In silico approach for identifying natural lead molecules against SARS-COV-2

Computational approach based on freely accessible tools for antimicrobial drug design

Antimicrobial drug development is crucial for public health, especially with the emergence of pandemics and drug resistance that prompts the search for new therapeutic resources. In this context, in silico assays consist of a valuable approach in the rational drug design because they enable a faster and more cost-effective identification of drug candidates compared to in vitro screening. However, once a potential drug is identified, in vitro and in vivo assays are essential to verify the expected activity of the compound and advance it through the subsequent stages of drug development. This work aims to outline an in silico protocol that utilizes only freely available computational tools for identifying new potential antimicrobial agents, which is also suitable in the broad spectrum of drug design. Additionally, this paper reviews relevant computational methods in this context and provides a summary of information concerning the protein-ligand interaction.

Essential oil constituents of regional ethnomedicinal plants as potential inhibitors of SARS-CoV-2 Mpro: an integrated molecular docking, molecular dynamics and QM/MM study

The scientific community has achieved a remarkable milestone by creating efficacious vaccines against the SARS-CoV-2 virus. The treatment alternatives are still restricted, though. The bioactive ingredients present in natural plants are known to exhibit diverse pharmacological effects against many diseases. Using computational techniques such as molecular docking, drug-likeness, ADMET study, MD simulation, and our own N-layered Integrated molecular Orbital and Molecular mechanics (ONIOM) calculations, this study aimed to investigate essential oil constituents of Lindera neesiana, Litsea cubeba and Zanthoxylum armatum DC plants as a potential natural inhibitor of SARS-CoV-2 main protease (Mpro). To determine their binding affinity, 107 phytochemical substances in total were docked inside the binding pocket of Mpro. Copaene showed the highest binding affinity among the 107 compounds, with an energy of -7.90 kcal/mol. Furthermore, physiochemical and ADMET properties were evaluated for the top five phytocompounds. The studied phytocompounds showed good physiochemical and pharmacokinetic behaviour with no associated toxicity. MD simulation further provided evidence for stable interaction of phytocompounds within the binding pocket of Mpro. Subsequently, ONIOM calculation was done on the best-hit complex, wherein the hydrogen bonding interactions were retained with appreciable negative energy. These in silico results indicate that the specific phytocompounds present in essential oils of L. neesiana, L. cubeba, and Z. armatum DC have significant inhibitor ability against SARS-CoV-2 main protease and could be explored for future therapeutic investigations.

In silico identification of D449-0032 compound as a putative SARS-CoV-2 Mpro inhibitor

The SARS-CoV-2 pandemic originated the urgency in developing therapeutic resources for the treatment of COVID-19. Despite the current availability of vaccines and some antivirals, the occurence of severe cases of the disease and the risk of the emergence of new virus variants still motivate research in this field. In this context, this study aimed at the computational prospection of likely inhibitors of the main protease (Mpro) of SARS-CoV-2 since inhibiting this enzyme leads to disruption of the viral replication process. The virtual screening of the antiviral libraries Asinex, ChemDiv, and Enamine targeting SARS-CoV-2 Mpro was performed, indicating the D449-0032 compound as a promising inhibitor. Molecular dynamics simulations showed the stability of the protein-ligand complex and in silico predictions of toxicity and pharmacokinetic parameters indicated the probable drug-like behavior of the compound. In vitro and in vivo studies are essential to confirm the Mpro inhibition by the D449-0032.Communicated by Ramaswamy H. Sarma.

Antibiofilm potential of gallic acid against Klebsiella pneumoniae and Enterobacter hormaechei: in-vitro and in-silico analysis

Biofilm refers to a community of microorganisms that adhere to a substrate and play a crucial role in microbial pathogenesis and developing infections associated with medical devices. Enterobacter hormaechei and Klebsiella pneumoniae are classified as significant nosocomial pathogens within the ESKAPE category and cause diverse infections. In addition to their reputation as prolific biofilm formers, these pathogens are increasingly becoming drug-resistant and pose a substantial threat to the healthcare setting. Due to the inherent resistance of biofilms to conventional therapies, novel strategies are imperative for effectively controlling E. hormaechei and K. pneumoniae biofilms. This study aimed to assess the anti-biofilm activity of gallic acid (GA) against E. hormaechei and K. pneumoniae. The results of biofilm quantification assays demonstrated that GA exhibited significant antibiofilm activity against E. hormaechei and K. pneumoniae at concentrations of 4 mg mL-1, 2 mg mL-1, 1 mg mL-1, and 0.5 mg mL-1. Similarly, GA exhibited a dose-dependent reduction in violacein production, a QS-regulated purple pigment, indicating its ability to suppress violacein production and disrupt QS mechanisms in Chromobacterium violaceum. Additionally, computational tools were utilized to identify the potential target involved in the biofilm formation pathway. The computational analysis further indicated the strong binding affinity of GA to essential biofilm regulators, MrkH and LuxS, suggesting its potential in targeting the c-di-GMP and quorum sensing (QS) pathways to hinder biofilm formation in K. pneumoniae. These compelling findings strongly advocate GA as a promising drug candidate against biofilm-associated infections caused by E. hormaechei and K. pneumoniae.

