Computational drug re-purposing targeting the spike glycoprotein of SARS-CoV-2 as an effective strategy to neutralize COVID-19

Pharmacoinformatic approach to identify potential phytochemicals against SARS-CoV-2 spike receptor-binding domain in native and variants of concern

Severe acute respiratory syndrome-related coronavirus-2 (SARS-CoV-2) pathogenesis is initiated by the binding of SARS-CoV-2 spike (S) protein with the angiotensin-converting enzyme 2 receptor (ACE2R) on the host cell surface. The receptor-binding domain (RBD) of the S protein mediates the binding and is more prone to mutations resulting in the generation of different variants. Recently, molecules with the potential to inhibit the interaction of S protein with ACE2R have been of interest due to their therapeutic value. In this context, the present work was performed to identify potential RBD binders from the Indian medicinal plant's phytochemical database through virtual screening, molecular docking, and molecular dynamic simulation. Briefly, 1578 compounds filtered from 9596 phytochemicals were chosen for screening against the RBD of the native SARS-CoV-2 S protein. Based on the binding energy, the top 30 compounds were selected and re-docked individually against the native and five variants of concern (VOCs: alpha, beta, gamma, delta, and omicron) of SARS-CoV-2. Four phytochemicals, namely withanolide F, serotobenine, orobanchol, and gibberellin A51, were found to be potential RBD binders in native and all SARS-CoV-2 VOCs. Among the four, withanolide F exhibited lower binding energy (- 10.84 to - 8.56 kcal/mol) and better ligand efficiency (- 0.3 to - 0.25) against all forms of RBD and hence was subjected to a 100 ns MD simulation which confirmed its stringent binding to the RBDs in native and VOCs. The study prioritizes withanolide F as a prospective COVID-19 (Coronavirus disease) therapeutic agent based on the observations. It warrants deeper investigations into the four promising leads for understanding their precise therapeutic value.

Human Immunodeficiency Virus Status, Tenofovir Exposure, and the Risk of Poor Coronavirus Disease 19 Outcomes: Real-World Analysis From 6 United States Cohorts Before Vaccine Rollout

BACKGROUND

People with human immunodeficiency virus (HIV) (PWH) may be at increased risk for severe coronavirus disease 2019 (COVID-19) outcomes. We examined HIV status and COVID-19 severity, and whether tenofovir, used by PWH for HIV treatment and people without HIV (PWoH) for HIV prevention, was associated with protection.

METHODS

Within 6 cohorts of PWH and PWoH in the United States, we compared the 90-day risk of any hospitalization, COVID-19 hospitalization, and mechanical ventilation or death by HIV status and by prior exposure to tenofovir, among those with severe acute respiratory syndrome coronavirus 2 infection between 1 March and 30 November 2020. Adjusted risk ratios (aRRs) were estimated by targeted maximum likelihood estimation, with adjustment for demographics, cohort, smoking, body mass index, Charlson comorbidity index, calendar period of first infection, and CD4 cell counts and HIV RNA levels (in PWH only).

RESULTS

Among PWH (n = 1785), 15% were hospitalized for COVID-19 and 5% received mechanical ventilation or died, compared with 6% and 2%, respectively, for PWoH (n = 189 351). Outcome prevalence was lower for PWH and PWoH with prior tenofovir use. In adjusted analyses, PWH were at increased risk compared with PWoH for any hospitalization (aRR, 1.31 [95% confidence interval, 1.20-1.44]), COVID-19 hospitalizations (1.29 [1.15-1.45]), and mechanical ventilation or death (1.51 [1.19-1.92]). Prior tenofovir use was associated with reduced hospitalizations among PWH (aRR, 0.85 [95% confidence interval, .73-.99]) and PWoH (0.71 [.62-.81]).

CONCLUSIONS

Before COVID-19 vaccine availability, PWH were at greater risk for severe outcomes than PWoH. Tenofovir was associated with a significant reduction in clinical events for both PWH and PWoH.

