Glycyrrhizin as a promising kryptonite against SARS-CoV-2: Clinical, experimental, and theoretical evidences.

COVID-19 is the most devastating disease in recent times affecting most people globally. The higher rate of transmissibility and mutations of SARS-CoV-2 along with the lack of potential therapeutics has made it a global crisis. Potential molecules from natural sources could be a fruitful remedy to combat COVID-19. This systematic review highlights the detailed therapeutic implication of naturally occurring glycyrrhizin and its related derivatives against COVID-19. Glycyrrhizin has already been established for blocking different biomolecular targets related to the SARS-CoV-2 replication cycle. In this article, several experimental and theoretical evidences of glycyrrhizin and related derivatives have been discussed in detail to evaluate their potential as a promising therapeutic strategy against COVID-19. Moreover, the implication of glycyrrhizin in traditional Chinese medicines for alleviating the symptoms of COVID-19 has been reviewed. The potential role of glycyrrhizin and related compounds in affecting various stages of the SARS-CoV-2 life cycle has also been discussed in detail. Derivatization of glycyrrhizin for designing potential lead compounds along with combination therapy with other anti-SARS-CoV-2 agents followed by extensive evaluation may assist in the formulation of novel anti-coronaviral therapy for better treatment to combat COVID-19.

Ligand-based quantitative structural assessments of SARS-CoV-2 3CLpro inhibitors: An analysis in light of structure-based multi-molecular modeling evidences.

Due to COVID-19, the whole world is undergoing a devastating situation, but treatment with no such drug candidates still has been established exclusively. In that context, 69 diverse chemicals with potential SARS-CoV-2 3CLpro inhibitory property were taken into consideration for building different internally and externally validated linear (SW-MLR and GA-MLR), non-linear (ANN and SVM) QSAR, and HQSAR models to identify important structural and physicochemical characters required for SARS-CoV-2 3CLpro inhibition. Importantly, 2-oxopyrrolidinyl methyl and benzylester functions, and methylene (hydroxy) sulphonic acid warhead group, were crucial for retaining higher SARS-CoV-2 3CLpro inhibition. These GA-MLR and HQSAR models were also applied to predict some already repurposed drugs. As per the GA-MLR model, curcumin, ribavirin, saquinavir, sepimostat, and remdesivir were found to be the potent ones, whereas according to the HQSAR model, lurasidone, saquinavir, lopinavir, elbasvir, and paritaprevir were the highly effective SARS-CoV-2 3CLpro inhibitors. The binding modes of those repurposed drugs were also justified by the molecular docking, molecular dynamics (MD) simulation, and binding energy calculations conducted by several groups of researchers. This current work, therefore, may be able to find out important structural parameters to accelerate the COVID-19 drug discovery processes in the future.

Unmasking of crucial structural fragments for coronavirus protease inhibitors and its implications in COVID-19 drug discovery.

Fragment based drug discovery (FBDD) by the aid of different modelling techniques have been emerged as a key drug discovery tool in the area of pharmaceutical science and technology. The merits of employing these methods, in place of other conventional molecular modelling techniques, endorsed clear detection of the possible structural fragments present in diverse set of investigated compounds and can create alternate possibilities of lead optimization in drug discovery. In this work, two fragment identification tools namely SARpy and Laplacian-corrected Bayesian analysis were used for previous SARS-CoV PLpro and 3CLpro inhibitors. A robust and predictive SARpy based fragments identification was performed which have been validated further by Laplacian-corrected Bayesian model. These comprehensive approaches have advantages since fragments are straight forward to interpret. Moreover, distinguishing the key molecular features (with respect to ECFP_6 fingerprint) revealed good or bad influences for the SARS-CoV protease inhibitory activities. Furthermore, the identified fragments could be implemented in the medicinal chemistry endeavors of COVID-19 drug discovery.

Exploring naphthyl derivatives as SARS-CoV papain-like protease (PLpro) inhibitors and its implications in COVID-19 drug discovery.

