Structure and dynamics of TIP3P, TIP4P, and TIP5P water near smooth and atomistic walls of different hydroaffinity

The entropic origin of the enhancement of liquid diffusion close to a neutral confining surface

It is known that, in the proximity of a neutral wall, liquids experience diffusion enhancement relative to their bulk diffusion, but the origin of this phenomenon is still unknown. We report a molecular dynamics simulation investigating the dynamics of a simple liquid in the proximity to a non-interacting smooth confining wall, which exhibits a strong diffusion enhancement within the liquid layers adjacent to the wall. We present an analysis of these results, demonstrating that the observed diffusion enhancement can be accounted for, with numerical accuracy, using the universal scaling law that relates the liquid diffusion rate to the excess entropy. These results show that the scaling law, which has so far only been used for the description of the bulk liquid diffusion, can be successfully used to describe the diffusion in liquids under nano-scale confinement.

Identification of Hub of the Hub-Genes From Different Individual Studies for Early Diagnosis, Prognosis, and Therapies of Breast Cancer

Breast cancer (BC) is a complex disease, which causes of high mortality rate in women. Early diagnosis and therapeutic improvements may reduce the mortality rate. There were more than 74 individual studies that have suggested BC-causing hub-genes (HubGs) in the literature. However, we observed that their HubG sets are not so consistent with each other. It may be happened due to the regional and environmental variations with the sample units. Therefore, it was required to explore hub of the HubG (hHubG) sets that might be more representative for early diagnosis and therapies of BC in different country regions and their environments. In this study, we selected top-ranked 10 HubGs (CCNB1, CDK1, TOP2A, CCNA2, ESR1, EGFR, JUN, ACTB, TP53, and CCND1) as the hHubG set by the protein-protein interaction network analysis based on all of 74 individual HubG sets. The hHubG set enrichment analysis detected some crucial biological processes, molecular functions, and pathways that are significantly associated with BC progressions. The expression analysis of hHubGs by box plots in different stages of BC progression and BC prediction models indicated that the proposed hHubGs can be considered as the early diagnostic and prognostic biomarkers. Finally, we suggested hHubGs-guided top-ranked 10 candidate drug molecules (SORAFENIB, AMG-900, CHEMBL1765740, ENTRECTINIB, MK-6592, YM201636, masitinib, GSK2126458, TG-02, and PAZOPANIB) by molecular docking analysis for the treatment against BC. We investigated the stability of top-ranked 3 drug-target complexes (SORAFENIB vs ESR1, AMG-900 vs TOP2A, and CHEMBL1765740 vs EGFR) by computing their binding free energies based on 100-ns molecular dynamic (MD) simulation based Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) approach and found their stable performance. The literature review also supported our findings much more for BC compared with the results of individual studies. Therefore, the findings of this study may be useful resources for early diagnosis, prognosis, and therapies of BC.

Machine learning, network pharmacology, and molecular dynamics reveal potent cyclopeptide inhibitors against dengue virus proteins

The dengue virus is a major global health hazard responsible for an estimated 390 million diseases yearly. This study focused on identifying cyclopeptide inhibitors for envelope structural proteins E, NS1, NS3, and NS5. Additionally, 5579 cyclopeptides were individually screened against the four target proteins using a machine learning-based quantitative structure-activity relationship model. Subsequently, the best 10 cyclopeptides from each protein were selected for molecular docking with their corresponding proteins. Moreover, the protein-peptide complexes with the highest affinity were subjected to a 100-ns molecular dynamics simulation. The protein-protein complexes exhibited superior structural stability and binding interactions. Based on the results of the MD simulation analyses, which included checking values for Root Mean Square Deviation, Root Mean Square Fluctuation, Principal Component Analysis (PCA), free energy landscapes, and energetic components, it was found that NS5-CP03714 complex is more stable and has stronger binding interactions than NS3-CP02054. PCA and free energy landscape plots have confirmed the higher conformational stability of NS5-CP03714. Analysis of the energetic components revealed that NS5-CP03714 (total binding energy = - 47.19 kcal/mol) exhibits more favorable interaction energies and overall binding energy compared to NS3-CP02054 (total binding energy = - 27.36 kcal/mol), suggesting a stronger and more stable formation of the complex. In addition, the drug-target network of two specific peptides (CP02950 and CP05582) and their associated target proteins were analyzed. This analysis revealed valuable information about their ability to target several proteins and their potential for broad-spectrum activity. Additional experimental investigations are necessary to validate these computational results and assess the efficacy of identified peptide inhibitors in biological systems.

