PACAP key interactions with PAC1, VPAC1, and VPAC2 identified by molecular dynamics simulations.

The neuropeptide pituitary adenylate cyclase-activating polypeptide (PACAP) belongs to the glucagon/secretin family. PACAP interacts with the pituitary adenylate cyclase-activating polypeptide receptor type 1 (PAC1) and vasoactive intestinal peptide receptors 1 and 2 (VPAC1 and VPAC2), exhibiting functions in the immune, endocrine, and nervous systems. This peptide is upregulated in numerous instances of brain injury, acting as a neuroprotective agent. It can also suppress HIV-1 and SARS-CoV-2 viral replication in vitro. This work aimed to identify, in each peptide-receptor system, the most relevant residues for complex stability and interaction energy communication via Molecular Dynamics (MD), Free Energy calculations, and Protein-energy networks, thus revealing in detail the underlying mechanisms of activation of these receptors. Hydrogen bond formation, interaction energies, and computational alanine scanning between PACAP and its receptors showed that His1, Asp3, Arg12, Arg14, and Lys15 are crucial to the peptide's stability. Furthermore, several PACAP interactions with structurally conserved positions deemed necessary in GPCR B1 activation, including Arg2.60, Lys2.67, and Glu7.42, were significant for the peptide's stability within the receptors. According to the protein-energy network, the connection between Asp3 of PACAP and the receptors' conserved Arg2.60 represents a critical energy communication hub in all complexes. Additionally, the ECDs of the receptors were also found to function as energy communication hubs for PACAP. Although the overall binding mode of PACAP in the three receptors was found to be highly conserved, Arg12 and Tyr13 of PACAP were more prominent in complex with PAC1, while Ser2 of PACAP was with VPAC2. The detailed analyses performed in this work pave the way for using PACAP and its receptors as therapeutic targets.Communicated by Ramaswamy H. Sarma.

In-silico studies on wild orange (Citrus macroptera Mont.) compounds against COVID-19 pro-inflammation targets.

One-fifth of COVID-19 patients suffer a severe course of COVID-19 (SARS-CoV-2) infection; however, the specific causes remain unclear. Despite numerous papers that have been flooded in different scientific journals clear clinical picture of COVID-19 aftermath persists to remain fuzzy. The survivors of severe COVID-19infection having defeated the virus are just the starting of an uncharted recovery path. Currently, there is no drug available that is safe to consume to combat this pandemic. However, researchers still struggling to find specific therapeutic solutions. The present study employed an in silico approach to assessing the inhibitory potential of the phytochemicals obtained from GC-MS analysis of Citrus macroptera against inflammatory proteins like COX-2, NMDAR and VCAM-1 which remains in a hyperactive state even after a patient is fully cured of this deadly mRNA virus. An extensive molecular docking investigation of the phyto-compounds at the active binding pockets of the inflammatory proteins revealed the promising inhibitory potential of the phytochemicals. Reasonable physicochemical attributes of the compounds following Lipinski's rule of five, VEBER and PAINS analysis further established them as potential therapeutic candidates against aforesaid inflammatory proteins. MM-GBSA binding free energy estimation revealed that Limonene was the most promising candidate displaying the highest binding efficacy with the concerned VCAM-1 protein included in the present analysis. An interesting finding is the phytochemicals exhibited better binding energy scores with the concerned COX-2, VCAM-1 and NMDA receptor proteins than the conventional drugs that are specifically targeted against them. Our in silico results suggest that all the natural phyto-compounds derived from C. macroptera could be employed in Post covid inflammation complexities after appropriate pre-clinical and clinical trials for further scientific validation.Communicated by Ramaswamy H. Sarma.

Computational studies on the design of NCI natural products as inhibitors to SARS-CoV-2 main protease.

The pandemic coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in more than 5 million deaths globally. Currently there are no effective drugs available to treat COVID-19. The viral protease replication can be blocked by the inhibition of main protease that is encoded in polyprotein 1a and is therefore a potential protein target for drug discovery. We have carried out virtual screening of NCI natural compounds followed by molecular docking in order to identify hit molecules as probable SARS-CoV-2 main protease inhibitors. The molecular dynamics (MD) simulations of apo form in complex with N3, α-ketoamide and NCI natural products was used to validate the screened compounds. The MD simulations trajectories were analyzed using normal mode analysis and principal component analysis revealing dynamical nature of the protein. These findings aid in understanding the binding of natural products and molecular mechanisms of SARS-CoV-2 main protease inhibition.Communicated by Ramaswamy H. Sarma.