Docking Studies and Molecular Dynamics Simulations of Potential Inhibitors from the Brown Seaweed Sargassum polycystum (Phaeophyceae) against PLpro of SARS-CoV-2

The COVID-19 disease is a major problem affecting human health all over the world. Consequently, researchers have been trying to find solutions to treat this pandemic-scale disease. Even if there are vaccines and approved drugs that could decrease the spread of this pandemic, multidisciplinary approaches are still needed to identify new small molecules as alternatives to combat COVID-19, especially those from nature. In this study, we employed computational approaches by screening 17 natural compounds from the tropical brown seaweed Sargassum polycystum known to have anti-viral properties that benefit human health. This study assessed some seaweed natural products that are bound to the PLpro of SARS-CoV-2. By employing pharmacophore and molecular docking, these natural compounds from S. polycystum showed remarkable scores for protein targets with competitive scores compared to X-ray crystallography ligands and well-known antiviral compounds. This study provides insightful information for advanced study and further in vitro examination and clinical investigation for drug development prospects of abundant yet underexploited tropical seaweeds.

Bisbenzylisoquinolines from Cissampelos pareira L. as antimalarial agents: Molecular docking, pharmacokinetics analysis, and molecular dynamic simulation studies

Malaria is a major global health issue due to the emergence of resistance to most of the available antimalarial drugs. There is an urgent need to discover new antimalarials to tackle the resistance issue. The present study aims to explore the antimalarial potential of chemical constituents reported from Cissampelos pareira L., a medicinal plant traditionally known for treating malaria. Phytochemically, benzylisoquinolines and bisbenzylisoquinolines are the major classes of alkaloids reported from this plant. In silico molecular docking revealed prominent interactions of bisbenzylisoquinolines such as hayatinine and curine with Pfdihydrofolate reductase (-6.983 Kcal/mol and -6.237 Kcal/mol), PfcGMP-dependent protein kinase (-6.652 Kcal/mol and -7.158 Kcal/mol), and Pfprolyl-tRNA synthetase (-7.569 Kcal/mol and -7.122 Kcal/mol). The binding affinity of hayatinine and curine with identified antimalarial targets was further evaluated using MD-simulation analysis. Among the identified antimalarial targets, the RMSD, RMSF, the radius of gyration, and PCA indicated the formation of stable complexes of hayatinine and curine with Pfprolyl-tRNA synthetase. The outcomes of in silico investigation putatively suggested that bisbenzylisoquinolines may act on the translation of the Plasmodium parasite to exhibit antimalarial potency.

High-Throughput Screening for the Potential Inhibitors of SARS-CoV-2 with Essential Dynamic Behavior

Global health security has been challenged by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic. Due to the lengthy process of generating vaccinations, it is vital to reposition currently available drugs in order to relieve anti-epidemic tensions and accelerate the development of therapies for Coronavirus Disease 2019 (COVID-19), the public threat caused by SARS-CoV-2. High throughput screening techniques have established their roles in the evaluation of already available medications and the search for novel potential agents with desirable chemical space and more cost-effectiveness. Here, we present the architectural aspects of highthroughput screening for SARS-CoV-2 inhibitors, especially three generations of virtual screening methodologies with structural dynamics: ligand-based screening, receptor-based screening, and machine learning (ML)-based scoring functions (SFs). By outlining the benefits and drawbacks, we hope that researchers will be motivated to adopt these methods in the development of novel anti- SARS-CoV-2 agents.

Analysis and Identification of Bioactive Compounds of Cannabinoids in Silico for Inhibition of SARS-CoV-2 and SARS-CoV

Despite the approval of multiple vaccinations in different countries, the majority of the world's population remains unvaccinated due to discrepancies in vaccine distribution and limited production capacity. The SARS-CoV-2 RBD-ACE2 complex (receptor binding domain that binds to ACE2) could be a suitable target for the development of a vaccine or an inhibitor. Various natural products have been used against SARS-CoV-2. Here, we docked 42 active cannabinoids to the active site of the SARS-CoV-2 and SARS-CoV complex of RBD-ACE2. To ensure the flexibility and stability of the complex produced after docking, the top three ligand molecules with the best overall binding energies were further analyzed through molecular dynamic simulation (MDS). Then, we used the webserver Swissadme program and binding free energy to calculate and estimate the MMPBSA and ADME characteristics. Our results showed that luteolin, CBGVA, and CBNA were the top three molecules that interact with the SARS-CoV-2 RBD-ACE2 complex, while luteolin, stigmasterol, and CBNA had the strongest contact with that SARS-CoV. Our findings show that luteolin may be a potential inhibitor of infections caused by coronavirus-like pathogens such as COVID-19, although further in vivo and in vitro research is required.