Walrycin B, as a novel separase inhibitor, exerts potent anticancer efficacy in a mouse xenograft model

Proper chromosome segregation during cell division relies on the timely dissolution of chromosome cohesion. Separase (EC3.4.22.49), a cysteine protease, plays a critical role in mitosis by cleaving the kleisin subunit of cohesin, thereby presenting a promising target for cancer therapy. However, challenges in isolating active human separase suitable for high-throughput screening have limited the identification of effective inhibitors. Here, we conducted a high-throughput screening of small-molecule inhibitors using the protease domain of Chaetomium thermophilum separase (ctSPD), which not only shares significant sequence similarity with human separase but is also readily available. After conducting a primary screening of a library containing 9,172 compounds and subsequent validation using human separase, we identified walrycin B and its analogs, toxoflavin, 3-methyltoxoflavin, and 3-phenyltoxoflavin, as potent inhibitors of human separase. Subsequent microscale thermophoresis assays and molecular dynamics simulations revealed that walrycin B binds to the active site of separase and competes with substrates for binding. Additionally, cell-based studies showed that walrycin B and its analogs effectively induce cell cycle arrest at the M phase, activate apoptosis, and ultimately lead to cell death in mitosis. Finally, in a mouse xenograft model, walrycin B exhibited significant antitumor efficacy with minimal side effects. Together, these findings highlight the therapeutic potential of walrycin B for cancer treatment and its utility as a chemical tool in future studies involving separase.

Chemical analogue based drug design for cancer treatment targeting PI3K: integrating machine learning and molecular modeling

Cancer is a generic term for a group of disorders defined by uncontrolled cell growth and the potential to invade or spread to other parts of the body. Gene and epigenetic alterations disrupt normal cellular control, leading to abnormal cell proliferation, resistance to cell death, blood vessel development, and metastasis (spread to other organs). One of the several routes that play an important role in the development and progression of cancer is the phosphoinositide 3-kinase (PI3K) signaling pathway. Moreover, the gene PIK3CG encodes the catalytic subunit gamma (p110γ) of phosphoinositide 3-kinase (PI3Kγ), a member of the PI3K family. Therefore, in this study, PIK3CG was targeted to inhibit cancer by identifying a novel inhibitor through computational methods. The study screened 1015 chemical fragments against PIK3CG using machine learning-based binding estimation and docking to select the potential compounds. Later, the analogues were generated from the selected hits, and 414 analogues were selected, which were further screened, and as most potential candidates, three compounds were obtained: (a) 84,332, 190,213, and 885,387. The protein-ligand complex's stability and flexibility were then investigated by dynamic modeling. The 100 ns simulation revealed that 885,387 exhibited the steadiest deviation and constant creation of hydrogen bonds. Compared to the other compounds, 885,387 demonstrated a superior binding free energy (ΔG = -18.80 kcal/mol) with the protein when the MM/GBSA technique was used. The study determined that 885,387 showed significant therapeutic potential and justifies further experimental investigation as a possible inhibitor of the PIK3CG target implicated in cancer.

Integrated Gene Expression Data-Driven Identification of Molecular Signatures, Prognostic Biomarkers, and Drug Targets for Glioblastoma

