Computational Determination of Potential Multiprotein Targeting Natural Compounds for Rational Drug Design Against SARS-COV-2.

SARS-CoV-2 caused the current COVID-19 pandemic and there is an urgent need to explore effective therapeutics that can inhibit enzymes that are imperative in virus reproduction. To this end, we computationally investigated the MPD3 phytochemical database along with the pool of reported natural antiviral compounds with potential to be used as anti-SARS-CoV-2. The docking results demonstrated glycyrrhizin followed by azadirachtanin, mycophenolic acid, kushenol-w and 6-azauridine, as potential candidates. Glycyrrhizin depicted very stable binding mode to the active pocket of the Mpro (binding energy, -8.7 kcal/mol), PLpro (binding energy, -7.9 kcal/mol), and Nucleocapsid (binding energy, -7.9 kcal/mol) enzymes. This compound showed binding with several key residues that are critical to natural substrate binding and functionality to all the receptors. To test docking prediction, the compound with each receptor was subjected to molecular dynamics simulation to characterize the molecule stability and decipher its possible mechanism of binding. Each complex concludes that the receptor dynamics are stable (Mpro (mean RMSD, 0.93 Å), PLpro (mean RMSD, 0.96 Å), and Nucleocapsid (mean RMSD, 3.48 Å)). Moreover, binding free energy analyses such as MMGB/PBSA and WaterSwap were run over selected trajectory snapshots to affirm intermolecular affinity in the complexes. Glycyrrhizin was rescored to form strong affinity complexes with the virus enzymes: Mpro (MMGBSA, -24.42 kcal/mol and MMPBSA, -10.80 kcal/mol), PLpro (MMGBSA, -48.69 kcal/mol and MMPBSA, -38.17 kcal/mol) and Nucleocapsid (MMGBSA, -30.05 kcal/mol and MMPBSA, -25.95 kcal/mol), were dominated mainly by vigorous van der Waals energy. Further affirmation was achieved by WaterSwap absolute binding free energy that concluded all the complexes in good equilibrium and stability (Mpro (mean, -22.44 kcal/mol), PLpro (mean, -25.46 kcal/mol), and Nucleocapsid (mean, -23.30 kcal/mol)). These promising findings substantially advance our understanding of how natural compounds could be shaped to counter SARS-CoV-2 infection.

Molecular Insights into Binding Mode and Interactions of Structure-Based Virtually Screened Inhibitors for Pseudomonas aeruginosa Multiple Virulence Factor Regulator (MvfR).

Multi-drug resistance (MDR) bacterial pathogens pose a threat to global health and warrant the discovery of new therapeutic molecules, particularly those that can neutralize their virulence and stop the evolution of new resistant mechanisms. The superbug nosocomial pathogen, Pseudomonas aeruginosa, uses a multiple virulence factor regulator (MvfR) to regulate the expression of multiple virulence proteins during acute and persistent infections. The present study targeted MvfR with the intention of designing novel anti-virulent compounds, which will function in two ways: first, they will block the virulence and pathogenesis P. aeruginosa by disrupting the quorum-sensing network of the bacteria, and second, they will stop the evolution of new resistant mechanisms. A structure-based virtual screening (SBVS) method was used to screen druglike compounds from the Asinex antibacterial library (~5968 molecules) and the comprehensive marine natural products database (CMNPD) (~32 thousand compounds), against the ligand-binding domain (LBD) of MvfR, to identify molecules that show high binding potential for the relevant pocket. In this way, two compounds were identified: Top-1 (4-((carbamoyloxy)methyl)-10,10-dihydroxy-2,6-diiminiodecahydropyrrolo[1,2-c]purin-9-yl sulfate) and Top-2 (10,10-dihydroxy-2,6-diiminio-4-(((sulfonatocarbamoyl)oxy)methyl)decahydropyrrolo[1,2-c]purin-9-yl sulfate), in contrast to the co-crystallized M64 control. Both of the screened leads were found to show deep pocket binding and interactions with several key residues through a network of hydrophobic and hydrophilic interactions. The docking results were validated by a long run of 200 ns of molecular dynamics simulation and MM-PB/GBSA binding free energies. All of these analyses confirmed the presence of strong complex formation and rigorous intermolecular interactions. An additional analysis of normal mode entropy and a WaterSwap assay were also performed to complement the aforementioned studies. Lastly, the compounds were found to show an acceptable range of pharmacokinetic properties, making both compounds potential candidates for further experimental studies to decipher their real biological potency.