Tenofovir-Containing Antiretroviral Therapy and Clinical Outcomes of SARS-CoV-2 Infection in People Living with HIV

Tenofovir has been hypothesized to be effective against COVID-19 and is available as two prodrugs, tenofovir disoproxil fumarate (TDF) and tenofovir alafenamide (TAF), both part of antiretroviral therapy (ART) regimens. People living with human immunodeficiency virus (PLWH) might be at higher risk for COVID-19 progression; however, information about the impact of tenofovir on COVID-19 clinical outcomes remains controversial. The COVIDARE is a prospective observational multicentric study in Argentina. PLWH with COVID-19 were enrolled from September 2020 to mid-June 2022. Patients were stratified according to baseline ART into those with tenofovir (TDF or TAF) and those without. Univariate and multivariate analyses were performed to evaluate the impact of tenofovir vs. non-tenofovir-containing regimens on major clinical outcomes. Of the 1155 subjects evaluated, 927 (80%) received tenofovir-based ART (79% TDF, 21% TAF) whilst the remaining population was under non-tenofovir regimens. The non-tenofovir group had older age and a higher prevalence of heart and kidney disease. Regarding the prevalence of symptomatic COVID-19, tomographic findings, hospitalization, and mortality, no differences were observed. The oxygen therapy requirement was higher in the non-tenofovir group. In the multivariate analyses, a first model with adjustment for viral load, CD4 T-cell count, and overall comorbidities showed that oxygen requirement was associated with non-tenofovir ART. In a second model with adjustment by chronic kidney disease, tenofovir exposure was not statistically significant.

Comparative docking studies of drugs and phytocompounds for emerging variants of SARS-CoV-2

In the last three years, COVID-19 has impacted the world with back-to-back waves leading to devastating consequences. SARS-CoV-2, the causative agent of COVID-19, was first detected in 2019 and since then has spread to 228 countries. Even though the primary focus of research groups was diverted to fight against COVID-19, yet no dedicated drug has been developed to combat the emergent life-threatening medical conditions. In this study, 35 phytocompounds and 43 drugs were investigated for comparative docking analysis. Molecular docking and virtual screening were performed against SARS-CoV-2 spike glycoprotein of 13 variants using AutoDock Vina tool 1.5.6 and Discovery Studio, respectively, to identify the most efficient drugs. Selection of the most suitable compounds with the best binding affinity was done after screening for toxicity, ADME (absorption, distribution, metabolism and excretion) properties and drug-likeliness. The potential candidates were discovered to be Liquiritin (binding affinities ranging between -7.0 and -8.1 kcal/mol for the 13 variants) and Apigenin (binding affinities ranging between -6.8 and -7.3 kcal/mol for the 13 variants) based on their toxicity and consistent binding affinity with the Spike protein of all variants. The stability of the protein-ligand complex was determined using Molecular dynamics (MD) simulation of Apigenin with the Delta plus variant of SARS-CoV-2. Furthermore, Liquiritin and Apigenin were also found to be less toxic than the presently used drugs and showed promising results based on in silico studies, though, confirmation using in vitro studies is required. This in-depth comparative investigation suggests potential drug candidates to fight against SARS-CoV-2 variants.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-022-03450-6.

A comparative study of 5- fluorouracil, doxorubicin, methotrexate, paclitaxel for their inhibition ability for Mpro of nCoV: Molecular docking and molecular dynamics simulations

A new corona virus (nCoV) is aetiological agent responsible for the viral pneumonia epidemic. Three is no specific therapeutic medicines available for the treatment of this condition and also effective treatment choices are few. In this work author tried to investigate some repurposing drug such as 5- fluorouracil, doxorubicin, methotrexate and paclitaxel against the main protease (Mpro) of nCoV by the computational model. Molecular docking was performed to screen out the best compound and doxorubicin was found to have minimum binding energy −121.89 kcal/mol. To further study, MD simulations were performed at 300 K and the result successfully corroborate the energy obtained by molecular docking. Temperature dependent MD simulation of the best molecule that is doxorubicin obtained from docking result was performed to check the variation in structural changes in Mpro of nCoV at 290 K, 310 K, 320 K and 325 K. It is sound that doxorubicin binds effectively with Mpro of nCoV at 290 K. Further ADME properties of the 5- fluorouracil, doxorubicin, methotrexate and paclitaxel were also evaluated to understand the bioavailability.