Design of novel pyrimidine based remdesivir analogues with dual target specificity for SARS CoV-2: A computational approach.

As the world undergone unpreceded time of tragedy with the corona virus, many researchers have raised to showcase their scientific contributions in terms of novel configured anti-viral drugs until now. Herein, we designed pyrimidine based nucleotides and assessed for the binding capability with SARS-CoV-2 viral replication targets of nsp12 RNA-dependent RNA polymerase and Mpro main protease. Molecular docking studies showed all the designed compounds to possess good binding affinity, with a few compounds which outperforms the control drug remdesivir GS-5743 and its active form GS-441524. Further molecular dynamics simulation studies confirmed their stability and preservation of the non-covalent interactions. Based on the present findings Ligand2-BzV_0Tyr, ligand3-BzV_0Ura, and ligand5-EeV_0Tyr showed good binding affinity with Mpro, whereas, ligand1-BzV_0Cys and Ligand2-BzV_0Tyr showed good binding affinity with RdRp, thus could act as potential lead compounds against SARS-CoV-2, which needs further validation studies. In particular, Ligand2-BzV_0Tyr could be more beneficial candidate with the dual target specificity for Mpro and RdRp.

Screening of Potential Inhibitors Against SARS-CoV-2 Based on Prescription Mining and Molecular Dynamics Simulations

Objective To detect the active ingredients in the traditional Chinese medicine prescription and its molecular mechanisms against SARS-CoV-2 by prescription mining and molecular dynamics simulations. Methods Herein, prescription mining and virtual screening of drugs were performed to screen the potential inhibitors against SARS-CoV-2. Molecular docking and molecular dynamics (MDs) simulations were further performed to explore the molecular recognition and inhibition mechanism between the potential inhibitors and SARS-CoV-2. Results The natural compounds library was constructed by 143 prescriptions of traditional Chinese medicine, which contained 640 natural compounds. Ten compounds were screened out from the natural compounds library. Among the 10 compounds, 23-trans-p-coumaryhormentic acid, the main active constituent of the Loquat leaf, showed the best binding affinity targeting the recognizing interface of SARS-CoV-2 S protein/ACE2. Upon binding 23-trans-p-coumaryhormentic acid, the key interactions between SARS-CoV-2 S protein and ACE2 were almost interrupted. Conclusion Ten compounds targeting SARS-CoV-2 S protein/ACE2 interface were screened out from natural compound library. And we inferred that 23-trans-p-coumaryhormentic acid is a potential inhibitor against SARS-CoV-2, which would contribute to the development of the antiviral drug for SARS-CoV-2. © 2022 Institute of Biophysics,Chinese Academy of Sciences. All rights reserved.

Design of Potent Inhibitors Targeting the Main Protease of SARS-CoV-2 Using QSAR Modeling, Molecular Docking, and Molecular Dynamics Simulations.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is a serious global public health threat. The evolving strains of SARS-CoV-2 have reduced the effectiveness of vaccines. Therefore, antiviral drugs against SARS-CoV-2 are urgently needed. The main protease (Mpro) of SARS-CoV-2 is an extremely potent target due to its pivotal role in virus replication and low susceptibility to mutation. In the present study, a quantitative structure-activity relationship (QSAR) study was performed to design new molecules that might have higher inhibitory activity against SARS-CoV-2 Mpro. In this context, a set of 55 dihydrophenanthrene derivatives was used to build two 2D-QSAR models using the Monte Carlo optimization method and the Genetic Algorithm Multi-Linear Regression (GA-MLR) method. From the CORAL QSAR model outputs, the promoters responsible for the increase/decrease in inhibitory activity were extracted and interpreted. The promoters responsible for an increase in activity were added to the lead compound to design new molecules. The GA-MLR QSAR model was used to ensure the inhibitory activity of the designed molecules. For further validation, the designed molecules were subjected to molecular docking analysis and molecular dynamics simulations along with an absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis. The results of this study suggest that the newly designed molecules have the potential to be developed as effective drugs against SARS-CoV-2.