Promising terpenes as SARS-CoV-2 spike receptor-binding domain (RBD) attachment inhibitors to the human ACE2 receptor: Integrated computational approach.

The spike protein receptor binding domain (S-RBD) is a necessary corona-viral protein for binding and entry of coronaviruses (COVs) into the host cells. Hence, it has emerged as an attractive antiviral drug target. Therefore, present study was aimed to target severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) S-RBD with novel bioactive compounds to retrieve potential candidates that could serve as anti-coronavirus disease 2019 (COVID-19) drugs. In this paper, computational approaches were employed, especially the structure-based virtual screening followed by molecular dynamics (MD) simulation as well as binding energy analysis for the computational identification of specific terpenes from the medicinal plants, which can block SARS-CoV-2 S-RBD binding to Human angiotensin-converting enzyme 2 (H-ACE2) and can act as potent anti-COVID-19 drugs after further advancements. The screening of focused terpenes inhibitors database composed of ~1000 compounds with reported therapeutic potential resulted in the identification of three candidate compounds, NPACT01552, NPACT01557 and NPACT00631. These three compounds established conserved interactions, which were further explored through all-atom MD simulations, free energy calculations, and a residual energy contribution estimated by MM-PB(GB)SA method. All these compounds showed stable conformation and interacted well with the hot-spot residues of SARS-CoV-2 S-RBD. Conclusively, the reported SARS-CoV-2 S-RBD specific terpenes could serve as seeds for developing potent anti-COVID-19 drugs. Importantly, the experimentally tested glycyrrhizin (NPACT00631) against SARS-CoV could be used further in the fast-track drug development process to help curb COVID-19.

Promising Terpenes as Natural Antagonists of Cancer: An In-Silico Approach.

Overexpression of murine double minute 2 (MDM2) results in the inactivation of p53 and causes cancer which is a leading cause of death in recent era. In recent decades, much attention has been paid to discover potential inhibitors against MDM2 in order to cure cancer. Outcomes from studies proposes that the MDM2 is a hot target to screen potent antagonists. Thus, this study aims at discovering natural compounds using several computational approaches to inhibit the MDM2 and to eliminate p53-MDM2 interaction, which would result in the reactivation of p53 activity. A library of 500 terpenes was prepared and several virtual screening approaches were employed to find out the best hits which could serve as p53-MDM2 antagonists. On the basis of the designed protocol, three terpenes were selected. In the present study, for the stability and validation of selected three protein-ligand complexes 20 ns molecular dynamics simulations and principal component analyses (PCA) were performed. Results found that the selected terpenes hits (3-trans-p-coumaroyl maslinic acid, Silvestrol and Betulonic acid) are potential inhibitors of p53-MDM2 interaction and could serve as potent antagonists.

Proteomics studies on stress responses in diatoms.

Diatoms are a highly diverse group of eukaryotic phytoplankton that are distributed throughout marine and freshwater environments and are believed to be responsible for approximately 40% of the total marine primary productivity. The ecological success of diatoms suggests that they have developed a range of strategies to cope with various biotic and abiotic stress factors. It is of great interest to understand the adaptive responses of diatoms to different stresses in the marine environment. Proteomic technologies have been applied to the adaptive responses of marine diatoms under different growth conditions in recent years such as nitrogen starvation, iron limitation and phosphorus deficiency. These studies have provided clues to elucidate the sophisticated sensing mechanisms that control their adaptive responses. Although only a very limited number of proteomic studies were conducted in diatoms, the obtained data have led to a better understanding of the biochemical processes that contribute to their ecological success. This review presents the current status of proteomic studies of diatom stress responses and discusses the novel developments and applications for the analysis of protein post-translational modification in diatoms. The potential future application of proteomics could contribute to a better understanding of the physiological mechanisms underlying diatom acclimation to a given stress and the acquisition of an enhanced diatom stress tolerance. Future challenges and research opportunities in the proteomics studies of diatoms are also discussed.

Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulation Analysis Reveal Insights into the Molecular Mechanism of Cordia myxa in the Treatment of Liver Cancer.

