Rational Repurposing of Drugs, Clinical Trial Candidates, and Natural Products for SARS-CoV-2 Therapy

In the last 20 years, the world has been threatened with coronavirus (CoV) pandemic threats from severe acute respiratory syndrome coronavirus (SARS-CoV) in 2002, Middle East respiratory syndrome coronavirus (MERS-CoV) in 2012 and finally COVID-19 due to SARS-CoV-2 in 2019. These viruses posed serious global pandemic threats, with estimated case fatality rates of 15% for SARS-CoV, 34% for MERS-CoV, and 1-3% for SARS-CoV-2. With the current pandemic still far from over there is an urgent need to find new drug treatments for COVID-19. We can assume that this will not be the last coronavirus to threaten humanity, so we need better tools to identify drugs active against past but also future coronavirus threats. In this Chapter we describe in silico computer modeling and screening approaches that can rapidly identify drugs from existing drug libraries that could be repurposed to treat COVID-19 infections. We also describe how this computational screening pipeline can be expanded in the future to identify drugs with broad spectrum activity against a wide diversity of coronaviruses. A significant concern is that the protection against CoVs provided by single drugs protection may be short-lived because viruses rapidly mutate to develop drug resistance. We know from other viruses such as HIV that drugs hitting multiple targets within the virus provide better protection against the development of resistance. This Chapter describes the current state of development of in silico CoV drug repurposing, the challenges and pitfalls of these approaches, and our predictions of how these methods could be used to develop drugs for future pandemics before they occur. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Inhibition of SARS-CoV2 Replication Regulated by NSP3 through Ayurveda Phytoconstituents of Indian Traditional Medicine

With Covid-19, a significant proportion of the population who are already vaccinated have tested positive. Therefore, there is a need for better medicines that act against the virus rigorously without causing any side effects. We aim to achieve the same through molecular docking and further simulations for bioactive phytochemicals of ayurvedic medicinal plants. The target for this study has been considered the NSP3 protein of the viral RNA that actively takes part in both replication and immune evasion pathways of the virus. Ligand libraries consisting of bioactive phytochemicals of aswasgandha and analogues of curcumin and piperine are curated. The libraries, along with the NSP3 protein moiety are docked onto two active sites. With the best-scored complexes further taken up for molecular dynamics simulation, the study resulted in favourable outcomes for three such ligands (compound ID 5469426, 69501714, ZINC000003874317). © 2023 Bharati Vidyapeeth, New Delhi.

Identification of key mutations responsible for the enhancement of receptor-binding affinity and immune escape of SARS-CoV-2 Omicron variant.

The Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has raised concerns worldwide due to its enhanced transmissibility and immune escapability. The first dominant Omicron BA.1 subvariant harbors more than 30 mutations in the spike protein from the prototype virus, of which 15 mutations are located at the receptor binding domain (RBD). These mutations in the RBD region attracted significant attention, which potentially enhance the binding of the receptor human angiotensin-converting enzyme 2 (hACE2) and decrease the potency of neutralizing antibodies/nanobodies. This study applied the molecular dynamics simulations combined with the molecular mechanics-generalized Born surface area (MMGBSA) method, to investigate the molecular mechanism behind the impact of the mutations acquired by Omicron on the binding affinity between RBD and hACE2. Our results indicate that five key mutations, i.e., N440K, T478K, E484A, Q493R, and G496S, contributed significantly to the enhancement of the binding affinity by increasing the electrostatic interactions of the RBD-hACE2 complex. Moreover, fourteen neutralizing antibodies/nanobodies complexed with RBD were used to explore the effects of the mutations in Omicron RBD on their binding affinities. The calculation results indicate that the key mutations E484A and Y505H reduce the binding affinities to RBD for most of the studied neutralizing antibodies/nanobodies, mainly attributed to the elimination of the original favorable gas-phase electrostatic and hydrophobic interactions between them, respectively. Our results provide valuable information for developing effective vaccines and antibody/nanobody drugs.