Template Entrance Channel as Possible Allosteric Inhibition and Resistance Site for Quinolines Tricyclic Derivatives in RNA Dependent RNA Polymerase of Bovine Viral Diarrhea Virus.

The development of potent non-nucleoside inhibitors (NNIs) could be an alternate strategy to combating infectious bovine viral diarrhea virus (BVDV), other than the traditional vaccination. RNA-dependent RNA polymerase (RdRp) is an essential enzyme for viral replication; therefore, it is one of the primary targets for countermeasures against infectious diseases. The reported NNIs, belonging to the classes of quinolines (2h: imidazo[4,5-g]quinolines and 5m: pyrido[2,3-g] quinoxalines), displayed activity in cell-based and enzyme-based assays. Nevertheless, the RdRp binding site and microscopic mechanistic action are still elusive, and can be explored at a molecular level. Here, we employed a varied computational arsenal, including conventional and accelerated methods, to identify quinoline compounds' most likely binding sites. Our study revealed A392 and I261 as the mutations that can render RdRp resistant against quinoline compounds. In particular, for ligand 2h, mutation of A392E is the most probable mutation. The loop L1 and linker of the fingertip is recognized as a pivotal structural determinant for the stability and escape of quinoline compounds. Overall, this work demonstrates that the quinoline inhibitors bind at the template entrance channel, which is governed by conformational dynamics of interactions with loops and linker residues, and reveals structural and mechanistic insights into inhibition phenomena, for the discovery of improved antivirals.

In-silico guided design, screening, and molecular dynamic simulation studies for the identification of potential SARS-CoV-2 main protease inhibitors for the targeted treatment of COVID-19.

COVID-19, the disease responsible for the recent pandemic, is caused by a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The main protease (Mpro) of SARS-CoV-2 is an essential proteolytic enzyme that plays a number of important roles in the replication of the virus in human host cells. Blocking the function of SARS-CoV-2 Mpro offers a promising and targeted, therapeutic option for the treatment of the COVID-19 infection. Such an inhibitory strategy is currently successful in treating COVID-19 under FDA's emergency use authorization, although with limited benefit to the immunocompromised along with an unfortunate number of side effects and drug-drug interactions. Current COVID vaccines protect against severe disease and death but are mostly ineffective toward long COVID which has been seen in 5-36% of patients. SARS-CoV-2 is a rapidly mutating virus and is here to stay endemically. Hence, alternate therapeutics to treat SARS-CoV-2 infections are still needed. Moreover, because of the high degree of conservation of Mpro among different coronaviruses, any newly developed antiviral agents should better prepare us for potential future epidemics or pandemics. In this paper, we first describe the design and computational docking of a library of novel 188 first-generation peptidomimetic protease inhibitors using various electrophilic warheads with aza-peptide epoxides, α-ketoesters, and ß-diketones identified as the most effective. Second-generation designs, 192 compounds in total, focused on aza-peptide epoxides with drug-like properties, incorporating dipeptidyl backbones and heterocyclic ring motifs such as proline, indole, and pyrrole groups, yielding 8 hit candidates. These novel and specific inhibitors for SARS-CoV-2 Mpro can ultimately serve as valuable alternate and broad-spectrum antivirals against COVID-19.Communicated by Ramaswamy H. Sarma.

Exploring the pharmacological aspects of natural phytochemicals against SARS-CoV-2 Nsp14 through an in silico approach.