Glioblastoma (GBM) is a highly prevalent and deadly brain tumor with high mortality rates, especially among adults. Despite extensive research, the underlying mechanisms driving its progression remain poorly understood. Computational analysis offers a powerful approach to explore potential prognostic biomarkers, drug targets, and therapeutic agents for GBM. In this study, we utilized three gene expression datasets from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) associated with GBM progression. Our goal was to uncover key molecular players implicated in GBM pathogenesis and potential avenues for targeted therapy. Analysis of the gene expression datasets revealed a total of 78 common DEGs that are potentially involved in GBM progression. Through further investigation, we identified nine hub DEGs that are highly interconnected in protein-protein interaction (PPI) networks, indicating their central role in GBM biology. Gene Ontology (GO) and pathway enrichment analyses provided insights into the biological processes and immunological pathways influenced by these DEGs. Among the nine identified DEGs, survival analysis demonstrated that increased expression of GMFG correlated with decreased patient survival rates in GBM, suggesting its potential as a prognostic biomarker and preventive target for GBM. Furthermore, molecular docking and ADMET analysis identified two compounds from the NIH clinical collection that showed promising interactions with the GMFG protein. Besides, a 100 nanosecond molecular dynamics (MD) simulation evaluated the conformational changes and the binding strength. Our study highlights the potential of GMFG as both a prognostic biomarker and a therapeutic target for GBM. The identification of GMFG and its associated pathways provides valuable insights into the molecular mechanisms driving GBM progression. Moreover, the identification of candidate compounds with potential interactions with GMFG offers exciting possibilities for targeted therapy development. However, further laboratory experiments are required to validate the role of GMFG in GBM pathogenesis and to assess the efficacy of potential therapeutic agents targeting this molecule.

Employing Machine Learning-Based QSAR for Targeting Zika Virus NS3 Protease: Molecular Insights and Inhibitor Discovery

Zika virus infection is a mosquito-borne viral disease that has become a global health concern recently. Zika virus belongs to the Flavivirus genus and is primarily transmitted by Aedes mosquitoes. Prevention of Zika virus infection involves avoiding mosquito bites by using repellent, wearing protective clothing, and staying in screened areas, especially for pregnant women. Treatment focuses on managing symptoms with rest, fluids, and acetaminophen, with close monitoring for pregnant women. Currently, there is no specific antiviral treatment or vaccine for the Zika virus, highlighting the importance of prevention strategies to control its spread. Therefore, in this study, the Zika virus non-structural protein NS3 was targeted to inhibit Zika infection by identifying the novel inhibitor through an in silico approach. Here, 2864 natural compounds were screened using a machine learning-based QSAR model, and later docking was performed to select the potential target. Subsequently, Tanimoto similarity and clustering were performed to obtain the potential target. The three most potential compounds were obtained: (a) 5297, (b) 432449, and (c) 85137543. The protein-ligand complex's stability and flexibility were then investigated by dynamic modelling. The 300 ns simulation showed that 5297 exhibited the steadiest deviation and constant creation of hydrogen bonds. Compared to the other compounds, 5297 demonstrated a superior binding free energy (ΔG = -20.81 kcal/mol) with the protein when the MM/GBSA technique was used. The study determined that 5297 showed significant therapeutic potential and justifies further experimental investigation as a possible inhibitor of the NS2B-NS3 protease target implicated in Zika virus infection.

Enhancing Immune Responses against SARS-CoV-2 Variants in Aged Mice with INDUK: A Chimeric DNA Vaccine Encoding the Spike S1-TM Subunits

Currently available vaccines against COVID-19 showed high efficacy against the original strain of SARS-CoV-2 but progressively lower efficacy against new variants. In response to emerging SARS-CoV-2 strains, we propose chimeric DNA vaccines encoding the spike antigen, including a combination of selected key mutations from different variants of concern. We developed two DNA vaccines, pVAX-S1-TM-D614G and pVAX-S1-TM-INDUK (INDUK), encoding the SARS-CoV-2 S1 spike subunit in fusion with the transmembrane region that allows protein trimerization as predicted by in silico analysis. pVAX-S1-TM-D614G included the dominant D614G substitution, while the chimeric vaccine INDUK contained additional selected mutations from the Delta (E484Q and L452R) and Alpha (N501Y and A570D) variants. Considering that aging is a risk factor for severe disease and that suboptimal vaccine responses were observed in older individuals, the immunogenicity of pVAX-S1-TM-D614G and INDUK was tested in both young and aged C57BL/6 mice. Two vaccine doses were able to trigger significant anti-SARS-CoV-2 antibody production, showing neutralizing activity. ELISA tests confirmed that antibodies induced by pVAX-S1-TM-D614G and INDUK were able to recognize both Wuhan Spike and Delta variant Spike as trimers, while neutralizing antibodies were detected by an ACE2:SARS-CoV-2 Spike S1 inhibitor screening assay, designed to assess the capacity of antibodies to block the interaction between the viral spike S1 protein and the ACE2 receptor. Although antibody titer declined within six months, a third booster dose significantly increased the magnitude of humoral response, even in aged individuals, suggesting that immune recall can improve antibody response durability. The analysis of cellular responses demonstrated that vaccination with INDUK elicited an increase in the percentage of SARS-CoV-2-specific IFN-γ producing T lymphocytes in immunized young mice and TNF-α-producing T lymphocytes in both young and aged mice. These findings not only hold immediate promise for addressing evolving challenges in SARS-CoV-2 vaccination but also open avenues to refine strategies and elevate the effectiveness of next-generation vaccines.

