Systematic virtual screening in search of SARS CoV-2 inhibitors against spike glycoprotein: pharmacophore screening, molecular docking, ADMET analysis and MD simulations

The Malaria Box molecules: a source for targeting the RBD and NTD cryptic pocket of the spike glycoprotein in SARS-CoV-2

CONTEXT

SARS-CoV-2, responsible for COVID-19, has led to over 500 million infections and more than 6 million deaths globally. There have been limited effective treatments available. The study aims to find a drug that can prevent the virus from entering host cells by targeting specific sites on the virus's spike protein.

METHOD

We examined 13,397 compounds from the Malaria Box library against two specific sites on the spike protein: the receptor-binding domain (RBD) and a predicted cryptic pocket. Using virtual screening, molecular docking, molecular dynamics, and MMPBSA techniques, they evaluated the stability of two compounds. TCMDC-124223 showed high stability and binding energy in the RBD, while TCMDC-133766 had better binding energy in the cryptic pocket. The study also identified that the interacting residues are conserved, which is crucial for addressing various virus variants. The findings provide insights into the potential of small molecules as drugs against the spike protein.

In silico identification of five binding sites on the SARS-CoV-2 spike protein and selection of seven ligands for such sites

To contribute to the development of products capable of complexing with the SARS-CoV-2 spike protein, and thus preventing the virus from entering the host cell, this work aimed at discovering binding sites in the whole protein structure, as well as selecting substances capable of binding efficiently to such sites. Initially, the three-dimensional structure of the protein, with all receptor binding domains in the closed state, underwent blind docking with 38 substances potentially capable of binding to this protein according to the literature. This allowed the identification of five binding sites. Then, those substances with more affinities for these sites underwent pharmacophoric search in the ZINC15 database. The 14,329 substances selected from ZINC15 were subjected to docking to the five selected sites of the spike protein. The ligands with more affinities for the protein sites, as well as the selected sites themselves, were used in the de novo design of new ligands that were also docked to the binding sites of the protein. The best ligands, regardless of their origins, were used to form complexes with the spike protein, which were subsequently used in molecular dynamics simulations and calculations of ligands affinities to the protein through the molecular mechanics/Poisson-Boltzmann surface area method (MMPBSA). Seven substances with good affinities to the spike protein (-12.9 to -20.6 kcal/mol), satisfactory druggability (Bioavailability score: 0.17 to 0.55), and low acute toxicity to mice (LD50: 751 to 1421 mg/kg) were selected as potentially useful for the future development of new products to manage COVID-19 infections.Communicated by Ramaswamy H. Sarma.

In silico screening, ADMET analysis and MD simulations of phytochemicals of Onosma bracteata Wall. as SARS CoV-2 inhibitors

Being attracted with their cardiotonic, antidiabetic, cough relieving activity, treatment of fever, absorbent, anti-asthmatic, etc. activities reported in ancient Ayurvedic literature, phytochemicals of Onosma bracteata wall should be evaluated for their activity against SARS-CoV-2 virus. The main objective of this study is to identify a hit molecule for the inhibition of entry, replication, and protein synthesis of SARS CoV-2 virus into the host. To achieve given objective, computational virtual screening of phytochemicals of Onosma bracteata wall has been performed against three main viral targets: spike, RdRp, and M^pro. Further, the analysis of Lipinski's Ro5 and their estimation of ADMET profiles were performed using computational tools. The MD simulations studies of top hits against each viral target have also been performed for 20 ns to ensure their stability. The analysis of results revealed that Pulmonarioside C (9) and other plant compounds showed better binding affinity towards targets than existing antiviral compounds, making them probable lead compounds against SARS-CoV-2. Structural modifications and studies through in silico analysis provided the founding stone for the establishment of SARS CoV-2 inhibitory potential of phytoconstitutents of Onosma bracteata wall.

Structure based Drug Designing Approaches in SARS-CoV-2 Spike Inhibitor Design

The COVID-19 outbreak and the pandemic situation have hastened the research community to design a novel drug and vaccine against its causative organism, the SARS-CoV-2. The spike glycoprotein present on the surface of this pathogenic organism plays an immense role in viral entry and antigenicity. Hence, it is considered an important drug target in COVID-19 drug design. Several three-dimensional crystal structures of this SARS-CoV-2 spike protein have been identified and deposited in the Protein DataBank during the pandemic period. This accelerated the research in computer- aided drug designing, especially in the field of structure-based drug designing. This review summarizes various structure-based drug design approaches applied to this SARS-CoV-2 spike protein and its findings. Specifically, it is focused on different structure-based approaches such as molecular docking, high-throughput virtual screening, molecular dynamics simulation, drug repurposing, and target-based pharmacophore modelling and screening. These structural approaches have been applied to different ligands and datasets such as FDA-approved drugs, small molecular chemical compounds, chemical libraries, chemical databases, structural analogs, and natural compounds, which resulted in the prediction of spike inhibitors, spike-ACE-2 interface inhibitors, and allosteric inhibitors.