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), possesses an important bifunctional nonstructural protein (nsp14) with a C-terminal N7-methyltransferase (N7-MTase) domain and an N-terminal domain with exoribonuclease (ExoN) activity that is required for maintaining high-fidelity viral replication. Viruses use the error-prone replication mechanism, which results in high mutation rates, to adapt quickly to stressful situations. The efficiency with which nsp14 removes mismatched nucleotides due to the presence of ExoN activity protects viruses from mutagenesis. We investigated the pharmacological role of the phytochemicals (Baicalein, Bavachinin, Emodin, Kazinol F, Lycorine, Sinigrin, Procyanidin A2, Tanshinone IIA, Tanshinone IIB, Tomentin A, and Tomentin E) against the highly conserved nsp14 protein using docking-based computational analyses in search of new potential natural drug targets. The selected eleven phytochemicals failed to bind the active site of N7-Mtase in the global docking study, while the local docking study identified the top five phytochemicals with high binding energy scores ranging from - 9.0 to - 6.4 kcal/mol. Procyanidin A2 and Tomentin A showed the highest docking score of - 9.0 and - 8.1 kcal/mol, respectively. Local docking of isoform variants was also conducted, yielding the top five phytochemicals, with Procyanidin A1 having the highest binding energy value of - 9.1 kcal/mol. The phytochemicals were later tested for pharmacokinetics and pharmacodynamics analysis for Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) which resulted in choosing Tomentin A as a potential candidate. The molecular dynamics simulations studies of nsp14 revealed significant conformational changes upon complex formation with the identified compound, implying that these phytochemicals could be used as safe nutraceuticals which will impart long-term immunological competence in the human population against CoVs. Supplementary Information: The online version contains supplementary material available at 10.1007/s40203-023-00143-7.

Identification of Potential Lead Compounds Targeting Novel Druggable Cavity of SARS-CoV-2 Spike Trimer by Molecular Dynamics Simulations.

The global pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become an urgent public health problem. Spike (S) protein mediates the fusion between the virus and the host cell membranes, consequently emerging as an important target of drug design. The lack of comparisons of in situ full-length S homotrimer structures in different states hinders understanding the structures and revealing the function, thereby limiting the discovery and development of therapeutic agents. Here, the steady-state structures of the in situ full-length S trimer in closed and open states (Sclosed and Sopen) were modeled with the constraints of density maps, associated with the analysis of the dynamic structural differences. Subsequently, we identified various regions with structure and property differences as potential binding pockets for ligands that promote the formation of inactive trimeric protein complexes. By using virtual screening strategy and a newly defined druggable cavity, five ligands were screened with potential bioactivities. Then molecular dynamic (MD) simulations were performed on apo protein structures and ligand bound complexes to reveal the conformational changes upon ligand binding. Our simulation results revealed that sulforaphane (SFN), which has the best binding affinity, could inhibit the conformational changes of S homotrimer that would occur during the viral membrane fusion. Our results could aid in the understanding of the regulation mechanism of S trimer aggregation and the structure-activity relationship, facilitating the development of potential antiviral agents.

Computational studies on phylogeny and drug designing using molecular simulations for COVID-19.

Since the first appearance of a novel coronavirus pneumonia (NCP) caused by a novel human coronavirus, and especially after the infection started its rapid spread over the world causing the COVID-19 (coronavirus disease 2019) pandemics, a very substantial part of the scientific community is engaged in the intensive research dedicated to finding of the potential therapeutics to cure this disease. As repurposing of existing drugs represents the only instant solution for those infected with the virus, we have been working on utilization of the structure-based virtual screening method to find some potential medications. In this study, we screened a library of 646 FDA approved drugs against the receptor-binding domain of the SARS-CoV-2 spike (S) protein and the main protease of this virus. Scoring functions revealed that some of the anticancer drugs (such as Pazopanib, Irinotecan, and Imatinib), antipsychotic drug (Risperidone), and antiviral drug (Raltegravir) have a potential to interact with both targets with high efficiency. Further we performed molecular dynamics simulations to understand the evolution in protein upon interaction with drug. Also, we have performed a phylogenetic analysis of 43 different coronavirus strains infecting 12 different mammalian species.Communicated by Ramaswamy H. Sarma.

Flavan-based phytoconstituents inhibit Mpro, a SARS-COV-2 molecular target, in silico.