Drug repurposing of pyrazolotriazine derivatives as potential anti-SARS-CoV-2 agents: in vitro and in silico studies

The search for new molecules targeting SARS-CoV-2 has been a priority since 2020. The continuous evolution of new mutants increases the need for more research in the area. One way to find new leads is to repurpose existing drugs and molecules against the required target. Here, we present the in vitro and in silico screening of ten previously synthesized and reported compounds as anti-COVID 19 agents. The compounds were screened in vitro against VERO-E6 cells to find their Cytotoxic Concentration (CC50) and their Inhibitory Concentration (IC50). Compounds 1, 2, and 5 revealed a promising anti-SARS-CoV-2 of (IC50 = 2.4, 11.2 and 2.8 µM), respectively while compounds 3 and 7 showed moderate activity of (IC50 = 17.8 and 26.1 µM) compared to Chloroquine which showed an IC50 of 24.9 µM. Among tested compounds, 1 showed the highest selectivity (CC50/IC50) of 192.8. Docking, molecular dynamics and ADME studies were done to investigate potential interactions between compounds and SARS-CoV-2 targets as well as to study the possibility of using them as lead compounds.

Evaluating the Physicochemical Properties-Activity Relationship and Discovering New 1,2-Dihydropyridine Derivatives as Promising Inhibitors for PIM1-Kinase: Evidence from Principal Component Analysis, Molecular Docking, and Molecular Dynamics Studies

In this study, we evaluated the physicochemical properties related to the previously reported anticancer activity of a dataset comprising thirty 1,2-dihydropyridine derivatives. We utilized Principal Component Analysis (PCA) to identify the most significant influencing factors. The PCA analysis showed that the first two principal components accounted for 59.91% of the total variance, indicating a strong correlation between the molecules and specific descriptors. Among the 239 descriptors analyzed, 18 were positively correlated with anticancer activity, clustering with the 12 most active compounds based on their IC50 values. Six of these variables-LogP, Csp3, b_1rotN, LogS, TPSA, and lip_don-are related to drug-likeness potential. Thus, we then ranked the 12 compounds according to these six variables and excluded those violating the drug-likeness criteria, resulting in a shortlist of nine compounds. Next, we investigated the binding affinity of these nine shortlisted compounds with the use of molecular docking towards the PIM-1 Kinase enzyme (PDB: 2OBJ), which is overexpressed in various cancer cells. Compound 6 exhibited the best docking score among the docked compounds, with a docking score of -11.77 kcal/mol, compared to -12.08 kcal/mol for the reference PIM-1 kinase inhibitor, 6-(5-bromo-2-hydroxyphenyl)-2-oxo-4-phenyl-1,2-dihydropyridine-3-carbonitrile. To discover new PIM-1 kinase inhibitors, we designed nine novel compounds featuring hybrid structures of compound 6 and the reference inhibitor. Among these, compound 31 displayed the best binding affinity, with a docking score of -13.11 kcal/mol. Additionally, we performed PubChem database mining using the structure of compound 6 and the similarity search tool, identifying 16 structurally related compounds with various reported biological properties. Among these, compound 52 exhibited the best binding affinity, with a docking score of -13.03 kcal/mol. Finally, molecular dynamics (MD) studies were conducted to confirm the stability of the protein-ligand complexes obtained from docking the studied compounds to PIM-1 kinase, validating the potential of these compounds as PIM-1 kinase inhibitors.

