Molecular Dynamics Simulations Reveal the Interaction Fingerprint of Remdesivir Triphosphate Pivotal in Allosteric Regulation of SARS-CoV-2 RdRp

Immunoinformatic approach for designing a multi-epitope vaccine against non-typhoidal salmonellosis using starvation-stress response proteins from Salmonella Oranienburg

Non-typhoidal Salmonella is responsible for gastrointestinal illnesses worldwide. Therefore, it is important to implement effective therapeutic interventions for preventing these diseases. Vaccines have proven highly efficacious in the treatment and prevention of several illnesses. Nevertheless, there is currently no authorized vaccine available for non-typhoidal salmonellosis. This study aimed to employ in silico techniques to develop a multi-epitope vaccine targeting non-typhoidal salmonellosis. Specifically, we focused on proteins associated with the starvation stress response (SSR) in Salmonella Oranienburg. The presence of these proteins is essential for the survival and disease of the host organism. The vaccine sequence was constructed utilizing B-cell and T-cell epitopes. Linkers, adjuvants and PADRE sequences were used to establish connections between epitopes. The vaccine exhibited no allergenicity, toxigenicity and a significantly high antigenicity score. Docking analysis conducted between the designed vaccine and the TLR-1, TLR-2 and TLR-4 receptors demonstrated favorable interactions and the potential to activate these receptors. In addition, it was found through immunological simulation testing that the vaccine elicits a robust immune response. The use of these proteins in the construction of a multi-epitope vaccine shows potential in terms of both safety and immunogenicity.

Exploring Erythrina flavonoids as potential SARS-CoV-2 RdRp inhibitors through virtual screening, in silico ADMET evaluation, and molecular dynamics simulation studies

The COVID-19 pandemic, caused by SARS-CoV-2, has intensified the search for effective antiviral agents. This study investigates the inhibitory potential of 473 flavonoids from the genus Erythrina against the key enzyme of SARS-CoV-2, RNA-dependent RNA polymerase (RdRp). Virtual screening campaign using molecular docking identified 128 flavonoids with stronger binding energies to RdRp than remdesivir, a WHO-endorsed drug. Lipinski's Rule of Five and ADMET profiling suggested butein (119) as the promising RdRp inhibitor. Moreover, molecular dynamics simulations revealed that 119 binds effectively to RdRp and interacts with the RNA template and primer, suggesting a multi-faceted inhibitory mechanism. Our findings highlight the potential of Erythrina-derived flavonoids, particularly compound 119, as potent RdRp inhibitors, warranting further experimental studies.

Crystallographic mining driven computer-guided approach to identify the ASK1 inhibitor likely to perturb the catalytic region

The pathological levels of reactive oxygen species (ROS) and oxidative stress has been recognized as a critical driver for inflammatory disorders. Apoptosis signal-regulating kinase 1 (ASK1) has been reported to be activated by intracellular ROS and its inhibition leads to a down regulation of p38-and JNK-dependent signaling. ASK1 inhibitors are reported to have the potential to treat clinically important inflammatory pathologies including liver, pulmonary and renal disorders. In view of its biological and pathological significance, inhibition of ASK1 with small molecules has been pursued as an attractive strategy to combat human diseases such as non-alcoholic steatohepatitis (NASH). Despite several ASK1 inhibitors being developed, the failure in Phase 3 clinical trials of most advanced candidate selonsertib's, underscores to discover therapeutic agents with diverse chemical moiety. Here, by using structural pharmacophore and enumeration strategy on mining co-crystals of ASK1, different scaffolds were generated to enhance the chemical diversity keeping the critical molecular interaction in the catalytic site intact. A total of 15,772 compounds were generated from diverse chemical scaffolds and were evaluated using a virtual screening pipeline. Based on docking and MM-GBSA scores, a lead candidate, S3C-1-D424 was identified from top hits. A comparative molecular dynamics simulations (MD) of APO, Selonsertib and shortlisted potential candidates combined with pharmacokinetics profiling and thermodynamic analysis, demonstrating their suitability as potential ASK1 inhibitors to explore further for establishment towards hit-to-lead campaign.Communicated by Ramaswamy H. Sarma.

