercalated or attached to functional peptides, most of them have not yet been associated with any known functions.

Conclusion

Some of the trinucleotide family distributions in different CoV genera are not random; they are present in short peptides that, in many cases, are intercalated or attached to functional sites of the proteome.

Natural Products as Potential Lead Compounds for Drug Discovery Against SARS-CoV-2

For the past 2 years, the coronavirus responsible for the COVID-19 infection has become a world pandemic, ruining the lives and economies of several nations in the world. This has scaled up research on the virus and the resulting infection with the goal of developing new vaccines and therapies. Natural products are known to be a rich source of lead compounds for drug discovery, including against infectious diseases caused by microbes (viruses, bacteria and fungi). In this review article, we conducted a literature survey aimed at identifying natural products with inhibitory concentrations against the coronaviruses or their target proteins, which lie below 10 µM. This led to the identification of 42 compounds belonging to the alkaloid, flavonoid, terpenoid, phenolic, xanthone and saponin classes. The cut off concentration of 10 µM was to limit the study to the most potent chemical entities, which could be developed into therapies against the viral infection to make a contribution towards limiting the spread of the disease.

Robust classification-based molecular modelling of diverse chemical entities as potential SARS-CoV-2 3CLpro inhibitors: theoretical justification in light of experimental evidences

COVID-19 is the most unanticipated incidence of 2020 affecting the human population worldwide. Currently, it is utmost important to produce novel small molecule anti-SARS-CoV-2 drugs urgently that can save human lives globally. Based on the earlier SARS-CoV and MERS-CoV infection along with the general characters of coronaviral replication, a number of drug molecules have been proposed. However, one of the major limitations is the lack of experimental observations with different drug molecules. In this article, 70 diverse chemicals having experimental SARS-CoV-2 3CL^proinhibitory activity were accounted for robust classification-based QSAR analysis statistically validated with 4 different methodologies to recognize the crucial structural features responsible for imparting the activity. Results obtained from all these methodologies supported and validated each other. Important observations obtained from these analyses were also justified with the ligand-bound crystal structure of SARS-CoV-2 3CL^pro enzyme. Our results suggest that molecules should contain a 2-oxopyrrolidine scaffold as well as a methylene (hydroxy) sulphonic acid warhead in proper orientation to achieve higher inhibitory potency against SARS-CoV-2 3CL^pro. Outcomes of our study may be able to design and discover highly effective SARS-CoV-2 3CL^pro inhibitors as potential anticoronaviral therapy to crusade against COVID-19.

Virtual Screening and Molecular Design of Potential SARS-COV-2 Inhibitors

According to recent studies, the main M^pro protease of the SARS-CoV-2 virus, which is the most important target in the development of promising drugs for the treatment of COVID-19, is evolutionarily conservative and has not undergone significant changes compared with the main M^pro protease of the SARS-CoV virus. Many researchers note the similarity between the binding sites of the main M^pro protease of SARS-CoV and SARS-CoV-2 viruses; thus, with the spreading epidemic, further studies on inhibitors of the main M^pro protease of the SARS-CoV virus to fight COVID-19 seems logical. In the course of the study, satisfactory QSAR models are built using simplex, fractal, and HYBOT descriptors; the Partial Least Squares (PLS), Random Forest (RF), Support Vectors, Gradient Boosting (GBM) methods; and the OCHEM Internet platform (https://ochem.eu), in which different types of molecular descriptors and machine learning methods are implemented. The structural interpretation, which allowed us to identify molecular fragments that increase and decrease the activity of SARS-CoV inhibitors, is performed for the obtained models. The results of the structural interpretation are used for the rational molecular design of potential SARS-CoV-2 inhibitors. The resulting QSAR models are used for the virtual screening of 2087 FDA-approved drugs.

Biflavonoid as potential 3-chymotrypsin-like protease (3CLpro) inhibitor of SARS-Coronavirus

3CL protease is one of the key proteins expressed by SARS-Coronavirus-2 cell, the potential to be targeted in the discovery of antivirus during this COVID-19 pandemic. This protein regulates the proteolysis of viral polypeptide essential in forming RNA virus. 3CL protease (3CLpro) was commonly targeted in the previous SARS-Coronavirus including bat and MERS, hence, by blocking this protein activity, the coronavirus should be eradicated. This study aims to review the potency of biflavonoid as the SARS-Coronavirus-2 3CLpro inhibitor. The review was initiated by describing the chemical structure of biflavonoid and followed by listing its natural source. Instead, the synthetic pathway of biflavonoid was also elaborated. The 3CLpro structure and its function were also illustrated followed by the list of its 3D-crystal structure available in a protein data bank. Lastly, the pharmacophores of biflavonoid have been identified as a protease inhibitor, was also discussed. This review hopefully will help researchers to obtain packed information about biflavonoid which could lead to the study in designing and discovering a novel SARS-Coronavirus-2 drug by targetting the 3CLpro enzyme.

Chemical-informatics approach to COVID-19 drug discovery: Monte Carlo based QSAR, virtual screening and molecular docking study of some in-house molecules as papain-like protease (PLpro) inhibitors

World Health Organization characterized novel coronavirus disease (COVID-19), caused by severe acute respiratory syndrome (SARS) coronavirus-2 (SARS-CoV-2) as world pandemic. This infection has been spreading alarmingly by causing huge social and economic disruption. In order to response quickly, the inhibitors already designed against different targets of previous human coronavirus infections will be a great starting point for anti-SARS-CoV-2 inhibitors. In this study, our approach integrates different ligand based drug design strategies of some in-house chemicals. The study design was composed of some major aspects: (a) classification QSAR based data mining of diverse SARS-CoV papain-like protease (PLpro) inhibitors, (b) QSAR based virtual screening (VS) to identify in-house molecules that could be effective against putative target SARS-CoV PLpro and (c) finally validation of hits through receptor-ligand interaction analysis. This approach could be used to aid in the process of COVID-19 drug discovery. It will introduce key concepts, set the stage for QSAR based screening of active molecules against putative SARS-CoV-2 PLpro enzyme. Moreover, the QSAR models reported here would be of further use to screen large database. This study will assume that the reader is approaching the field of QSAR and molecular docking based drug discovery against SARS-CoV-2 PLpro with little prior knowledge.

Communicated by Ramaswamy H. Sarma