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.

Computational Approaches to Designing Antiviral Drugs against COVID-19: A Comprehensive Review

The global impact of the COVID-19 pandemic caused by SARS-CoV-2 necessitates innovative strategies for the rapid development of effective treatments. Computational methodologies, such as molecular modelling, molecular dynamics simulations, and artificial intelligence, have emerged as indispensable tools in the drug discovery process. This review aimed to provide a comprehensive overview of these computational approaches and their application in the design of antiviral agents for COVID-19. Starting with an examination of ligand-based and structure-based drug discovery, the review has delved into the intricate ways through which molecular modelling can accelerate the identification of potential therapies. Additionally, the investigation extends to phytochemicals sourced from nature, which have shown promise as potential antiviral agents. Noteworthy compounds, including gallic acid, naringin, hesperidin, Tinospora cordifolia, curcumin, nimbin, azadironic acid, nimbionone, nimbionol, and nimocinol, have exhibited high affinity for COVID-19 Mpro and favourable binding energy profiles compared to current drugs. Although these compounds hold potential, their further validation through in vitro and in vivo experimentation is imperative. Throughout this exploration, the review has emphasized the pivotal role of computational biologists, bioinformaticians, and biotechnologists in driving rapid advancements in clinical research and therapeutic development. By combining state-of-the-art computational techniques with insights from structural and molecular biology, the search for potent antiviral agents has been accelerated. The collaboration between these disciplines holds immense promise in addressing the transmissibility and virulence of SARS-CoV-2.

Identification of Active Compounds against Melanoma Growth by Virtual Screening for Non-Classical Human DHFR Inhibitors

Antifolates such as methotrexate (MTX) have been largely known as anticancer agents because of their role in blocking nucleic acid synthesis and cell proliferation. Their mechanism of action lies in their ability to inhibit enzymes involved in the folic acid cycle, especially human dihydrofolate reductase (hDHFR). However, most of them have a classical structure that has proven ineffective against melanoma, and, therefore, inhibitors with a non-classical lipophilic structure are increasingly becoming an attractive alternative to circumvent this clinical resistance. In this study, we conducted a protocol combining virtual screening (VS) and cell-based assays to identify new potential non-classical hDHFR inhibitors. Among 173 hit compounds identified (average logP = 3.68; average MW = 378.34 Da), two-herein, called C1 and C2-exhibited activity against melanoma cell lines B16 and A375 by MTT and Trypan-Blue assays. C1 showed cell growth arrest (39% and 56%) and C2 showed potent cytotoxic activity (77% and 51%) in a dose-dependent manner. The effects of C2 on A375 cell viability were greater than MTX (98% vs 60%) at equivalent concentrations and times. Our results indicate that the integrated in silico/in vitro approach provided a benchmark to identify novel promising non-classical DHFR inhibitors showing activity against melanoma cells.

Perceiving SARS-CoV-2 Mpro and PLpro dual inhibitors from pool of recognized antiviral compounds of endophytic microbes: an in silico simulation study

Coronavirus disease 2019 (COVID-19) persists and shook the global population where the endgame to this pandemic is brought on by developing vaccines in record-breaking time. Nevertheless, these vaccines are far from perfect where their efficiency ranges from 65 to 90%; therefore, vaccines are not the one only solution to overcome this situation, and apart from administration of vaccines, the scientific community is at quest for finding alternative solutions to incumber SARS-CoV-2 infection. In this study, our research group is keen on identifying a bioactive molecule that is independent in its mode of action from existing vaccines which can potentially target the SARS-CoV-2 virus replicative efficacy. Papain-like protease (PLpro) and main protease (Mpro) are the most lucrative targets of COVIDs against which the drugs can be developed, as these proteases play a vital role in the replication and development of viral particles. Researchers have modelled a compound such as GRL0617 and X77 as an inhibitor of Mpro and PLpro, respectively, but use of these compounds has several limitations on hosts like toxicity and solubility. Under the current study by deploying rigorous computational assessments, pool of microbial secondary metabolites was screened and handpicked to search a structural or functional analogue of GRL0617 and X77, with an idea to identify a compound that can serve as dual inhibitor for both PLpro and Mpro. From the manually curated database of known antiviral compounds from fungal origin, we found cytonic acids A and B to potentially serve as dual inhibitor of PLpro and Mpro.