Berbamine prevents SARS-CoV-2 entry and transmission

Effective antiviral drugs are essential to combat COVID-19 and future pandemics. Although many compounds show antiviral in vitro activity, only a few retain effectiveness in vivo against SARS-CoV-2. Here, we show that berbamine (Berb) is effective against SARS-CoV, MER-CoV, SARS-CoV-2 and its variants, including the XBB.1.16 variant. In hACE2.Tg mice, Berb suppresses SARS-CoV-2 replication through two distinct mechanisms: inhibiting spike-mediated viral entry and enhancing antiviral gene expression during infection. The administration of Berb, in combination with remdesivir (RDV), clofazimine (Clof) and fangchinoline (Fcn), nearly eliminated viral load and promoted recovery from acute SARS-CoV-2 infection and its variants. Co-housed mice in direct contact with either pre-treated or untreated infected mice exhibited negligible viral loads, reduced lung pathology, and decreased viral shedding, suggesting that Berb may effectively hinder virus transmission. This broad-spectrum activity positions Berb as a promising preventive or therapeutic option against betacoronaviruses.

Molecular analysis of dUTPase of Helicobacter pylori for identification of novel inhibitors using in silico studies

The human gastric pathogen Helicobacter pylori chronically affects the gastric mucosal layer of approximately half of world's population. The emergence of resistant strains urges the need for identification of novel and selective drug against new molecular targets. A ubiquitous enzyme, Deoxyuridine 5'-triphosphate nucleotidohydrolase (dUTPase), is considered as first line of defense against uracil mis-incorporation into DNA, and essential for genome integrity. Lack of dUTPase triggers an elevated recombination frequency, DNA breaks and ultimately cell death. Hence, dUTPase can be considered as a promising target for development of novel lead inhibitor compounds in H. pylori treatment. Herein, we report the generation of three-dimensional model of the target protein using comparative modelling and its validation. To identify dUTPase inhibitors, a high throughput virtual screening approach utilizing Knowledge-based inhibitors and DrugBank database was implemented. Top ranked compounds were scrutinized based on investigations of the protein-ligand interaction fingerprints, molecular interaction maps and binding affinities and the drug potentiality. The best ligands were studied further for complex stability and intermolecular interaction profiling with respect to time under 100 ns classical molecular dynamic stimulation, establishing significant stability in dynamic states as observed from RMSD and RMSF parameters and interactions with the catalytic site residues. The binding free energy calculation computed using MM-GBSA method from the MD simulation trajectories demonstrated that our molecules possess strong binding affinity towards the Helicobacter pylori dUTPase protein. We conclude that our proposed molecules may be potential lead molecules for effective inhibition against the H. pylori dUTPase protein subject to experimental validation.Communicated by Ramaswamy H. Sarma.

Hotspot site microenvironment in the deubiquitinase OTUB1 drives its stability and aggregation

Lewy bodies (LB) are aberrant protein accumulations observed in the brain cells of individuals affected by Parkinson's disease (PD). A comprehensive analysis of LB proteome identified over a hundred proteins, many co-enriched with α-synuclein, a major constituent of LB. Within this context, OTUB1, a deubiquitinase detected in LB, exhibits amyloidogenic properties, yet the mechanisms underlying its aggregation remain elusive. In this study, we identify two critical sites in OTUB1-namely, positions 133 and 173-that significantly impact its amyloid aggregation. Substituting alanine at position 133 and lysine at position 173 enhances both thermodynamic and kinetic stability, effectively preventing amyloid aggregation. Remarkably, lysine at position 173 demonstrates the highest stability without compromising enzymatic activity. The increased stability and inhibition of amyloid aggregation are attributed mainly to the changes in the specific microenvironment at the hotspot. In our exploration of the in-vivo co-occurrence of α-synuclein and OTUB1 in LB, we observed a synergistic modulation of each other's aggregation. Collectively, our study unveils the molecular determinants influencing OTUB1 aggregation, shedding light on the role of specific residues in modulating aggregation kinetics and structural transition. These findings contribute valuable insights into the complex interplay of amino acid properties and protein aggregation, with potential implications for understanding broader aspects of protein folding and aggregation phenomena.