Traditional treatments of cancer have faced various challenges, including toxicity, medication resistance, and financial burdens. On the other hand, bioactive phytochemicals employed in complementary alternative medicine have recently gained interest due to their ability to control a wide range of molecular pathways while being less harmful. As a result, we used a network pharmacology approach to study the possible regulatory mechanisms of active constituents of Cordia myxa for the treatment of liver cancer (LC). Active constituents were retrieved from the IMPPAT database and the literature review, and their targets were retrieved from the STITCH and Swiss Target Prediction databases. LC-related targets were retrieved from expression datasets (GSE39791, GSE76427, GSE22058, GSE87630, and GSE112790) through gene expression omnibus (GEO). The DAVID Gene Ontology (GO) database was used to annotate target proteins, while the Kyoto Encyclopedia and Genome Database (KEGG) was used to analyze signaling pathway enrichment. STRING and Cytoscape were used to create protein-protein interaction networks (PPI), while the degree scoring algorithm of CytoHubba was used to identify hub genes. The GEPIA2 server was used for survival analysis, and PyRx was used for molecular docking analysis. Survival and network analysis revealed that five genes named heat shot protein 90 AA1 (HSP90AA1), estrogen receptor 1 (ESR1), cytochrome P450 3A4 (CYP3A4), cyclin-dependent kinase 1 (CDK1), and matrix metalloproteinase-9 (MMP9) are linked with the survival of LC patients. Finally, we conclude that four extremely active ingredients, namely cosmosiin, rosmarinic acid, quercetin, and rubinin influence the expression of HSP90AA1, which may serve as a potential therapeutic target for LC. These results were further validated by molecular dynamics simulation analysis, which predicted the complexes with highly stable dynamics. The residues of the targeted protein showed a highly stable nature except for the N-terminal domain without affecting the drug binding. An integrated network pharmacology and docking study demonstrated that C. myxa had a promising preventative effect on LC by working on cancer-related signaling pathways.

Identification of novel inhibitors against VP40 protein of Marburg virus by integrating molecular modeling and dynamics approaches.

Marburg virus (MV) is a highly etiological agent of haemorrhagic fever in humans and has spread across the world. Its outbreaks caused a 23-90% human death rate. However, there are currently no authorized preventive or curative measures yet. VP40 is the MV matrix protein, which builds protein shell underneath the viral envelope and confers hallmark filamentous. VP40 alone is able to induce assembly and budding of filamentous virus-like particles (VLPs), which resemble authentic virions. As a result, this research is credited with clarifying the function of VP40 and leading to the discovery of new therapeutic targets effective in combating MV disease (MVD). Virtual screening, molecular docking and molecular dynamics (MD) simulation were used to find the putative active chemicals based on a 3D pharmacophore model of the protein's active site cavity. Initially, andrographidine-C, a potent inhibitor was selected for the development of the pharmacophore model. Later, a library of 30,000 compounds along with the andrographidine-C was docked against VP40 protein. Three best hits including avanafil, diuvaretin and macrourone were subjected to further MD simulation analysis, as these compounds had better binding affinities as compared to andrographidine-C. Furthermore, throughout the 100 ns simulations, the back bone of VP40 protein in presence of avanafil, diuvaretin and macrourone remained stable which was further validated by MM-PBSA analysis. Additionally, all of these compounds depict maximum drug-like properties. The predicted drugs based on the ligand, avanafil, diuvaretin and macrourone could be exploited and developed as an alternative or complementary therapy for the treatment of MVD.Communicated by Ramaswamy H. Sarma.

Sociodemographic and Diabetes-related Risk Factors in San Diego County, California.

BACKGROUND: The research information would enable clinicians and public health professionals to formulate proper interventions for diabetic people according to age, gender, and race. OBJECTIVE: The aim of the study was to investigate the relationship between diabetes-related mortality, hospitalization and emergency department discharge, and sociodemographic characteristics, in addition to age-standardized mortality rate analysis. METHOD: A population-based cross-sectional descriptive study was carried out to determine the relationship between sociodemographic characteristics and diabetes-related risk factors of the San Diego County residents in 2018, including 49,283 individuals (27,366 males and 21,917 females). RESULTS: The outcomes were found to be statistically significant. Hospitalization and emergency department discharges among males and females were statistically significant. The statistical differences between gender and mortality were not significant. The mortality was not significant in the male group, while it was statistically significant in the female group. The noted agestandardized mortality rate of diabetes stood at 85.8 deaths per 100,000 standard population. CONCLUSION: This study found that mortality increases as people age, and 85% of deaths were found to be of people older than 65 years. The mortality was two times higher among white and Hispanic males than females. Findings from this study are important in understanding the sociodemographic characteristics at the county level, which can inform diabetes mortality prevention efforts.