A well-validated in-silico approach can provide promising drug candidates for the treatment of the ongoing CoVID19 pandemic. In this study, we have screened 32 phytochemical constituents (PCCs) with Mpro binding site (PDB:6W63) based on which we identified three possible candidates that are likely to be effective against CoVID19-viz., licoleafol (binding energy: -8.1 kcal/mol), epicatechin gallate (-8.5 kcal/mol) and silibinin (-8.4 kcal/mol) that result in higher binding affinity than the known inhibitor, X77 (-7.7 kcal/mol). Molecular dynamics (MD) simulations of PCCs-Mpro complex confirmed molecular docking results with high structural and dynamical stability. The selected compounds were found to exhibit low mean squared displacements (licoleafol: 2.25 ± 0.43 Å, epicatechin gallate: 1.93 ± 0.35 Å, and silibinin: 1.39 ± 0.19 Å) and overall low fluctuations of the binding complexes (root mean squared fluctuations below 2 Å). Visualization of the MD trajectories and structural analyses revealed that they remain confined to the initial binding region, with mean fluctuations lower than 3 Å. To access the collective motion of the atoms, we performed principal component analysis demonstrating that the first 10 principal components are the major contributors (approximate contribution of 80%) and are responsible for the overall PCCs motion. Considering that the three selected PCCs share the same flavan backbone and exhibit antiviral activity against hepatitis C, we opine that licoleafol, epi-catechin gallate, and silibinin can be promising anti-CoVID19 drug candidates.Communicated by Ramaswamy H. Sarma.

One microsecond MD simulations of the SARS-CoV-2 main protease and hydroxychloroquine complex reveal the intricate nature of binding.

Currently, several vaccines and antivirals across the globe are in clinical trials. Hydroxychloroquine (HCQ) was reported to inhibit the SARS-CoV-2 virus in antiviral assays. Here, it raises the curiosity about the molecular target of HCQ inside the cell. It may inhibit some of the viral targets, or some other complex mechanisms must be at disposal towards action mechanisms. In some of the viruses, proteases are experimentally reported to be a potential target of HCQ. However, no in-depth investigations are available in the literature yet. Henceforth, we have carried out extensive, one-microsecond long molecular dynamics simulations of the bound complex of hydroxychloroquine with main protease (Mpro) of SARS-CoV-2. Our analysis found that HCQ binds within the catalytic pocket of Mpro and remains stable upto one-third of simulation time but further causes increased fluctuations in simulation parameters. In the end, the HCQ does not possess any pre-formed hydrogen bond, other non-covalent interactions with Mpro, ultimately showing the unsteadiness in binding at catalytic binding pocket and may suggest that HCQ may not inhibit the Mpro. In the future, this study would require experimental validation on enzyme assays against Mpro, and that may be the final say. Communicated by Ramaswamy H. Sarma.

Quantitative structure-activity relationships, molecular docking and molecular dynamics simulations reveal drug repurposing candidates as potent SARS-CoV-2 main protease inhibitors.

The current outbreak of COVID-19 is leading an unprecedented scientific effort focusing on targeting SARS-CoV-2 proteins critical for its viral replication. Herein, we performed high-throughput virtual screening of more than eleven thousand FDA-approved drugs using backpropagation-based artificial neural networks (q2LOO = 0.60, r2 = 0.80 and r2pred = 0.91), partial-least-square (PLS) regression (q2LOO = 0.83, r2 = 0.62 and r2pred = 0.70) and sequential minimal optimization (SMO) regression (q2LOO = 0.70, r2 = 0.80 and r2pred = 0.89). We simulated the stability of Acarbose-derived hexasaccharide, Naratriptan, Peramivir, Dihydrostreptomycin, Enviomycin, Rolitetracycline, Viomycin, Angiotensin II, Angiotensin 1-7, Angiotensinamide, Fenoterol, Zanamivir, Laninamivir and Laninamivir octanoate with 3CLpro by 100 ns and calculated binding free energy using molecular mechanics combined with Poisson-Boltzmann surface area (MM-PBSA). Our QSAR models and molecular dynamics data suggest that seven repurposed-drug candidates such as Acarbose-derived Hexasaccharide, Angiotensinamide, Dihydrostreptomycin, Enviomycin, Fenoterol, Naratriptan and Viomycin are potential SARS-CoV-2 main protease inhibitors. In addition, our QSAR models and molecular dynamics simulations revealed that His41, Asn142, Cys145, Glu166 and Gln189 are potential pharmacophoric centers for 3CLpro inhibitors. Glu166 is a potential pharmacophore for drug design and inhibitors that interact with this residue may be critical to avoid dimerization of 3CLpro. Our results will contribute to future investigations of novel chemical scaffolds and the discovery of novel hits in high-throughput screening as potential anti-SARS-CoV-2 properties.Communicated by Ramaswamy H. Sarma.