System biology approach to identify the novel biomarkers in glioblastoma multiforme tumors by using computational analysis

Introduction: The most common primary brain tumor in adults is glioblastoma multiforme (GBM), accounting for 45.2% of all cases. The characteristics of GBM, a highly aggressive brain tumor, include rapid cell division and a propensity for necrosis. Regretfully, the prognosis is extremely poor, with only 5.5% of patients surviving after diagnosis. Methodology: To eradicate these kinds of complicated diseases, significant focus is placed on developing more effective drugs and pinpointing precise pharmacological targets. Finding appropriate biomarkers for drug discovery entails considering a variety of factors, including illness states, gene expression levels, and interactions between proteins. Using statistical techniques like p-values and false discovery rates, we identified differentially expressed genes (DEGs) as the first step in our research for identifying promising biomarkers in GBM. Of the 132 genes, 13 showed upregulation, and only 29 showed unique downregulation. No statistically significant changes in the expression of the remaining genes were observed. Results: Matrix metallopeptidase 9 (MMP9) had the greatest degree in the hub biomarker gene identification, followed by (periostin (POSTN) at 11 and Hes family BHLH transcription factor 5 (HES5) at 9. The significance of the identification of each hub biomarker gene in the initiation and advancement of glioblastoma multiforme was brought to light by the survival analysis. Many of these genes participate in signaling networks and function in extracellular areas, as demonstrated by the enrichment analysis.We also identified the transcription factors and kinases that control proteins in the proteinprotein interactions (PPIs) of the DEGs. Discussion: We discovered drugs connected to every hub biomarker. It is an appealing therapeutic target for inhibiting MMP9 involved in GBM. Molecular docking investigations indicated that the chosen complexes (carmustine, lomustine, marimastat, and temozolomide) had high binding affinities of -6.3, -7.4, -7.7, and -8.7 kcal/mol, respectively, the mean root-mean-square deviation (RMSD) value for the carmustine complex and marimastat complex was 4.2 Å and 4.9 Å, respectively, and the lomustine and temozolomide complex system showed an average RMSD of 1.2 Å and 1.6 Å, respectively. Additionally, high stability in root-mean-square fluctuation (RMSF) analysis was observed with no structural conformational changes among the atomic molecules. Thus, these in silico investigations develop a new way for experimentalists to target lethal diseases in future.

In silico analysis and characterization of potential inhibitors of MmaA3, a methoxy mycolic acid synthase from Mycobacterium tuberculosis

The emergence of the multi-and extensively drug-resistant (MDR and XDR) strains of Mycobacterium tuberculosis (M.tb), necessitates paradigm-shifting therapeutic approaches. The impermeable waxy lipid layer, primarily composed of mycolic acids, is a key factor in conferring resistance to conventional drugs. This study introduces a novel strategy to combat drug resistance by targeting Methoxy mycolic acid synthase 3 (MmaA3), a critical enzyme in the mycolic acid biosynthesis pathway. MmaA3 is responsible for the O-methylation of hydroxymycolate precursors and emerges as a promising therapeutic target. Through homology-based modeling, we generated a three-dimensional structure of MmaA3, providing crucial insights into its structural characteristics. High throughput virtual screening was performed against the MmaA3 model, using diverse sources: knowledge-based, FDA-approved Drugbank, and Asinex-Elite libraries. Through rigorous computational analyses, including binding affinity assessments, molecular interactions analysis, and binding free energy calculations, potential inhibitors of MmaA3 have been identified. Subsequent validation studies evaluated the stability of top protein-ligand complexes, and free energy calculations using molecular dynamics simulations. The stability of complexes within the catalytic site was confirmed through RMSD and RMSF profile analyses. Furthermore, binding free energy calculations using the MM-GBSA approach revealed significant binding affinity of identified ligands for MmaA3 target protein, comparable to its substrate/cofactors. These findings underscore the potential of the proposed molecules as candidates for further experimental exploration, offering promising avenues for the development of effective inhibitors against M.tb. Overall, our research contributes to significantly advancing the formulation of progressive therapeutic strategies in combating drug-resistant tuberculosis.