Novel coronavirus disease 2019 (COVID-19) emerges as a serious threat to public health globally. The rapid spreading of COVID-19, caused by severe acute respiratory syndrome (SARS) coronavirus 2 (SARS-CoV-2), proclaimed the multitude of applied research needed not only to save the human health but also for the environmental safety. As per the recent World Health Organization reports, the novel corona virus may never be wiped out completely from the world. In this connection, the inhibitors already designed against different targets of previous human coronavirus (HCoV) infections will be a great starting point for further optimization. Pinpointing biochemical events censorious to the HCoV lifecycle has provided two proteases: a papain-like protease (PLpro) and a 3C-like protease (3CLpro) enzyme essential for viral replication. In this study, naphthyl derivatives inhibiting PLpro enzyme were subjected to robust molecular modelling approaches to understand different structural fingerprints important for the inhibition. Here, we cover two main aspects such as (a) exploration of naphthyl derivatives by classification QSAR analyses to find important fingerprints that module the SARS-CoV PLpro inhibition and (b) implications of naphthyl derivatives against SARS-CoV-2 PLpro enzyme through detailed ligand-receptor interaction analysis. The modelling insights will help in the speedy design of potent broad spectrum PLpro inhibitors against infectious SARS-CoV and SARS-CoV-2 in the future.

Protease targeted COVID-19 drug discovery: What we have learned from the past SARS-CoV inhibitors?

The fascinating similarity between the SARS-CoV and SARS-CoV-2, inspires scientific community to investigate deeper into the SARS-CoV proteases such as main protease (Mpro) and papain-like protease (PLpro) and their inhibitors for the discovery of SARS-CoV-2 protease inhibitors. Because of the similarity in the proteases of these two corona viruses, there is a greater chance for the previous SARS-CoV Mpro and PLpro inhibitors to provide effective results against SARS-CoV-2. In this context, the molecular fragments from the SARS-CoV protease inhibitors through the fragment-based drug design and discovery technique can be useful guidance for COVID-19 drug discovery. Here, we have focused on the structure-activity relationship studies of previous SARS-CoV protease inhibitors and discussed about crucial fragments generated from previous SARS-CoV protease inhibitors important for the lead optimization of SARS-CoV-2 protease inhibitors. This study surely offers different strategic options of lead optimization to the medicinal chemists to discover effective anti-viral agent against the devastating disease, COVID-19.

Molecular dynamics analysis of phytochemicals from Ageratina adenophora against COVID-19 main protease (Mpro) and human angiotensin-converting enzyme 2 (ACE2).

The outbreak of COVID-19 created unprecedented strain in the healthcare system. Various research revealed that COVID-19 main protease (Mpro) and human angiotensin-converting enzyme 2 (ACE2) are responsible for viral replication and entry into the human body, respectively. Blocking the activity of these enzymes gives a potential therapeutic target for the COVID-19. The objective of the study was to explore phytochemicals from Ageratina adenophora against SARS-CoV-2 through in-silico studies. In this study, 34 phytochemicals of A. adenophora were docked with Mpro and ACE2 through AutoDock Tools-1.5.6 and their binding affinity was studied. Phytochemicals with higher affinity have been chosen for further molecular dynamics simulations to determine the stability with target protein. Molecular dynamics simulations were studied on GROMACS 5.1.4 version. Furthermore, 5-ß-glucosyl-7-demethoxy-encecalin (5GDE) and 2-oxocadinan-3,6(11)-dien-12,7-olide (BODO) were found to be potential blockers with excellent binding affinity with Mpro and ACE2 than their native inhibitors remdesivir and hydroxychloroquine respectively. The drug likeness study and pharmacokinetics of the phytoconstituents present in A. adenophora provide an excellent support for the lead drug discovery against COVID-19.