Structure-activity relationships of dihydropyrimidone inhibitors against native and auto-processed human neutrophil elastase.

BACKGROUND: Human neutrophil elastase (HNE) is a key driver of systemic and cardiopulmonary inflammation. Recent studies have established the existence of a pathologically active auto-processed form of HNE with reduced binding affinity against small molecule inhibitors. METHOD: AutoDock Vina v1.2.0 and Cresset Forge v10 software were used to develop a 3D-QSAR model for a series of 47 DHPI inhibitors. Molecular Dynamics (MD) simulations were carried out using AMBER v18 to study the structure and dynamics of sc (single-chain HNE) and tcHNE (two-chain HNE). MMPBSA binding free energies of the previously reported clinical candidate BAY 85-8501 and the highly active BAY-8040 were calculated with sc and tcHNE. RESULTS: The DHPI inhibitors occupy the S1 and S2 subsites of scHNE. The robust 3D-QSAR model showed acceptable predictive and descriptive capability with regression coefficient of r2 = 0.995 and cross-validation regression coefficient q2 = 0.579 for the training set. The key descriptors of shape, hydrophobics and electrostatics were mapped to the inhibitory activity. In auto-processed tcHNE, the S1 subsite undergoes widening and disruption. All the DHPI inhibitors docked with the broadened S1'-S2' subsites of tcHNE with lower AutoDock binding affinities. The MMPBSA binding free energy of BAY-8040 with tcHNE reduced in comparison with scHNE while the clinical candidate BAY 85-8501 dissociated during MD. Thus, BAY-8040 may have lower inhibitory activity against tcHNE whereas the clinical candidate BAY 85-8501 is likely to be inactive. CONCLUSION: SAR insights gained from this study will aid the future development of inhibitors active against both forms of HNE.

An optimized thermodynamics integration protocol for identifying beneficial mutations in antibody design.

Accurate identification of beneficial mutations is central to antibody design. Many knowledge-based (KB) computational approaches have been developed to predict beneficial mutations, but their accuracy leaves room for improvement. Thermodynamic integration (TI) is an alchemical free energy algorithm that offers an alternative technique for identifying beneficial mutations, but its performance has not been evaluated. In this study, we developed an efficient TI protocol with high accuracy for predicting binding free energy changes of antibody mutations. The improved TI method outperforms KB methods at identifying both beneficial and deleterious mutations. We observed that KB methods have higher accuracies in predicting deleterious mutations than beneficial mutations. A pipeline using KB methods to efficiently exclude deleterious mutations and TI to accurately identify beneficial mutations was developed for high-throughput mutation scanning. The pipeline was applied to optimize the binding affinity of a broadly sarbecovirus neutralizing antibody 10-40 against the circulating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) omicron variant. Three identified beneficial mutations show strong synergy and improve both binding affinity and neutralization potency of antibody 10-40. Molecular dynamics simulation revealed that the three mutations improve the binding affinity of antibody 10-40 through the stabilization of an altered binding mode with increased polar and hydrophobic interactions. Above all, this study presents an accurate and efficient TI-based approach for optimizing antibodies and other biomolecules.

Identification of core therapeutic targets for Monkeypox virus and repurposing potential of drugs against them: An in silico approach.