Ab initio Modeling of Hydrogen Bonding of Remdesivir and Adenosine with Uridine

Remdesivir (RDV) emerged as an effective drug against the SARS-CoV-2 virus pandemic. One of the crucial steps in the mechanism of action of RDV is its incorporation into the growing RNA strand. RDV, an adenosine analogue, forms Watson-Crick (WC) type hydrogen bonds with uridine in the complementary strand and the strength of this interaction will control efficacy of RDV. While there is a plethora of structural and energetic information available about WC H-bonds in natural base pairs, the interaction of RDV with uridine has not been studied yet at the atomic level. In this article, we aim to bridge this gap, to understand RDV and its hydrogen bonding interactions, by employing density functional theory (DFT) at the M06-2X/cc-pVDZ level. The interaction energy, QTAIM analysis, NBO and SAPT2 are performed for RDV, adenosine, and their complex with uridine to gain insights into the nature of hydrogen bonding. The computations show that RDV has similar geometry, energetic, molecular orbitals, and aromaticity as adenosine, suggesting that RDV is an effective adenosine analogue. The important geometrical parameters, such as bond distances and red-shift in the stretching vibrational modes of adenosine, RDV and uridine identify two WC-type H-bonds. The relative strength of these two H-bonds is computed using QTAIM parameters and the computed hydrogen bond energy. Finally, the SAPT2 study is performed at the minima and at non-equilibrium base pair distances to understand the dominant intermolecular physical force. This study, based on a thorough analysis of a variety of computations, suggests that both adenosine and RDV have similar structure, energetic, and hydrogen bonding behaviour.

Elevated glycosylation of CD36 in platelets is a risk factor for oxLDL-mediated platelet activation in type 2 diabetes

Platelet activation and related cardiovascular complications are the hallmarks of type 2 diabetes (T2D). We investigated the mechanism of platelet activation in T2D using MS-based identification of differentially expressed platelet proteins with a focus on glycosylated forms. Glycosylation is considered one of the common post-translational modifications in T2D, and N/O-linked glycosylation of glycoproteins (GPs)/integrins is known to play crucial roles in platelet activation. Our platelet proteome data revealed elevated levels of GPs GPIbα, GPIIbIIIa, GPIV (CD36), GPV and integrins in T2D patients. T2D platelets had elevated N-linked glycosylation of CD36 at asparagine (Asn)408,417 . Enrichment analysis revealed a close association of glycosylated CD36 with thrombospondin-1, fibrinogen and SERPINA1 in T2D platelets. The glycosylation of CD36 has previously been reported to increase cellular uptake of long-chain fatty acids. Our in silico molecular docking data also showed a favorable binding of cholesterol with glycosylated Asn417 CD36 compared to the non-glycosylated form. We further investigated the CD36:LDL cholesterol axis in T2D. Elevated levels of oxidized-low density lipoprotein (oxLDL) were found to cause significant platelet activation via CD36-mediated stimulation of Lyn-JNK signaling. Sulfo-N-succinimidyl oleate, an inhibitor of CD36, effectively inhibited oxLDL-mediated platelet activation and adhesion in vitro. Our study suggests increased glycosylation of CD36 in T2D platelets as a potential route for oxLDL-mediated platelet activation. The oxLDL:CD36 axis may thus be exploited as a prospective target to develop therapeutics against thrombosis in T2D.

Fangchinoline inhibits SARS-CoV-2 and MERS-CoV entry

The COVID-19 pandemic caused by SARS-CoV-2, lead to mild to severe respiratory illness and resulted in 6.9 million deaths worldwide. Although vaccines are effective in preventing COVID-19, they may not be sufficient to protect immunocompromised individuals from this respiratory illness. Moreover, novel emerging variants of SARS-CoV-2 pose a risk of new COVID-19 waves. Therefore, identification of effective antivirals is critical in controlling SARS and other coronaviruses, such as MERS-CoV. We show that Fangchinoline (Fcn), a bisbenzylisoquinoline alkaloid, inhibits replication of SARS-CoV, SARS-CoV-2, and MERS-CoV in a range of in vitro assays, by blocking entry. Therapeutic use of Fcn inhibited viral loads in the lungs, and suppressed associated airway inflammation in hACE2. Tg mice and Syrian hamster infected with SARS-CoV-2. Combination of Fcn with remdesivir (RDV) or an anti-leprosy drug, Clofazimine, exhibited synergistic antiviral activity. Compared to Fcn, its synthetic derivative, MK-04-003, more effectively inhibited SARS-CoV-2 and its variants B.1.617.2 and BA.5 in mice. Taken together these data demonstrate that Fcn is a pan beta coronavirus inhibitor, which possibly can be used to combat novel emerging coronavirus diseases.