Protease targeted COVID-19 drug discovery and its challenges: Insight into viral main protease (Mpro) and papain-like protease (PLpro) inhibitors.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) brutally perils physical and mental health worldwide. Unavailability of effective anti-viral drug rendering global threat of COVID-19 caused by SARS-CoV-2. In this scenario, viral protease enzymes are crucial targets for drug discovery. This extensive study meticulously focused on two viral proteases such as main protease (Mpro) and papain-like protease (PLpro), those are essential for viral replication. This review provides a detail overview of the targets (Mpro and PLpro) from a structural and medicinal chemistry point of view, together with recently reported protease inhibitors. An insight into the challenges in the development of effective as well as drug like protease inhibitors is discussed. Peptidomimetic and/or covalent coronavirus protease inhibitors possessed potent and selective active site inhibition but compromised in pharmacokinetic parameters to be a drug/drug like molecule. Lead optimization of non-peptidomimetic and/or low molecular weight compounds may be a better option for oral delivery. A masterly combination of adequate pharmacokinetic properties with coronavirus protease activity as well as selectivity will provide potential drug candidates in future. This study is a part of our endeavors which surely dictates medicinal chemistry efforts to discover effective anti-viral agent for this devastating disease.

First structure-activity relationship analysis of SARS-CoV-2 virus main protease (Mpro) inhibitors: an endeavor on COVID-19 drug discovery.

Main protease (Mpro) of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) intervenes in the replication and transcription processes of the virus. Hence, it is a lucrative target for anti-viral drug development. In this study, molecular modeling analyses were performed on the structure activity data of recently reported diverse SARS-CoV-2 Mpro inhibitors to understand the structural requirements for higher inhibitory activity. The classification-based quantitative structure-activity relationship (QSAR) models were generated between SARS-CoV-2 Mpro inhibitory activities and different descriptors. Identification of structural fingerprints to increase or decrease in the inhibitory activity was mapped for possible inclusion/exclusion of these fingerprints in the lead optimization process. Challenges in ADME properties of protease inhibitors were also discussed to overcome the problems of oral bioavailability. Further, depending on the modeling results, we have proposed novel as well as potent SARS-CoV-2 Mpro inhibitors.

Chemical-informatics approach to COVID-19 drug discovery: Exploration of important fragments and data mining based prediction of some hits from natural origins as main protease (Mpro) inhibitors.

As the world struggles against current global pandemic of novel coronavirus disease (COVID-19), it is challenging to trigger drug discovery efforts to search broad-spectrum antiviral agents. Thus, there is a need of strong and sustainable global collaborative works especially in terms of new and existing data analysis and sharing which will join the dots of knowledge gap. Our present chemical-informatics based data analysis approach is an attempt of application of previous activity data of SARS-CoV main protease (Mpro) inhibitors to accelerate the search of present SARS-CoV-2 Mpro inhibitors. The study design was composed of three major aspects: (1) classification QSAR based data mining of diverse SARS-CoV Mpro inhibitors, (2) identification of favourable and/or unfavourable molecular features/fingerprints/substructures regulating the Mpro inhibitory properties, (3) data mining based prediction to validate recently reported virtual hits from natural origin against SARS-CoV-2 Mpro enzyme. Our Structural and physico-chemical interpretation (SPCI) analysis suggested that heterocyclic nucleus like diazole, furan and pyridine have clear positive contribution while, thiophen, thiazole and pyrimidine may exhibit negative contribution to the SARS-CoV Mpro inhibition. Several Monte Carlo optimization based QSAR models were developed and the best model was used for screening of some natural product hits from recent publications. The resulted active molecules were analysed further from the aspects of fragment analysis. This approach set a stage for fragment exploration and QSAR based screening of active molecules against putative SARS-CoV-2 Mpro enzyme. We believe the future in vitro and in vivo studies would provide more perspectives for anti-SARS-CoV-2 agents.

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.

Fight against novel coronavirus: A perspective of medicinal chemists.

The ongoing novel coronavirus disease (COVID-19) pandemic makes us painfully perceive that our bullet shells are blank so far for fighting against severe human coronavirus (HCoV). In spite of vast research work, it is crystal clear that the evident does not warrant the commercial blossoming of anti-HCoV drugs. In this circumstance, drug repurposing and/or screening of databases are the only fastest option. This study is an initiative to recapitulate the medicinal chemistry of severe acute respiratory syndrome (SARS)-CoV-2 (SARS-CoV-2). The aim is to present an exquisite delineation of the current research from the perspective of a medicinal chemist to allow the rapid development of anti-SARS-CoV-2 agents.