Monkeypox virus (mpox virus) outbreak has rapidly spread to 82 non-endemic countries. Although it primarily causes skin lesions, secondary complications and high mortality (1-10%) in vulnerable populations have made it an emerging threat. Since there is no specific vaccine/antiviral, it is desirable to repurpose existing drugs against mpox virus. With little knowledge about the lifecycle of mpox virus, identifying potential inhibitors is a challenge. Nevertheless, the available genomes of mpox virus in public databases represent a goldmine of untapped possibilities to identify druggable targets for the structure-based identification of inhibitors. Leveraging this resource, we combined genomics and subtractive proteomics to identify highly druggable core proteins of mpox virus. This was followed by virtual screening to identify inhibitors with affinities for multiple targets. 125 publicly available genomes of mpox virus were mined to identify 69 highly conserved proteins. These proteins were then curated manually. These curated proteins were funnelled through a subtractive proteomics pipeline to identify 4 highly druggable, non-host homologous targets namely; A20R, I7L, Top1B and VETFS. High-throughput virtual screening of 5893 highly curated approved/investigational drugs led to the identification of common as well as unique potential inhibitors with high binding affinities. The common inhibitors, i.e., batefenterol, burixafor and eluxadoline were further validated by molecular dynamics simulation to identify their best potential binding modes. The affinity of these inhibitors suggests their repurposing potential. This work can encourage further experimental validation for possible therapeutic management of mpox.

Investigating the antiviral therapeutic potentialities of marine polycyclic lamellarin pyrrole alkaloids as promising inhibitors for SARS-CoV-2 and Zika main proteases (Mpro).

The new coronavirus variant (SARS-CoV-2) and Zika virus are two world-wide health pandemics. Along history, natural products-based drugs have always crucially recognized as a main source of valuable medications. Considering the SARS-CoV-2 and Zika main proteases (Mpro) as the re-production key element of the viral cycle and its main target, herein we report an intensive computer-aided virtual screening for a focused list of 39 marine lamellarins pyrrole alkaloids, against SARS-CoV-2 and Zika main proteases (Mpro) using a set of combined modern computational methodologies including molecular docking (MDock), molecule dynamic simulations (MDS) and structure-activity relationships (SARs) as well. Indeed, the molecular docking studies had revealed four promising marine alkaloids including [lamellarin H (14)/K (17)] and [lamellarin S (26)/Z (39)], according to their notable ligand-protein energy scores and relevant binding affinities with the SARS-CoV-2 and Zika (Mpro) pocket residues, respectively. Consequentially, these four chemical hits were further examined thermodynamically though investigating their MD simulations at 100 ns, where they showed prominent stability within the accommodated (Mpro) pockets. Moreover, in-deep SARs studies suggested the crucial roles of the rigid fused polycyclic ring system, particularly aromatic A- and F- rings, position of the phenolic -OH and δ-lactone functionalities as essential structural and pharmacophoric features. Finally, these four promising lamellarins alkaloids were investigated for their in-silico ADME using the SWISS ADME platform, where they displayed appropriated drug-likeness properties. Such motivating outcomes are greatly recommending further in vitro/vivo examinations regarding those lamellarins pyrrole alkaloids (LPAs).Communicated by Ramaswamy H. Sarma.

Immunoinformatics Approaches in Designing Vaccines Against COVID-19.

Since the onset of the COVID-19 pandemic, a number of approaches have been adopted by the scientific communities for developing efficient vaccine candidate against SARS-CoV-2. Conventional approaches of developing a vaccine require a long time and a series of trials and errors which indeed limit the feasibility of such approaches for developing a dependable vaccine in an emergency situation like the COVID-19 pandemic. Hitherto, most of the available vaccines have been developed against a particular antigen of SARS-CoV, spike protein in most of the cases, and intriguingly, these vaccines are not effective against all the pathogenic coronaviruses. In this context, immunoinformatics-based reverse vaccinology approaches enable a robust design of efficacious peptide-based vaccines against all the infectious strains of coronaviruses within a short frame of time. In this chapter, we enumerate the methodological trajectory of developing a universal anti-SARS-CoV-2 vaccine, namely, "AbhiSCoVac," through advanced computational biology-based immunoinformatics approach and its in-silico validation using molecular dynamics simulations.

Identification and characterization of 7-azaindole derivatives as inhibitors of the SARS-CoV-2 spike-hACE2 protein interaction.