An insight into the simulation directed understanding of the mechanism in SARS CoV-2 N-CTD, dimer integrity, and RNA-binding: Identifying potential antiviral inhibitors.

Coronavirus 2019 is a transmissible disease and has caused havoc throughout the world. The present study identifies the novel potential antiviral inhibitors against the nucleocapsid C-terminal domain that aids in RNA-binding and replication. A total of 485,629 compounds were screened, and MD was performed. The trajectory analysis (DCCM & PCA), structural integrity, and degree of compaction depicted the protein-ligand complex stability (PDB-PISA and Rgyr). Results obtained from screening shortlists 13 compounds possessing high Docking score. Further, seven compounds had a permissible RMSD limit (3 Å), with robust RMSF. Post-MD analysis of the top two compounds (204 and 502), DCCM & PCA analysis show a positive atomic displacements correlation among residues of active sites-dimer (Chain A and Chain B) & residual clustering. The ΔGint of RNA-bound (-83.5 kcal/mol) and drug-bound N-CTD-204 (-40.8 kcal/mol) and 502(-39.7 kcal/mol) as compared to Apo (-35.95 kcal/mol) suggests stabilization of protein, with less RNA-binding possibility. The Rgyr values depict the loss of compactness on RNA-binding when compared to the drug-bound N-CTD complex. Further, overlapping the protein complexes (0 ns and 100 ns) display significant changes in RMSD of the protein (204-2.07 Å and 502-1.89 Å) as compared to the Apo (1.72 Å) and RNA-bound form (1.76 Å), suggesting strong interaction for compound 204 as compared to 502. ADMET profiling indicates that these compounds can be used for further experiments (in vitro and pre-clinical). Compound 204 could be a promising candidate for targeting the N-protein-RNA assembly and viral replication.

Biomolecular Simulations in the Time of COVID19, and After.

COVID19 has changed life for people worldwide. Despite lockdowns globally, computational research has pressed on, working remotely and collaborating virtually on research questions in COVID19 and the virus it is caused by, SARS-CoV-2. Molecular simulations can help to characterize the function of viral and host proteins and have the potential to contribute to the search for vaccines and treatments. Changes in the modus operandi of research groups include broader adoption of the use of preprint servers, earlier and more open sharing of methods, models, and data, the use of social media to rapidly disseminate information, online seminars, and cloud-based virtual collaboration. Research funders and computing providers worldwide recognized the need to provide rapid and significant access to computational architectures. In this review, we discuss how the interplay of all of these factors is influencing the impact - both potential and realized - of biomolecular simulations in the fight against SARS-CoV-2.

Atomic-level thermodynamics analysis of the binding free energy of SARS-CoV-2 neutralizing antibodies.

Understanding how protein-protein binding affinity is determined from molecular interactions at the interface is essential in developing protein therapeutics such as antibodies, but this has not yet been fully achieved. Among the major difficulties are the facts that it is generally difficult to decompose thermodynamic quantities into contributions from individual molecular interactions and that the solvent effect-dehydration penalty-must also be taken into consideration for every contact formation at the binding interface. Here, we present an atomic-level thermodynamics analysis that overcomes these difficulties and illustrate its utility through application to SARS-CoV-2 neutralizing antibodies. Our analysis is based on the direct interaction energy computed from simulated antibody-protein complex structures and on the decomposition of solvation free energy change upon complex formation. We find that the formation of a single contact such as a hydrogen bond at the interface barely contributes to binding free energy due to the dehydration penalty. On the other hand, the simultaneous formation of multiple contacts between two interface residues favorably contributes to binding affinity. This is because the dehydration penalty is significantly alleviated: the total penalty for multiple contacts is smaller than a sum of what would be expected for individual dehydrations of those contacts. Our results thus provide a new perspective for designing protein therapeutics of improved binding affinity.

Unveiling the Inhibitory Potentials of Peptidomimetic Azanitriles and Pyridyl Esters towards SARS-CoV-2 Main Protease: A Molecular Modelling Investigation.