Antiviral Effect of 5'-Arylchalcogeno-3-aminothymidine Derivatives in SARS-CoV-2 Infection

The understanding that zidovudine (ZDV or azidothymidine, AZT) inhibits the RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2 and that chalcogen atoms can increase the bioactivity and reduce the toxicity of AZT has directed our search for the discovery of novel potential anti-coronavirus compounds. Here, the antiviral activity of selenium and tellurium containing AZT derivatives in human type II pneumocytes cell model (Calu-3) and monkey kidney cells (Vero E6) infected with SARS-CoV-2, and their toxic effects on these cells, was evaluated. Cell viability analysis revealed that organoselenium (R3a-R3e) showed lower cytotoxicity than organotellurium (R3f, R3n-R3q), with CC50 ≥ 100 µM. The R3b and R3e were particularly noteworthy for inhibiting viral replication in both cell models and showed better selectivity index. In Vero E6, the EC50 values for R3b and R3e were 2.97 ± 0.62 µM and 1.99 ± 0.42 µM, respectively, while in Calu-3, concentrations of 3.82 ± 1.42 µM and 1.92 ± 0.43 µM (24 h treatment) and 1.33 ± 0.35 µM and 2.31 ± 0.54 µM (48 h) were observed, respectively. The molecular docking calculations were carried out to main protease (Mpro), papain-like protease (PLpro), and RdRp following non-competitive, competitive, and allosteric inhibitory approaches. The in silico results suggested that the organoselenium is a potential non-competitive inhibitor of RdRp, interacting in the allosteric cavity located in the palm region. Overall, the cell-based results indicated that the chalcogen-zidovudine derivatives were more potent than AZT in inhibiting SARS-CoV-2 replication and that the compounds R3b and R3e play an important inhibitory role, expanding the knowledge about the promising therapeutic capacity of organoselenium against COVID-19.

Non-oncology drug (meticrane) shows anti-cancer ability in synergy with epigenetic inhibitors and appears to be involved passively in targeting cancer cells

Emerging evidence suggests that chemotherapeutic agents and targeted anticancer drugs have serious side effects on the healthy cells/tissues of the patient. To overcome this, the use of non-oncology drugs as potential cancer therapies has been gaining momentum. Herein, we investigated one non-oncology drug named meticrane (a thiazide diuretic used to treat essential hypertension), which has been reported to indescribably improve the therapeutic efficacy of anti-CTLA4 in mice with AB1 HA tumors. In our hypothesis-driven study, we tested anti-cancer potential meticrane in hematological malignance (leukemia and multiple myeloma) and liver cancer cell lines. Our analysis showed that: 1) Meticrane induced alteration in the cell viability and proliferation in leukemia cells (Jurkat and K562 cells) and liver cancer (SK-hep-1), however, no evidence of apoptosis was detectable. 2) Meticrane showed additive/synergistic effects with epigenetic inhibitors (DNMT1/5AC, HDACs/CUDC-101 and HDAC6/ACY1215). 3) A genome-wide transcriptional analysis showed that meticrane treatment induces changes in the expression of genes associated with non-cancer associated pathways. Of importance, differentially expressed genes showed favorable correlation with the survival-related genes in the cancer genome. 4) We also performed molecular docking analysis and found considerable binding affinity scores of meticrane against PD-L1, TIM-3, CD73, and HDACs. Additionally, we tested its suitability for immunotherapy against cancers, but meticrane showed no response to the cytotoxicity of cytokine-induced killer (CIK) cells. To our knowledge, our study is the first attempt to identify and experimentally confirm the anti-cancer potential of meticrane, being also the first to test the suitability of any non-oncology drug in CIK cell therapy. Beyond that, we have expressed some concerns confronted during testing meticrane that also apply to other non-oncology drugs when considered for future clinical or preclinical purposes. Taken together, meticrane is involved in some anticancer pathways that are passively targeting cancer cells and may be considered as compatible with epigenetic inhibitors.