The COVID-19 pandemic, caused by SARS-CoV-2, has become a global public health crisis. The entry of SARS-CoV-2 into host cells is facilitated by the binding of its spike protein (S1-RBD) to the host receptor hACE2. Small molecule compounds targeting S1-RBD-hACE2 interaction could provide an alternative therapeutic strategy sensitive to viral mutations. In this study, we identified G7a as a hit compound that targets the S1-RBD-hACE2 interaction, using high-throughput screening in the SARS2-S pseudovirus model. To enhance the antiviral activity of G7a, we designed and synthesized a series of novel 7-azaindole derivatives that bind to the S1-RBD-hACE2 interface. Surprisingly, ASM-7 showed excellent antiviral activity and low cytotoxicity, as confirmed by pseudovirus and native virus assays. Molecular docking and molecular dynamics simulations revealed that ASM-7 could stably bind to the binding interface of S1-RBD-hACE2, forming strong non-covalent interactions with key residues. Furthermore, the binding of ASM-7 caused alterations in the structural dynamics of both S1-RBD and hACE2, resulting in a decrease in their binding affinity and ultimately impeding the viral invasion of host cells. Our findings demonstrate that ASM-7 is a promising lead compound for developing novel therapeutics against SARS-CoV-2.

Exploiting the potential of natural polyphenols as antivirals against monkeypox envelope protein F13 using machine learning and all-atoms MD simulations.

The re-emergence of monkeypox (MPX), in the era of COVID-19 pandemic is a new global menace. Regardless of its leniency, there are chances of MPX expediting severe health deterioration. The role of envelope protein, F13 as a critical component for production of extracellular viral particles makes it a crucial drug target. Polyphenols, exhibiting antiviral properties have been acclaimed as an effective alternative to the traditional treatment methods for management of viral diseases. To facilitate the development of potent MPX specific therapeutics, herein, we have employed state-of-the-art machine learning techniques to predict a highly accurate 3-dimensional structure of F13 as well as identify binding hotspots on the protein surface. Additionally, we have effectuated high-throughput virtual screening methodology on 57 potent natural polyphenols having antiviral activities followed by all-atoms molecular dynamics (MD) simulations, to substantiate the mode of interaction of F13 protein and polyphenol complexes. The structure-based virtual screening based on Glide SP, XP and MM/GBSA scores enables the selection of six potent polyphenols having higher binding affinity towards F13. Non-bonded contact analysis, of pre- and post- MD complexes propound the critical role of Glu143, Asp134, Asn345, Ser321 and Tyr320 residues in polyphenol recognition, which is well supported by per-residue decomposition analysis. Close-observation of the structural ensembles from MD suggests that the binding groove of F13 is mostly hydrophobic in nature. Taken together, this structure-based analysis from our study provides a lead on Myricetin, and Demethoxycurcumin, which may act as potent inhibitors of F13. In conclusion, our study provides new insights into the molecular recognition and dynamics of F13-polyphenol bound states, offering new promises for development of antivirals to combat monkeypox. However, further in vitro and in vivo experiments are necessary to validate these results.

Antibacterial Activity and in Silico Investigation of 2-[(3-Substitutedphenyl) Azomethine] Phenol as anti-SARS-CoV-2 Mpro and anti-Plasmodium falciparum Agents

Imine derivatives are widely used in medicine for the treatment of several diseases causing human infections;we examined Schiff's bases derivatives: 2-[(3-methylphenyl) azomethine] phenol (L1), 2-[(3-chlorophenyl) azomethine] phenol (L2) and 2-[(3-nitrophenyl) azomethine] phenol (L3) against three human pathogenic bacterial strains according to the disk diffusion test. In addition, to revealing the importances of the in silico study of these derivatives, in particular the molecular docking which is based on the protein structures: the main protease 3CL of SARS-CoV-2 and the aminopeptidase of the M1 family. Also, a molecular dynamics simulation was performed to examine the structural stability of the best docked conformation. The evaluation of the global reactivity parameters of the molecular system of Schiff base derivatives was applied by the DFT method with the hybrid functional (B3LYP)/6-31G (d) basis set. The results of the antibacterial activity showed a strong activity in the presence of the L3 ligand against Escherichia coli (ATCC 25922) with a diameter inhibition zone equal to 11 ± 0.61 mm. Molecular docking shows that the L3 ligand formed with protein targets more stable complexes by predicting interesting interactions: hydrogen, hydrophobic and electrostatic bonds with the residues of these targets 3CLpro and PfA-M1. Further, molecular dynamics simulations confirm a strong energy contribution with these interactions. Therefore, suggesting that our ligands could contribute to the development of anti-coronavirus-2 and anti-malarial drug properties. [ FROM AUTHOR] Copyright of Polycyclic Aromatic Compounds is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