Utilization of aqueous broccoli florets extract for green synthesis and characterization of silver nanoparticles, with potential biological applications.

The process of creating nanoparticles using chemicals is not eco-friendly. However, a more environmentally conscious approach known as green chemistry, which involves using vegetable-mediated nanoparticle production, combines nanotechnology with biotechnology. In this study, the researchers aimed to assess the effectiveness of the green chemistry technique in producing silver nanoparticles using an liquid extract from broccoli florets (Brassica oleracea) under ideal environment. The successful production of silver nanoparticles was achieved through silver nitrate (AgNO3) biological reduction with the help of an aqueous broccoli florets extract at a slightly acidic pH of 6-7. The silver nanoparticles occurrence was shown by a change of color that moved from colorless to reddish-brown. To characterize the green-produced nanoparticles, various analytical techniques such as Ultraviolet-Visible Spectroscopy (UV-VIS), Fourier Transform Infrared Spectroscopy (FT-IR), X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), and Energy-Dispersive X-ray Spectroscopy (EDAX) were employed. The antioxidant properties of the formed silver nanoparticles (AgNPs) were examined in vitro using the 2,2-diphenyl-1-picrylhydrazyl (DPPH) and Ferric Reducing Antioxidant Power (FRAP) tests. Additionally, the antibacterial properties of AgNPs against various pathogenic bacteria was evaluated. The reduction procedure was easy and simple manageable, with UV-Vis spectroscopy indicating the surface plasmon resonance (SPR) presence at 425 nm. FTIR was utilized to identify active chemical groups in the biomass before and after reduction. SEM and X-ray diffraction analyses indicated that the silver nanoparticles had an average the size of individual particles of 33 nm and exhibited a face-centered cubic (FCC) structure. EDAX analysis confirmed the occurrence of elemental silver in the nanoparticles. The study demonstrated that the biosynthesis of AgNPs led to significant variations in antioxidant activity, which was dose-dependent and showed a similar pattern to the testing of the scarfing action of the ascorbic acid against free radicals using DPPH and FRAP. The AgNPs also dispalyed firm deep-spectrum antibacterial action observed against the tested pathogenic bacteria, outperforming certain medications. Interestingly, the silver nanoparticles remained stable at ambient temperature for 25 days without precipitation, retaining their antioxidant and antibacterial properties. In conclusion, the research findings suggest that an aqueous extract of fresh broccoli florets can serve as a viable and environmentally friendly method for producing stable silver nanoparticles with beneficial antioxidant and antibacterial characteristics.

Development of a Novel Vaccine Candidates against Cardiobacterium valvarum through Reverse Vaccinology and Computational Approaches.

Antibiotic resistance is a major public health concern that has resulted in high healthcare costs, increased mortality, and the emergence of novel bacterial diseases. Cardiobacterium valvarum, an antibiotic-resistant bacterium, is one of the leading causes of heart disease. Currently, there is no licensed vaccination against C. valvarum. In this research, an in silico-based vaccine was designed against C. valvarum using reverse vaccinology, bioinformatics, and immunoinformatics techniques. 4206 core proteins, 2027 nonredundant proteins, and 2179 redundant proteins were predicted. Among nonredundant proteins, 23 proteins were predicted in an extracellular membrane, 30 in the outer membrane, and 62 in the periplasmic membrane region. After applying several subtractive proteomics filters, two proteins, TonB-dependent siderophore receptor and hypothetical protein, were chosen for epitope prediction. In the epitope selection phase, B and T-cellepitopes were analyzed and shortlisted for vaccine design. The vaccine model was designed by linking selected epitopes with GPGPG linkers to avoid flexibility. Furthermore, the vaccine model was linked to cholera toxin B adjuvant to induce a proper immune response. The docking approach was utilized to analyze binding affinity to immune cell receptors. Molecular docking results predicted 12.75 kcal/mol for a Vaccine with MHC-I, 6.89 for a vaccine with MHC-II, and 19.51 vaccine with TLR-4. The MMGBSA estimated -94, -78, and -76 kcal/mol for TLR-4 and vaccine, MHC-I and vaccine, and MHC-II and vaccine, while the MMPBSA analysis estimated -97, -61, and -72 kcal/mol for TLR-4 with the vaccine, MHC-I with vaccine, and MHC-II with a vaccine. Molecular dynamic simulation analysis revealed that the designed vaccine construct has proper stability with immune cell receptors as it is essential for inducing an immune response. In conclusion, we observed that the model vaccine candidate has the potency to induce an immune response in the host. However, the study is designed purely on a computational basis; hence, experimental validation is strongly recommended.