An understanding of coronavirus and exploring the molecular dynamics simulations to find promising candidates against the Mpro of nCoV to combat the COVID-19: A systematic review

The first infection case of new coronavirus was reported at the end of 2019 and after then, the cases are reported in all nations across the world in a very short period. Further, the regular news of mutations in the virus has made life restricted with appropriate behavior. To date, a new strain (Omicron and its new subvariant Omicron XE) has brought fear amongst us due to a higher trajectory of increase in the number of cases. The researchers thus started giving attention to this viral infection and discovering drug-like candidates to cure the infections. Finding a drug for any viral infection is not an easy task and takes plenty of time. Therefore, computational chemistry/bioinformatics is followed to get promising molecules against viral infection. Molecular dynamics (MD) simulations are being explored to get drug candidates in a short period. The molecules are screened via molecular docking, which provides preliminary information which can be further verified by molecular dynamics (MD) simulations. To understand the change in structure, MD simulations generated several trajectories such as root mean square deviation (RMSD), root mean square fluctuation (RMSF), hydrogen bonding, and radius of gyration for the main protease (Mpro) of the new coronavirus (nCoV) in the presence of small molecules. Additionally, change in free energy for the formation of complex of Mpro of nCoV with the small molecule can be determined by applying molecular mechanics with generalized born and surface area solvation (MM-GBSA). Thus, the promising molecules can be further explored for clinical trials to combat coronavirus disease-19 (COVID-19).

Computer-aided discovery, design, and investigation of COVID-19 therapeutics

Coronavirus disease 2019 (COVID-19) pandemic is currently the most serious public health threat faced by mankind. Thus, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes COVID-19, is being intensively investigated. Several vaccines are now available for clinical use. However, owing to the highly mutated nature of RNA viruses, the SARS-CoV-2 is changing at a rapid speed. Breakthrough infections by SARS-CoV-2 variants have been seen in vaccinated individuals. As a result, effective therapeutics for treating COVID-19 patients is urgently required. With the advance of computer technology, computational methods have become increasingly powerful in the biomedical research and pharmaceutical drug discovery. The applications of these techniques have largely reduced the costs and simplified processes of pharmaceutical drug developments. Intensive and extensive studies on SARS-CoV-2 proteins have been carried out and three-dimensional structures of the major SARS-CoV-2 proteins have been resolved and deposited in the Protein Data Bank. These structures provide the foundations for drug discovery and design using the structure-based computations, such as molecular docking and molecular dynamics simulations. In this review, introduction to the applications of computational methods in the discovery and design of novel drugs and repurposing of existing drugs for the treatments of COVID-19 is given. The examples of computer-aided investigations and screening of COVID-19 effective therapeutic compounds, functional peptides, as well as effective molecules from the herb medicines are discussed.

Insight into coronaviruses and natural products-based approach for COVID-19 treatment

There is a deep-rooted belief in mankind that for every illness, somewhere in the world, there exists a botanical-based healing agent in nature in the form of a natural product. Natural products are better equipped to become successful drugs because of their million years of coevolution in a biological milieu. Generally, most herbal formulations and natural products obtained from traditionally used medicinal plants are nontoxic and have rarely shown any adverse side effects on humans. Plants synthesize secondary metabolites primarily for their defense against microbes and herbivores, and because of this, these metabolites have good specificity and potency against harmful pathogens. Nowadays, mankind is facing the contagion effect of SARS-CoV-2 that has caused the ongoing pandemic of COVID-19, which has no specific and effective treatment. Hence this is the time to explore nature for effective, safe, and affordable remedies against this disease. This chapter includes an overview of coronaviruses, their therapeutic targets, and the progress made in identifying lead natural products against the coronaviruses. Additionally, molecular docking and pharmacokinetics analysis of anticoronaviral natural products have been performed to narrow down the possible lead molecules.

In silico studies of selected xanthophylls as potential candidates against SARS-CoV-2 targeting main protease (Mpro) and papain-like protease (PLpro)

Introduction: The main protease (Mpro) and the papain-like protease (PLpro) are essential for the replication of SARS-CoV-2. Both proteases can be targets for drugs acting against SARS-CoV-2.

Objective: This paper aims to investigate the in silico activity of nine xanthophylls as inhibitors of Mpro and PLpro.

Methods: The structures of Mpro (PDB-ID: 6LU7) and PLpro (PDB-ID: 6W9C) were obtained from RCSB Protein Data Bank and developed with BIOVIA Discovery Studio. Active sites of proteins were performed using CASTp. For docking the PyRx was used. Pharmacokinetic parameters of ADMET were evaluated using SwissADME and pkCSM.

Results: β-cryptoxanthin exhibited the highest binding energy: –7.4 kcal/mol in the active site of Mpro. In PLpro active site, the highest binding energy had canthaxanthin of –9.4 kcal/mol, astaxanthin –9.3 kcal/mol, flavoxanthin –9.2 kcal/mol and violaxanthin –9.2 kcal/mol. ADMET studies presented lower toxicity of xanthophylls in comparison to ritonavir and ivermectin.

Conclusion: Our findings suggest that xanthophylls can be used as potential inhibitors against SARS-CoV-2 main protease and papain-like protease.