In silico identification and validation of phenolic lipids as potential inhibitor against bacterial and viral strains.

The recurrence of coronavirus disease and bacterial resistant strains has drawn attention to naturally occurring bioactive molecules that can demonstrate broad-spectrum efficacy against bacteria as well as viral strains. The drug-like abilities of naturally available "anacardic acids" (AA) and their derivatives against different bacterial and viral protein targets through in-silico tools were explored. Three viral protein targets [P DB: 6Y2E (SARS-CoV-2), 1AT3 (Herpes) and 2VSM (Nipah)] and four bacterial protein targets [P DB: 2VF5 (Escherichia coli), 2VEG (Streptococcus pneumoniae), 1JIJ (Staphylococcus aureus) and 1KZN (E. coli)] were selected to evaluate the activity of bioactive AA molecules. The potential ability to inhibit the progression of microbes has been discussed based on the structure, functionality and interaction ability of these molecules on the selected protein targets for multi-disease remediation. The number of interactions, full-fitness value and energy of the ligand-target system were determined from the docked structure in SwissDock and Autodock Vina. In order to compare the efficacy of these active derivatives to that of commonly used drugs against bacteria and viruses, a few of the selected molecules were subjected to 100 ns long MD simulations. It was found that the phenolic groups and alkyl chains of AA derivatives are more likely to bind with microbial targets, that could be responsible for the improved activity against these targets. The results suggest that the proposed AA derivatives have demonstrated potential to become active drug ingredients against microbial protein targets. Further, experimental investigations are essential for clinical verification of the drug-like abilities of AA derivatives.Communicated by Ramaswamy H. Sarma.

In silico screening of chalcones and flavonoids as potential inhibitors against yellow head virus 3C-like protease.

Yellow head virus (YHV) is one of the most important pathogens in prawn cultivation. The outbreak of YHV could potentially result in collapses in aquaculture industries. Although a flurry of development has been made in searching for preventive and therapeutic approaches against YHV, there is still no effective therapy available in the market. Previously, computational screening has suggested a few cancer drugs to be used as YHV protease (3CLpro) inhibitors. However, their toxic nature is still of concern. Here, we exploited various computational approaches, such as deep learning-based structural modeling, molecular docking, pharmacological prediction, and molecular dynamics simulation, to search for potential YHV 3CLpro inhibitors. A total of 272 chalcones and flavonoids were in silico screened using molecular docking. The bioavailability, toxicity, and specifically drug-likeness of hits were predicted. Among the hits, molecular dynamics simulation and trajectory analysis were performed to scrutinize the compounds with high binding affinity. Herein, the four selected compounds including chalcones cpd26, cpd31 and cpd50, and a flavonoid DN071_f could be novel potent compounds to prevent YHV and GAV propagation in shrimp. The molecular mechanism at the atomistic level is also enclosed that can be used to further antiviral development.

In-silico study: docking simulation and molecular dynamics of peptidomimetic fullerene-based derivatives against SARS-CoV-2 Mpro.