Computational Modeling and Evaluation of Potential mRNA and Peptide-Based Vaccine against Marburg Virus (MARV) to Provide Immune Protection against Hemorrhagic Fever.

A hemorrhagic fever caused by the Marburg virus (MARV) belongs to the Filoviridae family and has been classified as a risk group 4 pathogen. To this day, there are no approved effective vaccinations or medications available to prevent or treat MARV infections. Reverse vaccinology-based approach was formulated to prioritize B and T cell epitopes utilizing a numerous immunoinformatics tools. Potential epitopes were systematically screened based on various parameters needed for an ideal vaccine such as allergenicity, solubility, and toxicity. The most suitable epitopes capable of inducing immune response were shortlisted. Epitopes with population coverage of 100% and fulfilling set parameters were selected for docking with human leukocyte antigen molecules, and binding affinity of each peptide was analyzed. Finally, 4 CTL and HTL each while 6 B cell 16-mers were used for designing multiepitope subunit (MSV) and mRNA vaccine joined via suitable linkers. Immune simulations were used to validate the constructed vaccine's capacity to induce a robust immune response whereas molecular dynamics simulations were used to confirm epitope-HLA complex stability. Based on these parameter's studies, both the vaccines constructed in this study offer a promising choice against MARV but require further experimental verification. This study provides a rationale point to begin with the development of an efficient vaccine against Marburg virus; however, the findings need further experimental validation to confirm the computational finding of this study.

Structural Dynamics of P-Rex1 Complexed with Natural Leads Establishes the Protein as an Attractive Target for Therapeutics to Suppress Cancer Metastasis.

Phosphatidylinositol 3,4,5-trisphosphate- (PIP3-) dependent Rac exchanger 1 (P-Rex1) functions as Rho guanine nucleotide exchange factor and is activated by synergistic activity of Gßγ and PIP3 of the heterotrimeric G protein. P-Rex1 activates Rac GTPases for regulating cell invasion and migration and promotes metastasis in several human cancers including breast, prostate, and skin cancer. The protein is a promising therapeutic target because of its multifunction roles in human cancers. Herein, the present study attempts to identify selective P-Rex1 natural inhibitors by targeting PIP3-binding pocket using large-size multiple natural molecule libraries. Each library was filtered subsequently in FAF-Drugs4 based on Lipinski's rule of five (RO5), toxicity, and filter pan assay interference compounds (PAINS). The output hits were virtually screened at the PIP3-binding pocket through PyRx AutoDock Vina and cross-checked by GOLD. The best binders at the PIP3-binding pocket were prioritized using a comparative analysis of the docking scores. Top-ranked two compounds with high GOLD fitness score (>80) and lowest AutoDock binding energy (< -12.7 kcal/mol) were complexed and deciphered for molecular dynamics along with control-P-Rex1 complex to validate compound binding conformation and disclosed binding interaction pattern. Both the systems were seen in good equilibrium, and along the simulation time, the compounds are in strong contact with the P-Rex1 PIP3-binding site. Hydrogen bonding analysis towards simulation end identified the formation of 16 and 22 short- and long-distance hydrogen bonds with different percent of occupancy to the PIP3 residues for compound I and compound 2, respectively. Radial distribution function (RDF) analysis of the key hydrogen bonds between the compound and the PIP3 residues demonstrated a strong affinity of the compounds to the mentioned PIP3 pocket. Additionally, MMGB/PBSA energies were performed that confirmed the dominance of Van der Waals energy in complex formation along with favorable contribution from hydrogen bonding. These findings were also cross-validated by a more robust WaterSwap binding energy predictor, and the results are in good agreement with a strong binding affinity of the compounds for the protein. Lastly, the key contribution of residues in interaction with the compounds was understood by binding free energy decomposition and alanine scanning methods. In short, the results of this study suggest that P-Rex1 is a good druggable target to suppress cancer metastasis; therefore, the screened druglike molecules of this study need in vitro and in vivo anti-P-Rex1 validation and may serve as potent leads to fight cancer.

Computational study to investigate Proteus mirabilis proteomes for multi-epitope vaccine construct design.