Discovery of non-nucleoside oxindole derivatives as potent inhibitors against dengue RNA-dependent RNA polymerase

A series of thiazole linked Oxindole-5-Sulfonamide (OSA) derivatives were designed as inhibitors of RNA-dependent RNA polymerase (RdRp) activity of Dengue virus. These were synthesized and then evaluated for their efficacy in ex-vivo virus replication assay using human cell lines. Among 20 primary compounds in the series, OSA-15 was identified as a hit. A series of analogues were synthesized by replacing the difluoro benzyl group of OSA-15 with different substituted benzyl groups. The efficacy of OSA-15derivatives was less than that of the parent compound, except OSA-15-17, which has shown improved efficacy than OSA-15. The further optimization was carried out by adding dimethyl (DM) groups to both the sulfonamide and oxindole NH's to produce OSA-15-DM and OSA-15-17-DM. These two compounds were showing no detectable cytotoxicity and the latter was more efficacious. Further, both these compounds were tested for inhibition in all the serotypes of the Dengue virus using an ex-vivo assay. The EC₅₀ of OSA-15-17-DM was observed in a low micromolar range between 2.5 and 5.0 µg/ml. Computation docking and molecular dynamics simulation studies confirmed the binding of identified hits to DENV RdRp. OSA15-17-DM blocks the RNA entrance and elongation site for their biological activity with high binding affinity. Overall, the identified oxindole derivatives are novel compounds that can inhibit Dengue replication, working as non-nucleoside inhibitors (NNI) to explore as anti-viral RdRp activity.

Computational Analysis of SAM Analogs as Methyltransferase Inhibitors of nsp16/nsp10 Complex from SARS-CoV-2

Methyltransferases (MTases) enzymes, responsible for RNA capping into severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), are emerging important targets for the design of new anti-SARS-CoV-2 agents. Here, analogs of S-adenosylmethionine (SAM), obtained from the bioisosteric substitution of the sulfonium and amino acid groups, were evaluated by rigorous computational modeling techniques such as molecular dynamics (MD) simulations followed by relative binding free analysis against nsp16/nsp10 complex from SARS-CoV-2. The most potent inhibitor (2a) shows the lowest binding free energy (-58.75 Kcal/mol) and more potency than Sinefungin (SFG) (-39.8 Kcal/mol), a pan-MTase inhibitor, which agrees with experimental observations. Besides, our results suggest that the total binding free energy of each evaluated SAM analog is driven by van der Waals interactions which can explain their poor cell permeability, as observed in experimental essays. Overall, we provide a structural and energetic analysis for the inhibition of the nsp16/nsp10 complex involving the evaluated SAM analogs as potential inhibitors.

In Silico Study towards Repositioning of FDA-Approved Drug Candidates for Anticoronaviral Therapy: Molecular Docking, Molecular Dynamics and Binding Free Energy Calculations

The SARS-CoV-2 targets were evaluated for a set of FDA-approved drugs using a combination of drug repositioning and rigorous computational modeling methodologies such as molecular docking and molecular dynamics (MD) simulations followed by binding free energy calculations. Six FDA-approved drugs including, Ouabain, Digitoxin, Digoxin, Proscillaridin, Salinomycin and Niclosamide with promising anti-SARS-CoV-2 activity were screened in silico against four SARS-CoV-2 proteins—papain-like protease (PLpro), RNA-dependent RNA polymerase (RdRp), SARS-CoV-2 main protease (Mpro), and adaptor-associated kinase 1 (AAK1)—in an attempt to define their promising targets. The applied computational techniques suggest that all the tested drugs exhibited excellent binding patterns with higher scores and stable complexes compared to the native protein cocrystallized inhibitors. Ouabain was suggested to act as a dual inhibitor for both PLpro and Mpro enzymes, while Digitoxin bonded perfectly to RdRp. In addition, Salinomycin targeted PLpro. Particularly, Niclosamide was found to target AAK1 with greater affinity compared to the reference drug. Our study provides comprehensive molecular-level insights for identifying or designing novel anti-COVID-19 drugs.

State-of-the-Art Molecular Dynamics Simulation Studies of RNA-Dependent RNA Polymerase of SARS-CoV-2