COVID-19 is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, has become a global pandemic resulting in significant morbidity and mortality. This study presents 12 new peptidomimetic fullerene-based derivatives in three groups that are investigated theoretically as SARS-CoV-2 Mpro inhibitors to increase the chance of treating COVID-19. Studied compounds are designed and optimized at B88-LYP/DZVP method. Molecular descriptors results show the stability and reactivity of the compounds with Mpro, especially in the 3rd group (Ser compounds). However, Lipinski's Rule of Five values indicates that the compounds are not suitable as oral drugs. Furthermore, molecular docking simulations are carried out to investigate the binding affinity and interaction modes of the top five compounds (compounds 1, 9, 11, 2, and 10) with the Mpro protein, which have the lowest binding energy. Molecular dynamics simulations are also performed to evaluate the stability of the protein-ligand complexes with compounds 1 and 9 and compare them with natural substrate interaction. The analysis of RMSD, H-bonds, Rg, and SASA indicates that both compounds 1 (Gly-α acid) and 9 (Ser-α acid) have good stability and strong binding affinity with the Mpro protein. However, compound 9 shows slightly better stability and binding affinity compared to compound 1.

Marine drugs as putative inhibitors against non-structural proteins of SARS-CoV-2: an in silico study.

INTRODUCTION: Coronavirus disease 2019 (COVID-19) is an unprecedented pandemic, threatening human health worldwide. The need to produce novel small-molecule inhibitors against the ongoing pandemic has resulted in the use of drugs such as chloroquine, azithromycin, dexamethasone, favipiravir, ribavirin, remdesivir and azithromycin. Moreover, the reports of the clinical trials of these drugs proved to produce detrimental effects on patients with side effects like nephrotoxicity, retinopathy, cardiotoxicity and cardiomyopathy. Recognizing the need for effective and non-harmful therapeutic candidates to combat COVID-19, we aimed to develop promising drugs against SARS-COV-2. DISCUSSION: In the current investigation, high-throughput virtual screening was performed using the Comprehensive Marine Natural Products Database against five non-structural proteins: Nsp3, Nsp5, Nsp12, Nsp13 and Nsp15. Furthermore, standard precision (SP) docking, extra precision (XP) docking, binding free energy calculation and absorption, distribution, metabolism, excretion and toxicity studies were performed using the SchrÓ§dinger suite. The top-ranked 5 hits obtained by computational studies exhibited to possess a greater binding affinity with the selected non-structural proteins. Amongst the five hits, CMNPD5804, CMNPD20924 and CMNPD1598 hits were utilized to design a novel molecule (D) that has the capability of interacting with all the key residues in the pocket of the selected non-structural proteins. Furthermore, 200 ns of molecular dynamics simulation studies provided insight into the binding modes of D within the catalytic pocket of selected proteins. CONCLUSION: Hence, it is concluded that compound D could be a promising inhibitor against these non-structural proteins. Nevertheless, there is still a need to conduct in vitro and in vivo studies to support our findings.

Molecular insights to the binding interactions of APNS containing HIV-protease inhibitors against SARS-CoV-2 Mpro: an in silico approach towards drug repurposing.

SARS-CoV-2 Mpro is one of the most vital enzymes of the new coronavirus-2 (SARS-CoV-2) and is a crucial target for drug discovery. Unfortunately, there is not any potential drugs available to combat the action of SARS-CoV-2 Mpro. Based on the reports HIV-protease inhibitors can be applied against the SARS by targeting the SARS-CoV-1 Mpro, we have chosen few clinically trialed experimental and allophenylnorstatine (APNS) containing HIV-protease inhibitors (JE-2147, JE-533, KNI-227, KNI-272 & KNI-1931), to examine their binding affinities with SARS-CoV-2 Mpro and to assess their potential to check for a possible drug candidate against the protease. Here, we have chosen a methodology to understand the binding mechanism of these five inhibitors to SARS-CoV-2 Mpro by merging molecular docking, molecular dynamics (MD) simulation and MM-PBSA based free energy calculations. Our estimations disclose that JE-2147 is highly effective (ΔGBind = -28.31 kcal/mol) due to an increased favorable van der Waals (ΔEvdw) interactions and decreased solvation (ΔGsolv) energies between the inhibitor and viral protease. JE-2147 shows a higher level of interactions as compared to JE-533 (-6.85 kcal/mol), KNI-227 (-18.36 kcal/mol), KNI-272 (-15.69 kcal/mol) and KNI-1931 (-21.59 kcal/mol) against SARS-CoV-2 Mpro. Binding contributions of important residues (His41, Met49, Cys145, His164, Met165, Glu166, Pro168, Gln189, etc.) from the active site or near the active site regions with ≥1.0 kcal/mol suggest a potent binding of the inhibitors. It is anticipated that the current study of binding interactions of these APNS containing inhibitors can pitch some valuable insights to design the significantly effective anti-SARS-CoV-2 Mpro drugs.Communicated by Ramaswamy H. Sarma.