Proteus mirabilis is a gram-negative bacterium particularly known for its unique swarming ability. The swarming gives the bacteria ability to enhance adherence to the catheter surface and epithelium cells of the urethra to cause catheter associated urinary tract infections. P. mirabilis has evolved resistant to antibiotics. Additionally, there is an approved vaccine against P. mirabilis, thus demanding for identification of new vaccine targets. This gram-negative bacterium consists of 19,502 core proteins, out of which 19,063 are redundant proteins and remaining 439 are non-redundant proteins. The non-redundant proteins have 21 proteins present on the cell surface out of which 11 proteins are virulent. Antigenicity analysis predicted only 2 proteins as antigenic (fimbrial biogenesis outer membrane usher protein and ligand-gated channel protein). Four and seven B-cells epitopes were predicted from the former and later proteins, respectively. The predicted B-cells epitopes were used for T- cells epitopes prediction. The predicted epitopes were linked to each other through GPGPG linkers and joined with cholera toxin beta subunit adjuvant. A multi-epitopes vaccine construct consisting of 226 residues was docked with MHC-I, MHC-II and TLR-4. The best docked complex in each case has binding energy of -714.6, -744.6 and -829.5 kcal/mol, respectively. Moreover, the docking results were validated through molecular dynamics simulation and binding free energies estimation. The net energy of -137.2 kcal/mol was calculated for vaccine-MHC-I complex, -133.39 kcal/mol for vaccine-MHC-II and -158.68 kcal/mol for vaccine-TLR-4 complex. The designed vaccine construct could provoke immune responses against targeted pathogen and may be used in experimental testing.Communicated by Ramaswamy H. Sarma.

Computational Investigations of Traditional Chinese Medicinal Compounds against the Omicron Variant of SARS-CoV-2 to Rescue the Host Immune System.

Macrodomain-I of the NSP3 (non-structural protein 3) is responsible for immune response hijacking in the SARS-CoV-2 infection known as COVID-19. In the omicron variant (B.1.1.529), this domain harbors a new mutation, V1069I, which may increase the binding of ADPr and consequently the infection severity. This macrodomain-I, due to its significant role in infection, is deemed to be an important drug target. Hence, using structural bioinformatics and molecular simulation approaches, we performed a virtual screening of the traditional Chinese medicines (TCM) database for potential anti-viral drugs. The screening of 57,000 compounds yielded the 10 best compounds with docking scores better than the control ADPr. Among the top ten, the best three hits-TCM42798, with a docking score of -13.70 kcal/mol, TCM47007 of -13.25 kcal/mol, and TCM30675 of -12.49 kcal/mol-were chosen as the best hits. Structural dynamic features were explored including stability, compactness, flexibility, and hydrogen bonding, further demonstrating the anti-viral potential of these hits. Using the MM/GBSA approach, the total binding free energy for each complex was reported to be -69.78 kcal/mol, -50.11 kcal/mol, and -47.64 kcal/mol, respectively, which consequently reflect the stronger binding and inhibitory potential of these compounds. These agents might suppress NSP3 directly, allowing the host immune system to recuperate. The current study lays the groundwork for the development of new drugs to combat SARS-CoV-2 and its variants.

Integrated computer-aided drug design and biophysical simulation approaches to determine natural anti-bacterial compounds for Acinetobacter baumannii.

Acinetobacter baumannii is a nosocomial bacterial pathogen and is responsible for a wide range of diseases including pneumonia, necrotizing fasciitis, meningitis, and sepsis. The enzyme 5-enolpyruvylshikimate-3-phosphate (EPSP) synthase (encoded by aroA gene) in ESKAPE pathogens catalyzes the sixth step of shikimate pathway. The shikimate pathway is an attractive drug targets pathway as it is present in bacteria but absent in humans. As EPSP is essential for the A. baumannii growth and needed during the infection process, therefore it was used as a drug target herein for high-throughput screening of a comprehensive marine natural products database (CMNPD). The objective was to identify natural molecules that fit best at the substrate binding pocket of the enzyme and interact with functionally critical residues. Comparative assessment of the docking scores allowed selection of three compounds namely CMNPD31561, CMNPD28986, and CMNPD28985 as best binding molecules. The molecules established a balanced network of hydrophobic and hydrophilic interactions, and the binding pose remained in equilibrium throughout the length of molecular simulation time. Radial distribution function (RDF) analysis projected key residues from enzyme active pocket which actively engaged the inhibitors. Further validation is performed through binding free energies estimation that affirms very low delta energy of <-22 kcal/mol in MM-GBSA method and <-12 kcal/mol in MM-PBSA method. Lastly, the most important active site residues were mutated and their ligand binding potential was re-investigated. The molecules also possess good druglike properties and better pharmacokinetics. Together, these findings suggest the potential biological potency of the leads and thus can be used by experimentalists in vivo and in vitro studies.

mRNA-Based Vaccine Designing against Epstein-Barr Virus to Induce an Immune Response Using Immunoinformatic and Molecular Modelling Approaches.