Further Polycyclic Quinones of Micromonospora sp

The crude acetone extract of a marine Micromonospora sp. strain associated with Eudistoma vannnamei was fractioned with hexane and ethyl acetate. The crude extract and both soluble fractions were assayed against several bacteria strains. The new polycyclic quinones 12-hydroxy-9-propyltetracene-6,1-dione (1), 5,12-dihydroxy-4-methoxy-9-propyltetracene-5,12-dione (2), and 4,6-dihydroxy-3-methoxycarbonyl- methyl-6a-(oxobutyl)-5,12-anthraquinone (3), along with the known 4,6-dihydroxy-3-methoxycarbonyl-methyl-6a-(oxo-3-methyl-butyl)-5,12-anthraquinone (4) and 4,6-dihydroxy-3-methoxycarbonyl-methyl-6a-(oxopentyl)-5,12-anthraquinone (5) were isolated from the hexane-soluble fraction, while from the active ethyl acetate fraction were isolated the known 4,6,11-trihydroxy-9-propyltetracene-5,12-dione (6), 4-methoxy-9-propyltetracene-6,11-dione (7), 7,8,9,10-tetrahydro-9-hydroxy-4-methoxy-9-propyltetracene-6,11-dione (8), and 10β-carbomethoxy-7,8,9,10-tetrahydro-4,6,7α,9α,11-pentahydroxy-9-propyltetracene-5,12-dione (9). The structures of the new compounds were established by interpretation of HRMS and NMR techniques. A study of molecular docking was performed with the compounds from the active ethyl acetate fraction to correlate tentatively with the antimicrobial activity. Molecular docking, RMSD, RMSF, and MM-GBSA evaluations were performed to investigate the inhibitory activity of 6-8 against the protein PDB-codex 1MWT, being considered a promising target for studying drug development responsible for inhibiting replication of Staphylococcus aureus. Penicillin G was used as the standard inhibitory. Anthracyclinones 6-8 were the best hydrolase inhibitor with affinity energy -8.1 to -7.9 kcal/mol compared to penicillin G, which presented -6.9 kcal/mol. Both 8 and 7 present potent inhibitory effects against hydrolase through molecular dynamics simulation and exhibit favorable drug-like properties, promising new hydrolase blockers to fight bacterial infections from Staphylococcus aureus.

A Machine Learning Approach to Identify Key Residues Involved in Protein-Protein Interactions Exemplified with SARS-CoV-2 Variants

Human infection with the coronavirus disease 2019 (COVID-19) is mediated by the binding of the spike protein of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to the human angiotensin-converting enzyme 2 (ACE2). The frequent mutations in the receptor-binding domain (RBD) of the spike protein induced the emergence of variants with increased contagion and can hinder vaccine efficiency. Hence, it is crucial to better understand the binding mechanisms of variant RBDs to human ACE2 and develop efficient methods to characterize this interaction. In this work, we present an approach that uses machine learning to analyze the molecular dynamics simulations of RBD variant trajectories bound to ACE2. Along with the binding free energy calculation, this method was used to characterize the major differences in ACE2-binding capacity of three SARS-CoV-2 RBD variants-namely the original Wuhan strain, Omicron BA.1, and the more recent Omicron BA.5 sublineages. Our analyses assessed the differences in binding free energy and shed light on how it affects the infectious rates of different variants. Furthermore, this approach successfully characterized key binding interactions and could be deployed as an efficient tool to predict different binding inhibitors to pave the way for new preventive and therapeutic strategies.