Investigating the novel acetonitrile derivatives as potential SARS-CoV-2 main protease inhibitor using molecular modeling approach.

The COVID-19 is declared a pandemic by World Health Organization (WHO). It causes respiratory illness which leads to oxygen deficiency; it has affected millions of lives all around the globe. It has also been observed that people with diabetes condition are more likely to have severe symptoms when infected with the SARS-CoV2. So, continued efforts are being taken to design and discover potential anti-covid drugs. Earlier, a study reveals that the acetonitrile (2-phenyl-4H-benzopyrimedo [2,1-b]-thiazol-4-yliden) derivatives have potential anti-diabetic activity. Hence, drugs repurpose approach was used to identify the potential acetonitrile derivative targeting the main protease of SARS-CoV2. Here, ADMET, molecular docking, and molecular dynamics simulation techniques were employed, to identify potential acetonitrile compounds against the main protease. The acetonitrile compounds (A to M) show the drug-likeness properties. Next, the molecular docking and dynamics simulation study reveals that acetonitrile compounds A, F, G, and L show a higher binding affinity and have an effect on the structure and dynamics of the main protease. Furthermore, binding energy calculations reveal that the acetonitrile derivative F has a higher binding affinity with the main protease and derivative L has a lower binding affinity with the main protease. The binding affinity of acetonitrile derivatives decreases in the order of F > A > G > L with the main protease. Thus, our computational modeling study provides valuable structural and energetic information of interaction of potential acetonitrile derivatives with the main protease which could be further used as potential lead molecules against the SARS-CoV2.Communicated by Ramaswamy H. Sarma.

Reporting dinaciclib and theodrenaline as a multitargeted inhibitor against SARS-CoV-2: an in-silico study.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is one of the rapid spreading coronaviruses that belongs to the Coronaviridae family. The rapidly evolving nature of SARS-CoV-2 results in a variety of variants with a capability of evasion to existing therapeutics and vaccines. So, there is an imperative need to discover potent drugs that can able to disrupt the function of multiple drug targets to tackle the SARS-CoV-2 menace. Here in this study, we took the different targets of SARS-CoV-2 prepared in the Schrodinger maestro. The library of the DrugBank database is screened against the selected crucial targets. Our molecular docking, Molecular Mechanics/Generalized Born Surface Area (MMGBSA), and molecular dynamics simulation studies led to identifying dinaciclib and theodrenaline as potential drugs against multiple drug targets: main protease, NSP15-endoribonuclease and papain-like-protease, of SARS-CoV-2. Dinaciclib with papain-like protease and NSP15-endoribonuclease show the docking score of -7.015 and -8.737, respectively, while the theodrenaline with NSP15-endoribonuclease and main protease produced the docking score of -8.507 and -7.289, respectively. Furthermore, the binding free energy calculations with MM/GBSA and molecular dynamics simulation studies of the complexes confirm the reliability of the drugs. The selected drugs are capable of binding to multiple targets simultaneously, thus withstanding their activity of target disruption in different variants of SARS-CoV-2. Although, the repurposed drugs are showing potent activity, but may need further in-vitro and in-vivo validations.Communicated by Ramaswamy H. Sarma.