Molecular dynamics (MD) simulations are powerful theoretical methods that can reveal biomolecular properties, such as structure, fluctuations, and ligand binding, at the level of atomic detail. In this review article, recent MD simulation studies on these biomolecular properties of the RNA-dependent RNA polymerase (RdRp), which is a multidomain protein, of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are presented. Although the tertiary structures of RdRps in SARS-CoV-2 and SARS-CoV are almost identical, the RNA synthesis activity of RdRp of SARS-CoV is higher than SARS-CoV-2. Recent MD simulations observed a difference in the dynamic properties of the two RdRps, which may cause activity differences. RdRp is also a drug target for Coronavirus disease 2019 (COVID-19). Nucleotide analogs, such as remdesivir and favipiravir, are considered to be taken up by RdRp and inhibit RNA replication. Recent MD simulations revealed the recognition mechanism of RdRp for these drug molecules and adenosine triphosphate (ATP). The ligand-recognition ability of RdRp decreases in the order of remdesivir, favipiravir, and ATP. As a typical recognition process, it was found that several lysine residues of RdRp transfer these ligand molecules to the binding site such as a “bucket brigade.” This finding will contribute to understanding the mechanism of the efficient ligand recognition by RdRp. In addition, various simulation studies on the complexes of SARS-CoV-2 RdRp with several nucleotide analogs are reviewed, and the molecular mechanisms by which these compounds inhibit the function of RdRp are discussed. The simulation studies presented in this review will provide useful insights into how nucleotide analogs are recognized by RdRp and inhibit the RNA replication.

Impact of Remdesivir Incorporation along the Primer Strand on SARS-CoV-2 RNA-Dependent RNA Polymerase

Remdesivir was the first antiviral drug that received emergency use authorization from the United States Food and Drug Administration and is now formally approved to treat COVID-19. Remdesivir is a nucleotide analogue that targets the RNA-dependent RNA polymerase (RdRp) of coronaviruses, including SARS-CoV-2. The solution of multiple RdRp structures has been one of the main axes of research in the race against the SARS-CoV-2 virus. Several hypotheses of the mechanism of inhibition of RdRp by remdesivir have been proposed, although open questions remain. This work uses molecular dynamics simulations to explore the impact of remdesivir and two analogues as incoming nucleotides and of up to four incorporations of remdesivir along the primer strand on RdRp. The simulation results suggest that the overall structure and the dynamical behavior of RdRp are destabilized by remdesivir and the two analogues in the incoming position. The incorporation of remdesivir along the primer strand impacts specific non-bonded interactions between the nascent RNA and the polymerase subunit, as well as the overall dynamical networks on RdRp. The strongest impact on the structure and dynamics are observed after three incorporations, when remdesivir is located at position -A3, in agreement with previously reported experimental and computational results. Our results provide atomic-level details of the role played by remdesivir on the disruption of RNA synthesis by RdRp and the main drivers of these disruptions.

Computational Study of SARS-CoV-2 RNA Dependent RNA Polymerase Allosteric Site Inhibition

The COVID-19 pandemic has caused millions of fatalities since 2019. Despite the availability of vaccines for this disease, new strains are causing rapid ailment and are a continuous threat to vaccine efficacy. Here, molecular docking and simulations identify strong inhibitors of the allosteric site of the SARS-CoV-2 virus RNA dependent RNA polymerase (RdRp). More than one hundred different flavonoids were docked with the SARS-CoV-2 RdRp allosteric site through computational screening. The three top hits were Naringoside, Myricetin and Aureusidin 4,6-diglucoside. Simulation analyses confirmed that they are in constant contact during the simulation time course and have strong association with the enzyme's allosteric site. Absorption, distribution, metabolism, excretion and toxicity (ADMET) data provided medicinal information of these top three hits. They had good human intestinal absorption (HIA) concentrations and were non-toxic. Due to high mutation rates in the active sites of the viral enzyme, these new allosteric site inhibitors offer opportunities to drug SARS-CoV-2 RdRp. These results provide new information for the design of novel allosteric inhibitors against SARS-CoV-2 RdRp.

Co-crystallization and structure determination: An effective direction for anti-SARS-CoV-2 drug discovery

Safer and more-effective drugs are urgently needed to counter infections with the highly pathogenic SARS-CoV-2, cause of the COVID-19 pandemic. Identification of efficient inhibitors to treat and prevent SARS-CoV-2 infection is a predominant focus. Encouragingly, using X-ray crystal structures of therapeutically relevant drug targets (PLpro, Mpro, RdRp, and S glycoprotein) offers a valuable direction for anti-SARS-CoV-2 drug discovery and lead optimization through direct visualization of interactions. Computational analyses based primarily on MMPBSA calculations have also been proposed for assessing the binding stability of biomolecular structures involving the ligand and receptor. In this study, we focused on state-of-the-art X-ray co-crystal structures of the abovementioned targets complexed with newly identified small-molecule inhibitors (natural products, FDA-approved drugs, candidate drugs, and their analogues) with the assistance of computational analyses to support the precision design and screening of anti-SARS-CoV-2 drugs.