Multi-targeted therapeutic potential of stigmasterol from the Euphorbia ammak plant in treating lung and breast cancer

Cancer is the most prevalent disease globally, which presents a significant challenge to the healthcare industry, with breast and lung cancer being predominant malignancies. This study used RNA-seq data from the TCGA database to identify potential biomarkers for lung and breast cancer. Tumor Necrosis Factor (TNFAIP8) and Sulfite Oxidase (SUOX) showed significant expression variation and were selected for further study using structure-based drug discovery (SBDD). Compounds derived from the Euphorbia ammak plant were selected for in-silico study with both TNFAIP8 and SUOX. Stigmasterol had the greatest binding scores (normalized scores of -8.53 kcal/mol and -9.69 kcal/mol) with both proteins, indicating strong stability in their binding pockets throughout the molecular dynamics' simulation. Although Stigmasterol first changed its initial conformation (RMSD = 0.5 nm with the starting conformation) in SUOX, it eventually reached a stable conformation (RMSD of 1.5 nm). The compound on TNFAIP8 showed a persistent shape (RMSD of 0.35 nm), indicating strong protein stability. The binding free energy of the complex was calculated using the MM/GBSA technique; TNFAIP8 had a ΔGTOTAL of -24.98 kcal/mol, with TYR160 being the most significant residue, contributing -2.52 kcal/mol. On the other hand, the SUOX complex had a binding free energy of -16.87 kcal/mol, with LEU151 being the primary contributor (-1.17 kcal/mol). Analysis of the complexes' free energy landscape unveiled several states with minimum free energy, indicating robust interactions between the protein and ligand. In its conclusion, this work emphasises the favourable ability of Stigmasterol to bind with prospective targets for lung and breast cancer, indicating the need for more experimental study.

Computational Exploration of Naturally Occurring Flavonoids as TGF-β Inhibitors in Breast Cancer: Insights from Docking and Molecular Dynamics Simulations and In-vitro Cytotoxicity Study

Breast cancer is a global health concern, demanding innovative treatments. Targeting the Transforming Growth Factor-beta (TGF-β) signaling pathway, pivotal in breast cancer, is a promising approach. TGF-β inhibits proliferation via G1 phase cell cycle arrest, acting as a suppressor initially, but in later stages, it promotes progression by enhancing motility, invasiveness, and metastasis formation. This study explores naturally occurring flavonoids' interactions with TGF-β. Using molecular docking against the protein's crystal structure (PDB Id: 1PY5), Gossypin showed the highest docking score and underwent molecular dynamics simulation, revealing complex flexibility and explaining how flavonoids impede TGF-β signaling in breast cancer. ADMET predictions adhered to Lipinski's rule of Five. Insights into flavonoid-TGF-β binding offer a novel angle for breast cancer treatment. Flavonoids having a good docking score like gossypin, morin, luteolin and taxifolin shown potent cytotoxic effect on breast cancer cell line, MCF-7. Understanding these interactions could inspire flavonoid-based therapies targeting TGF-β to halt breast cancer growth. These findings pave the way for personalized, targeted breast cancer therapies, offering hope against this formidable disease.

Investigating the effects of Laggera pterodonta on H3N2-Induced inflammatory and immune responses through network pharmacology, molecular docking, and experimental validation in a mice model

For centuries, Laggera pterodonta (LP), a Chinese herbal medicine, has been widely employed for treating respiratory infectious diseases; however, the mechanism underlying LP's effectiveness against the influenza A/Aichi/2/1968 virus (H3N2) remains elusive. This study aims to shed light on the mechanism by which LP combats influenza in H3N2-infected mice. First, we conducted quasi-targeted metabolomics analysis using liquid chromatography-mass spectrometry to identify LP components. Subsequently, network pharmacology, molecular docking, and simulation were conducted to screen candidate targets associated with AKT and NF-κB. In addition, we conducted a series of experiments including qPCR, hematoxylin-eosin staining, flow cytometry, immunohistochemistry, and enzyme-linked immunosorbent assay to provide evidence that LP treatment in H3N2-infected mice can reduce pro-inflammatory cytokine levels (TNF-α, IL-6, IL-1β, and MCP-1) while increasing T cells (CD3+, CD4+, and CD8+) and syndecan-1 and secretory IgA expression. This, in turn, aids in the prevention of excessive inflammation and the fortification of immunity, both of which are compromised by H3N2. Finally, we utilized a Western blot assay to confirm that LP indeed inhibits the AKT/NF-κB signaling cascade. Thus, the efficacy of LP serves as a cornerstone in establishing a theoretical foundation for influenza treatment.