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is responsible for COVID-19, which was declared a global pandemic in March 2020 by the World Health Organization (WHO). Since SARS-CoV-2 main protease plays an essential role in the virus's life cycle, the design of small drug molecules with lower molecular weight has been a promising development targeting its inhibition. Herein, we evaluated the novel peptidomimetic azatripeptide and azatetrapeptide nitriles against SARS-CoV-2 main protease. We employed molecular dynamics (MD) simulations to elucidate the selected compounds' binding free energy profiles against SARS-CoV-2 and further unveil the residues responsible for the drug-binding properties. Compound 8 exhibited the highest binding free energy of -49.37 ± 0.15 kcal/mol, followed by compound 7 (-39.83 ± 0.19 kcal/mol), while compound 17 showed the lowest binding free energy (-23.54 ± 0.19 kcal/mol). In addition, the absorption, distribution, metabolism, and excretion (ADME) assessment was performed and revealed that only compound 17 met the drug-likeness parameters and exhibited high pharmacokinetics to inhibit CYP1A2, CYP2C19, and CYP2C9 with better absorption potential and blood-brain barrier permeability (BBB) index. The additional intermolecular evaluations suggested compound 8 as a promising drug candidate for inhibiting SARS-CoV-2 Mpro. The substitution of isopropane in compound 7 with an aromatic benzene ring in compound 8 significantly enhanced the drug's ability to bind better at the active site of the SARS-CoV-2 Mpro.

Surfactin-like lipopeptides from Bacillus clausii efficiently bind to spike glycoprotein of SARS-CoV-2.

The coronavirus disease 2019 (COVID-19) rapidly spread across the globe, infecting millions and causing hundreds of deaths. It has been now around three years but still, it remained a serious threat worldwide, even after the availability of some vaccines. Bio-surfactants are known to have antiviral activities and might be a potential alternative for the treatment of SARS-CoV-2 infection. In the present study, we have isolated and purified, a surfactin-like lipopeptide produced by a probiotic bacterial strain Bacillus clausii TS. Upon purification and characterization with MALDI analysis, the molecular weight of the lipopeptide is confirmed as 1037 Da (similar to surfactin C) which is known to have antiviral activities against various enveloped viruses. Purified surfactin-like lipopeptide showed efficient binding and inhibition of SARS-CoV-2 spike (S1) protein, revealed by competitive ELISA assay. Further, we have explored the complete thermodynamics of the inhibitory binding of surfactin-like lipopeptide with S1 protein using isothermal titration calorimetric (ITC) assay. ITC results are in agreement with ELISA with a binding constant of 1.78 × 10-4 M-1. For further validation of the inhibitory binding of surfactin-like lipopeptide with S1 protein and its receptor binding domain (RBD), we performed molecular docking, dynamics, and simulation experiments. Our results suggested that surfactin could be a promising drug agent for the spike protein targeting drug development strategy against SARS-CoV-2 and other emerging variants.Communicated by Ramaswamy H. Sarma.

Mutations in the receptor-binding domain of human SARS CoV-2 spike protein increases its affinity to bind human ACE-2 receptor.

The severe acute respiratory syndrome virus-2 (SARS CoV-2) infection has resulted in the current global pandemic. The binding of SARS CoV-2 spike protein receptor-binding domain (RBD) to the human angiotensin converting enzyme-2 (ACE-2) receptor causes the host infection. The spike protein has undergone several mutations with reference to the initial strain isolated during December 2019 from Wuhan, China. A number of these mutant strains have been reported as variants of concern and as variants being monitored. Some of these mutants are known to be responsible for increased transmissibility of the virus. The reason for the increased transmissibility caused by the point mutations can be understood by studying the structural implications and inter-molecular interactions in the binding of viral spike protein RBD and human ACE-2. Here, we use the crystal structure of the RBD in complex with ACE-2 available in the public domain and analyse the 250 ns molecular dynamics (MD) simulations of wild-type and mutants; K417N, K417T, N440K, N501Y, L452R, T478K, E484K and S494P. The ionic, hydrophobic and hydrogen bond interactions, amino acid residue flexibility, binding energies and structural variations are characterized. The MD simulations provide clues to the molecular mechanisms of ACE-2 receptor binding in wild-type and mutant complexes. The mutant spike proteins RBD were associated with greater binding affinity with ACE-2 receptor. Communicated by Ramaswamy H. Sarma.