Potential Mechanism of Colchicine against COVID-19 and Non-Small Cell Lung Cancer based on Network Pharmacology and Bioinformatics Analysis

Colchicine is an alkaloid with antitumor effect isolated from Colchicum autumnale plants, it has been reported in multiple studies as a potential treatment for coronavirus disease-19 and this study applied network pharmacology and bioinformatics analysis to explore the potential mechanism of colchicine against non-small cell lung cancer and coronavirus disease-19. The R software was used to determine the differentially expressed genes of non-small cell lung cancer/coronavirus disease-19, and carry out prognostic analysis and clinical analysis of the differentially expressed genes, the targets of colchicine were obtained from various databases, the protein-protein interaction network of intersection targets of colchicine and non-small cell lung cancer/coronavirus disease-19 was constructed, enrichment analysis of gene ontology and kyoto encyclopedia of genes and genomes pathways was performed by Metascape database and the molecular docking and molecular dynamics simulation were completed. We obtained a total of 716 differentially expressed genes and identified 13 potential prognostic genes associated with the clinical characterization of non-small cell lung cancer/coronavirus disease-19 patients. C-C motif chemokine ligand 2, toll like receptor 4, intercellular adhesion molecule 1, peroxisome proliferator activated receptor gamma, interleukin 17A, interferon gamma, angiotensin I converting enzyme, fos proto-oncogene, nuclear factor kappa B inhibitor alpha, TIMP metallopeptidase inhibitor 1 and secreted phosphoprotein 1 were core targets. The intersection targets of colchicine and non-small cell lung cancer/coronavirus disease-19 were mainly enriched in biological processes such as inflammatory response, response to cytokine and response to lipopolysaccharide, as well as signal pathways such as interleukin 17 signaling pathway, hypoxia inducible factor 1 signaling pathway and nucleotide binding oligomerization domain-like receptor signaling pathway. The results of molecular docking showed that the colchicine is better combined with the core targets. Analysis of molecular dynamics simulation showed that the protein and ligand form a stabilizing effect. Based on bioinformatics analysis and network pharmacology, we obtained biomarkers that may be used for the prognosis of non-small cell lung cancer/coronavirus disease-19 patients and revealed that colchicine may play a potential role in the treatment of non-small cell lung cancer/coronavirus disease-19 by regulating multiple targets and multiple signaling pathways and participating in multiple biological processes.

Influence of natural ventilation design on the dispersion of pathogen-laden droplets in a coach bus.

Natural ventilation is an energy-efficient design approach to reduce infection risk (IR), but its optimized design in a coach bus environment is less studied. Based on a COVID-19 outbreak in a bus in Hunan, China, the indoor-outdoor coupled CFD modeling approach is adopted to comprehensively explore how optimized bus natural ventilation (e.g., opening/closing status of front/middle/rear windows (FW/MW/RW)) and ceiling wind catcher (WCH) affect the dispersion of pathogen-laden droplets (tracer gas, 5 µm, 50 µm) and IR. Other key influential factors including bus speed, infector's location, and ambient temperature (Tref) are also considered. Buses have unique natural ventilation airflow patterns: from bus rear to front, and air change rate per hour (ACH) increases linearly with bus speed. When driving at 60 km/h, ACH is only 6.14 h-1 and intake fractions of tracer gas (IFg) and 5 µm droplets (IFd) are up to 3372 ppm and 1394 ppm with ventilation through leakages on skylights and no windows open. When FW and RW are both open, ACH increases by 43.5 times to 267.50 h-1, and IFg and IFd drop rapidly by 1-2 orders of magnitude compared to when no windows are open. Utilizing a wind catcher and opening front windows significantly increases ACH (up to 8.8 times) and reduces IF (5-30 times) compared to only opening front windows. When the infector locates at the bus front with FW open, IFg and IFd of all passengers are <10 ppm. More droplets suspend and further spread in a higher Tref environment. It is recommended to open two pairs of windows or open front windows and utilize the wind catcher to reduce IR in coach buses.