An integrated computational approach towards the screening of active plant metabolites as potential inhibitors of SARS-CoV-2: an overview

COVID-19 and its causative organism SARS-CoV-2 paralyzed the world and was designated a pandemic by the World Health Organization in March 2020. The worldwide health system is trying to discover an effective therapeutic measure since no clinically authorized medications are present. Screening of plant-derived pharmaceuticals may be a viable technique to fight COVID-19 in this vital situation. This review discusses the potential application of in silico approaches in developing new therapeutic molecules related to preventing SARS-CoV-2 infection. Also, it describes the binding affinity of various phytoconstituents with distinct SARS-CoV-2 target sites. In this perspective, an extensive literature survey was carried out to find the potential phytoconstituents to develop new therapeutic entities to treat COVID-19 in different online academic databases and books. Data retrieved from databases were analyzed and interpreted to conclude that many phytochemicals will bind with the 3-chymotrypsin-like (3CLpro) and papain-like proteases (PL^pro), spike glycoprotein, ACE-2, NSP15-endoribonuclease, and E protein targets of SARS-CoV-2 main protease using in silico molecular docking approach. The present investigations reveal that phytoconstituents such as curcumin, apigenin, chrysophanol, and gingerol are significantly binding with spike glycoprotein; laurolistine, acetoside, etc. are bound with M^pro for anti-SARS-CoV-2 therapies. Using virtual applications of in silico studies, the current study constitutes a progressive data analysis on the mechanism of binding efficiency of distinct classes of plant metabolites against the active sites of SARS-CoV-2. Furthermore, the current review also demonstrates the fundamental necessity of the alternative and complementary medicine for future therapeutic uses of phytoconstituents by phytochemists in the fight against COVID-19.

Probing the mutational landscape of the SARS-CoV-2 spike protein via quantum mechanical modeling of crystallographic structures

We employ a recently developed complexity-reduction quantum mechanical (QM-CR) approach, based on complexity reduction of density functional theory calculations, to characterize the interactions of the SARS-CoV-2 spike receptor binding domain (RBD) with ACE2 host receptors and antibodies. QM-CR operates via ab initio identification of individual amino acid residue's contributions to chemical binding and leads to the identification of the impact of point mutations. Here, we especially focus on the E484K mutation of the viral spike protein. We find that spike residue 484 hinders the spike's binding to the human ACE2 receptor (hACE2). In contrast, the same residue is beneficial in binding to the bat receptor Rhinolophus macrotis ACE2 (macACE2). In agreement with empirical evidence, QM-CR shows that the E484K mutation allows the spike to evade categories of neutralizing antibodies like C121 and C144. The simulation also shows how the Delta variant spike binds more strongly to hACE2 compared to the original Wuhan strain, and predicts that a E484K mutation can further improve its binding. Broad agreement between the QM-CR predictions and experimental evidence supports the notion that ab initio modeling has now reached the maturity required to handle large intermolecular interactions central to biological processes.

Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2

Despite tremendous efforts in the past two years, our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), virus-host interactions, immune response, virulence, transmission, and evolution is still very limited. This limitation calls for further in-depth investigation. Computational studies have become an indispensable component in combating coronavirus disease 2019 (COVID-19) due to their low cost, their efficiency, and the fact that they are free from safety and ethical constraints. Additionally, the mechanism that governs the global evolution and transmission of SARS-CoV-2 cannot be revealed from individual experiments and was discovered by integrating genotyping of massive viral sequences, biophysical modeling of protein-protein interactions, deep mutational data, deep learning, and advanced mathematics. There exists a tsunami of literature on the molecular modeling, simulations, and predictions of SARS-CoV-2 and related developments of drugs, vaccines, antibodies, and diagnostics. To provide readers with a quick update about this literature, we present a comprehensive and systematic methodology-centered review. Aspects such as molecular biophysics, bioinformatics, cheminformatics, machine learning, and mathematics are discussed. This review will be beneficial to researchers who are looking for ways to contribute to SARS-CoV-2 studies and those who are interested in the status of the field.