Epstein-Barr Virus (EBV) is a human pathogen that has a morbidity rate of 90% in adults worldwide. Infectious mononucleosis is caused by EBV replication in B cells and epithelial cells of the host. EBV has also been related to autoimmune illnesses, including multiple sclerosis and cancers like nasopharyngeal carcinomas and Burkitt's lymphoma. Currently, no effective medications or vaccinations are available to treat or prevent EBV infection. Thus, the current study focuses on a bioinformatics approach to design an mRNA-based multi-epitope (MEV) vaccine to prevent EBV infections. For this purpose, we selected six antigenic proteins from the EBV proteome based on their role in pathogenicity to predict, extract, and analyze T and B cell epitopes using immunoinformatics tools. The epitopes were directed through filtering parameters including allergenicity, toxicity, antigenicity, solubility, and immunogenicity assessment, and finally, the most potent epitopes able to induce T and B cell immune response were selected. In silico molecular docking of prioritized T cell peptides with respective Human Leukocytes Antigens molecules, were carried out to evaluate the individual peptide's binding affinity. Six CTL, four HTL, and ten linear B cell epitopes fulfilled the set parameters and were selected for MEV-based mRNA vaccine. The prioritized epitopes were joined using suitable linkers to improve epitope presentation. The immune simulation results affirmed the designed vaccine's capacity to elicit a proper immune response. The MEV-based mRNA vaccine constructed in this study offers a promising choice for a potent vaccine against EBV.

Novel Chimeric Vaccine Candidate Development against Leptotrichia buccalis.

The misuse of antibiotics in our daily lives has led to the emergence of antimicrobial resistance. As a result, many antibiotics are becoming ineffective. This phenomenon is linked with high rates of mortality and morbidity. Therefore, new approaches are required to address this major health issue. Leptotrichia buccalis is a Gram-negative, rod-shaped bacterium which normally resides in the oral and vaginal cavities. It is an emerging bacterial pathogen which is developing new antibiotic-resistance mechanisms. No approved vaccine is available against this pathogen, which is a cause for growing concern. In this study, an in silico-based, multi-epitopes vaccine against this pathogen was designed by applying reverse vaccinology and immunoinformatic approaches. Of a total of 2193 predicted proteins, 294 were found to be redundant while 1899 were non-redundant. Among the non-redundant proteins, 6 were predicted to be present in the extracellular region, 12 in the periplasmic region and 23 in the outer-membrane region. Three proteins (trypsin-like peptidase domain-containing protein, sel1 repeat family protein and TrbI/VirB10 family protein) were predicted to be virulent and potential subunit vaccine targets. In the epitopes prediction phase, the three proteins were subjected to B- and T-cell epitope mapping; 19 epitopes were used for vaccine design. The vaccine construct was docked with MHC-I, MHC-II and TLR-4 immune receptors and only the top-ranked complex (based on global energy value) was selected in each case. The selected docked complexes were examined in a molecular dynamic simulation and binding free energies analysis in order to assess their intermolecular stability. It was observed that the vaccine binding mode with receptors was stable and that the system presented stable dynamics. The net binding free energy of complexes was in the range of -300 to -500 kcal/mol, indicating the formation of stable complexes. In conclusion, the data reported herein might help vaccinologists to formulate a chimeric vaccine against the aforementioned target pathogen.

Structural basis of UDP-N-acetylglucosamine pyrophosphorylase and identification of promising terpenes to control Aedes aegypti.