Structural dynamics of Na+ and Ca2+ interactions with full-size mammalian NCX

Cytosolic Ca2+ and Na+ allosterically regulate Na+/Ca2+ exchanger (NCX) proteins to vary the NCX-mediated Ca2+ entry/exit rates in diverse cell types. To resolve the structure-based dynamic mechanisms underlying the ion-dependent allosteric regulation in mammalian NCXs, we analyze the apo, Ca2+, and Na+-bound species of the brain NCX1.4 variant using hydrogen-deuterium exchange mass spectrometry (HDX-MS) and molecular dynamics (MD) simulations. Ca2+ binding to the cytosolic regulatory domains (CBD1 and CBD2) rigidifies the intracellular regulatory loop (5L6) and promotes its interaction with the membrane domains. Either Na+ or Ca2+ stabilizes the intracellular portions of transmembrane helices TM3, TM4, TM9, TM10, and their connecting loops (3L4 and 9L10), thereby exposing previously unappreciated regulatory sites. Ca2+ or Na+ also rigidifies the palmitoylation domain (TMH2), and neighboring TM1/TM6 bundle, thereby uncovering a structural entity for modulating the ion transport rates. The present analysis provides new structure-dynamic clues underlying the regulatory diversity among tissue-specific NCX variants.

Suramin inhibits phenotypic transformation of vascular smooth muscle cells and neointima hyperplasia by suppressing transforming growth factor beta receptor 1 /Smad2/3 pathway activation

Vascular smooth muscle cells (VSMCs) contribute to neointimal hyperplasia (NIH) after vascular injury, a common feature of vascular remodelling disorders. Suramin is known to exert antitumour effects by inhibiting the proliferation of various tumour cells; however, its effects and mechanism on VSMCs remain unclear. This study investigated the effects of suramin on human aortic smooth muscle cells (HASMCs), rat aortic smooth muscle cells (RASMCs) and NIH to examine its suitability for the prevention of vascular remodelling disorders. In vitro, suramin administration reduced platelet-derived growth factor type BB (PDGF-BB)-stimulated proliferation, migration, and dedifferentiation of VSMCs through a transforming growth factor beta receptor 1 (TGFBR1)/Smad2/3-dependent pathway. Suramin dramatically inhibited NIH ligation in the left common carotid artery (LCCA) vivo. Therefore, our results indicate that suramin protects against the development of pathological vascular remodelling by attenuating VSMCs proliferation, migration, and phenotypic transformation and may be used as a potential medicine for the treatment of NIH.

Exploring therapeutic potential of Rutin by investigating its cyclin-dependent kinase 6 inhibitory activity and binding affinity

Cyclin-dependent kinase 6 (CDK6) participates in numerous signalling pathways and regulates various physiological processes. Due to its unique structural features and promising therapeutic potential, CDK6 has emerged as a drug target for designing and developing small-molecule inhibitors for anti-cancer therapeutics and other CDK6-associated diseases. The current study evaluates binding affinity and the inhibitory potential of rutin for CDK6 to develop a proof of concept for rutin as a potent CDK6 inhibitor. Molecular docking and 200 ns all-atom simulations reveal that rutin binds to the active site pocket of CDK6, forming interactions with key residues of the binding pocket. In addition, the CDK6-rutin complex remains stable throughout the simulation trajectory. A high binding constant (Ka = 7.6 × 105M-1) indicates that rutin has a strong affinity for CDK6. Isothermal titration calorimetry has further validated a strong binding of rutin with CDK6 and its spontaneous nature. The kinase activity of CDK6 is significantly inhibited by rutin with an IC50 value of 3.10 μM. Our findings highlight the significant role of rutin in developing potential therapeutic molecules to manage cancer and CDK6-associated diseases via therapeutic targeting of CDK6.