A fractal scaling analysis of the SARS-CoV-2 genome sequence

An approach based on fractal scaling analysis to characterize the organization of the SARS-CoV-2 genome sequence was used. The method is based on the detrended fluctuation analysis (DFA) implemented on a sliding window scheme to detect variations of long-range correlations over the genome sequence regions. The nucleotides sequence is mapped in a numerical sequence by using four different assignation rules: amino-keto, purine-pyrimidine, hydrogen-bond and hydrophobicity patterns. The originally reported sequence from Wuhan isolates (Wuhan Hu-1) was considered as a reference to contrast the structure of the 2002-2004 SARS-CoV-1 strain. Long-range correlations, quantified in terms of a scaling exponent, depended on both the mapping rule and the sequence region. Deviations from randomness were attributed to serial correlations or anti-correlations, which can be ascribed to ordered regions of the genome sequence. It was found that the Wuhan Hu-1 sequence was more random than the SARS-CoV-1 sequence, which suggests that the SARS-CoV-2 possesses a more efficient genomic structure for replication and infection. In general, the virus isolated in the early 2020 months showed slight correlation differences with the Wuhan Hu-1 sequence. However, early isolates from India and Italy presented visible differences that led to a more ordered sequence organization. It is apparent that the increased sequence order, particularly in the spike region, endowed some early variants with a more efficient mechanism to spreading, replicating and infecting. Overall, the results showed that the DFA provides a suitable framework to assess long-term correlations hidden in the internal organization of the SARS-CoV-2 genome sequence.

Therapeutic development by repurposing drugs targeting SARS-CoV-2 spike protein interactions by simulation studies

The human-to-human transmitted respiratory illness in COVID-19 affected by the pathogenic Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-CoV-2), which appeared in the last of December 2019 in Wuhan, China, and rapidly spread in many countries. Thereon, based on the urgent need for therapeutic molecules, we conducted in silico based docking and simulation molecular interaction studies on repurposing drugs, targeting SARS-CoV-2 spike protein. Further, the best binding energy of doxorubicin interacting with virus spike protein (PDB: 6VYB) was observed to be -6.38 kcal/mol and it was followed by exemestane and gatifloxacin. The molecular simulation dynamics analysis of doxorubicin, Reference Mean Square Deviation (RMSD), Root Mean Square fluctuation (RMSF), Radius of Gyration (Rg), and formation of hydrogen bonds plot interpretation suggested, a significant deviation and fluctuation of Doxorubicin-Spike RBD complex during the whole simulation period. The Rg analysis has stated that the Doxorubicin-Spike RBD complex was stable during 15,000-35,000 ps MDS. The results have suggested that doxorubicin could inhibit the virus spike protein and prevent the access of the SARS-CoV-2 to the host cell. Thus, in-vitro/in-vivo research on these drugs could be advantageous to evaluate significant molecules that control the COVID-19 disease.