According to the world health organization (WHO) 2020 report, vector borne diseases account for 17 % of all infections with reported 700 thousand death each year. They are of considerable importance to health professionals as they are posing a serious health threat and include dengue fever, Zika fever, chikungunya, yellow fever, and other disease agents. Aedes aegypti serve as a vector for transmitting several of these tropical fevers. In the present study, UDP-N-acetylglucosamine pyrophosphorylase enzyme (Aa-UAP) of A. aegypti which plays a significant contribution in chitin metabolism is targeted with natural terpenes to propose an eco-friendly and novel candidates for the development of new insecticides. The three dimensional Aa-UAP structure was constructed via a comparative homology approach and validated, followed by structure-based virtual screening against 1000 terpenes collected from natural MDP3 and NPACT databases. Top hits were subjected to molecular dynamics (MD) simulations and binding free energies analysis to elucidate complex intermolecular stability and affinity over simulated time. The results demonstrated that Aa-UAP possesses a homodimer state and its active site residues are well conserved. Three compounds (NPACT00138, NPACT00452, and NPACT00839) were prioritized as they are establishing conserved and stable interactions with the active binding-site residues of Aa-UAP. Conclusively, the reported Aa-UAP specific terpenes could serve as promising leads in order to develop potential insecticides. Importantly, the FDA approved drug NPACT00839 (Paclitaxel) could be used further in the fast-track experimental testing pipeline for biological optimization.

Natural products for treatment of Plasmodium falciparum malaria: An integrated computational approach.

Malaria is a life-threatening infectious disease with an estimated 229 million cases in the year 2019 worldwide. Plasmodium falciparum 1-deoxy-d-xylulose-5-phosphate reductoisomerase (PfDXR) is one of the key enzymes in the biosynthetic pathway of isoprenoid, (required for parasite growth and survival) and considered as an attractive target for designing anti-malarial drugs. Fosmidomycin is an effective DXR inhibitor and has been proven effective and safe against P. falciparum in clinical trials. However, due to low bioavailability and inappropriate drug attributes, it is not a preferred option. The present study was performed to identify PfDXR inhibitors with improved pharmacology/safety. For this purpose, an integrated computational framework, comprising of pharmacophore modeling, virtual screening, molecular docking, molecular dynamics (MD) simulation and MM/PBSA, was used. The binding free energy analysis was performed using a focused library of phytochemicals established from medicinal plants. The study identified four bioactive compounds namely, Myricetin 3-rhamnoside, 7-O-Galloyltricetiflavan, (25S)-5-beta-spirostan-3-beta-ol 3-O-beta-d-glucopyranosyl-(1->2)-beta-d-glucopyranoside, and Oleanolic acid 28-O-beta-d-glucopyranoside as potential inhibitors of PfDXR. The selection of these four compounds was based on pharmacophore mapping, docking score, binding stability, molecular interactions with the residues of PfDXR active site, binding stability and free energy estimation. In conclusion, medicinal plant-based scaffolds were predicted with enhanced efficacy and adequate physiochemical/pharmacokinetic profile that might be helpful in controlling malaria.

Insights into the Binding of Receptor-Binding Domain (RBD) of SARS-CoV-2 Wild Type and B.1.620 Variant with hACE2 Using Molecular Docking and Simulation Approaches.

Recently, a new variant, B.1620, with mutations (S477N-E484K) in the spike protein's receptor-binding domain (RBD) has been reported in Europe. In order to design therapeutic strategies suitable for B.1.620, further studies are required. A detailed investigation of the structural features and variations caused by these substitutions, that is, a molecular level investigation, is essential to uncover the role of these changes. To determine whether and how the binding affinity of ACE2-RBD is affected, we used protein-protein docking and all-atom simulation approaches. Our analysis revealed that B.1.620 binds more strongly than the wild type and alters the hydrogen bonding network. The docking score for the wild type was reported to be -122.6 +/- 0.7 kcal/mol, while for B.1.620, the docking score was -124.9 +/- 3.8 kcal/mol. A comparative binding investigation showed that the wild-type complex has 11 hydrogen bonds and one salt bridge, while the B.1.620 complex has 14 hydrogen bonds and one salt bridge, among which most of the interactions are preserved between the wild type and B.1.620. A dynamic analysis of the two complexes revealed stable dynamics, which corroborated the global stability trend, compactness, and flexibility of the three essential loops, providing a better conformational optimization opportunity and binding. Furthermore, binding free energy revealed that the wild type had a total binding energy of -51.14 kcal/mol, while for B.1.628, the total binding energy was -68.25 kcal/mol. The current findings based on protein complex modeling and bio-simulation methods revealed the atomic features of the B.1.620 variant harboring S477N and E484K mutations in the RBD and the basis for infectivity. In conclusion, the current study presents distinguishing features of B.1.620, which can be used to design structure-based drugs against the B.1.620 variant.