Tenofovir, Another Inexpensive, Well-Known and Widely Available Old Drug Repurposed for SARS-COV-2 Infection

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is spreading worldwide with different clinical manifestations. Age and comorbidities may explain severity in critical cases and people living with human immunodeficiency virus (HIV) might be at particularly high risk for severe progression. Nonetheless, current data, although sometimes contradictory, do not confirm higher morbidity, risk of more severe COVID-19 or higher mortality in HIV-infected people with complete access to antiretroviral therapy (ART). A possible protective role of ART has been hypothesized to explain these observations. Anti-viral drugs used to treat HIV infection have been repurposed for COVID-19 treatment; this is also based on previous studies on severe acute respiratory syndrome virus (SARS-CoV) and Middle East respiratory syndrome virus (MERS-CoV). Among them, lopinavir/ritonavir, an inhibitor of viral protease, was extensively used early in the pandemic but it was soon abandoned due to lack of effectiveness in clinical trials. However, remdesivir, a nucleotide analog that acts as reverse-transcriptase inhibitor, which was tested early during the pandemic because of its wide range of antiviral activity against several RNA viruses and its safety profile, is currently the only antiviral medication approved for COVID-19. Tenofovir, another nucleotide analog used extensively for HIV treatment and pre-exposure prophylaxis (PrEP), has also been hypothesized as effective in COVID-19. No data on tenofovir's efficacy in coronavirus infections other than COVID-19 are currently available, although information relating to SARS-CoV-2 infection is starting to come out. Here, we review the currently available evidence on tenofovir's efficacy against SARS-CoV-2.

In-Silico Drug Designing of Spike Receptor with Its ACE2 Receptor and Nsp10/Nsp16 MTase Complex Against SARS-CoV-2

The realm Riboviria constitutes Coronaviruses, which led to the emergence of the pandemic COVID 19 in the twenty-first century affected millions of lives. At present, the management of COVID 19 largely depends on antiviral therapeutics along with the anti-inflammatory drug. The vaccine is under the final clinical phase, and emergency use is available. We aim at ACE2 and Nsp10/Nsp16 MTase as potential drug candidate in COVID 19 management in the present work. For drug designing, various computational simulation strategies have been employed like Swiss-Model, Hawk Dock, HDOCK, py Dock, and PockDrug for homology modeling, binding energies of the molecule with a target, simulate the conformation and binding poses, statistics of protein lock with target key and drug ability, respectively. The current in-silico screening depicts that the spike protein receptor is complementary to the target when bound to each other and forms a stable complex. The MMGBSA free energy binding property of receptor and ligand is critical. The intermolecular Statistics with the target Nsp10/Nsp16 MTase complex are plausible. We have also observed a high-affinity pocket binding site with the target. Therefore, the favorable intermolecular interactions and Physico-chemical properties emanate as a drug candidate treating COVID-19. This study has approached computational tools to analyze the conformation, binding affinity, and drug ability of receptor-ligand. Thus, the spike receptor with its ACE2 receptor with Nsp10/Nsp16 MTase complex would be a potent drug against SARS CoV-2 and can cure the infection as per consensus scoring.

Metal-Bound Methisazone; Novel Drugs Targeting Prophylaxis and Treatment of SARS-CoV-2, a Molecular Docking Study

SARS-CoV-2 currently lacks effective first-line drug treatment. We present promising data from in silico docking studies of new Methisazone compounds (modified with calcium, Ca; iron, Fe; magnesium, Mg; manganese, Mn; or zinc, Zn) designed to bind more strongly to key proteins involved in replication of SARS-CoV-2. In this in silico molecular docking study, we investigated the inhibiting role of Methisazone and the modified drugs against SARS-CoV-2 proteins: ribonucleic acid (RNA)-dependent RNA polymerase (RdRp), spike protein, papain-like protease (PlPr), and main protease (MPro). We found that the highest binding interactions were found with the spike protein (6VYB), with the highest overall binding being observed with Mn-bound Methisazone at −8.3 kcal/mol, followed by Zn and Ca at −8.0 kcal/mol, and Fe and Mg at −7.9 kcal/mol. We also found that the metal-modified Methisazone had higher affinity for PlPr and MPro. In addition, we identified multiple binding pockets that could be singly or multiply occupied on all proteins tested. The best binding energy was with Mn–Methisazone versus spike protein, and the largest cumulative increases in binding energies were found with PlPr. We suggest that further studies are warranted to identify whether these compounds may be effective for treatment and/or prophylaxis.