In vitro and in vivo evaluation of the antimicrobial, antioxidant, cytotoxic, hemolytic activities and in silico POM/DFT/DNA-binding and pharmacokinetic analyses of new sulfonamide bearing thiazolidin-4-ones

In this work, Schiff bases and Thiazolidin-4-ones, were synthesized using Sonication and Microwave techniques, respectively. The Schiff base derivatives (3a-b) were synthesized via the reaction of Sulfathiazole (1) with benzaldehyde derivatives (2a-b), followed by the synthesis of 4-thiazoledinone (4a-b) derivatives by cyclizing the synthesized Schiff bases through thioglycholic acid. All the synthesized compounds were characterized by spectroscopic techniques such as FT IR, NMR and HRMS. The synthesized compounds were tested for their in vitro antimicrobial and antioxidant and in vivo cytotoxicity and hemolysis ability. The synthesized compounds displayed better antimicrobial and antioxidant activity and low toxicity in comparison to reference drugs and negative controls, respectively. The hemolysis test revealed the compounds exhibit lower hemolytic effects and hemolytic values are comparatively low and the safety of compounds is in comparison with standard drugs. Theoretical calculations were carried out by using the molecular operating environment (MOE) and Gaussian computing software and observations were in good agreement with the in vitro and in vivo biological activities. Petra/Osiris/Molinspiration (POM) results indicate the presence of three combined antibacterial, antiviral and antitumor pharmacophore sites. The molecular docking revealed the significant binding affinities and non-bonding interactions between the compounds and Erwinia Chrysanthemi (PDB ID: 1SHK). The molecular dynamics simulation under in silico physiological conditions revealed a stable conformation and binding pattern in a stimulating environment. HighlightsNew series of Thaiazolidin-4-one derivatives have been synthesized.Sonication and microwave techniques are used.Antimicrobial, Antioxidant, cytotoxicity, and hemolysis activities were observed for all synthesized compounds.Molecular Docking and DFT/POM analyses have been predicted.Communicated by Ramaswamy H. Sarma.

Modulating the antibacterial effect of the existing antibiotics along with repurposing drug metformin

Owing to the extensive prevalence of resistant bacteria to numerous antibiotic classes, antimicrobial resistance (AMR) poses a well-known hazard to world health. As an alternate approach in the field of antimicrobial drug discovery, repurposing the available medications which are also called antibiotic resistance breakers has been pursued for the treatment of infections with antimicrobial resistance pathogens. In this study, we used Haloperidol, Metformin and Hydroxychloroquine as repurposing drugs in in vitro (Antibacterial Antibiotic Sensitivity Test and Minimum Inhibitory Concentration-MIC) and in vivo (Shigellosis in Swiss albino mice) tests in combination with traditional antibiotics (Oxytetracycline, Erythromycin, Doxycycline, Gentamicin, Ampicillin, Chloramphenicol, and Penicillin) against a group of AMR resistance bacteria (Bacillus cereus, Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, and Shigella boydii). After observing the results of the conducted in vitro experiments we studied the effects of the above non antibiotic drugs in combination with the said antibiotics. As an repurposing adjuvant antibiotic drug, Metformin exhibited noteworthy activity in almost all in vitro, in vivo and in silico tests (Zone of inhibition for 30 to 43 mm for E.coli in combination with Doxycycline; MIC value decreased 50 µM to 0.781 µM with Doxycycline on S. boydii).In rodents Doxycycline and Metformin showed prominent against Shigellosis in White blood cell count (6.47 ± 0.152 thousand/mm3) and Erythrocyte sedimentation rate (10.5 ± 1.73 mm/hr). Our findings indicated that Metformin and Doxycycline combination has a crucial impact on Shigellosis. The molecular docking study was performed targeting the Acriflavine resistance protein B (AcrB) (PDB ID: 4CDI) and MexA protein (PDB ID: 6IOK) protein with Metformin (met8) drug which showed the highest binding energy with - 6.4 kcal/mol and - 5.5 kcal/mol respectively. Further, molecular dynamics simulation revealed that the docked complexes were relatively stable during the 100 ns simulation period. This study suggest Metformin and other experimented drugs can be used as adjuvants boost up antibiosis but further study is needed to find out the safety and efficacy of this non-antibiotic drug as potent antibiotic adjuvant.

D-Glucosamine is a Potential Urease Inhibitor from Middle Eastern Medicinal Plants for Combatting Helicobacter Pylori Infections; a Molecular Docking and Simulation Approach

Helicobacter pylori stands as a significant risk factor for both peptic and stomach ulcers. Their resistance to the highly acidic host environment primarily stems from their capability to produce urease, an enzyme that rapidly converts urea into NH3 and CO2. These byproducts are crucial for the bacterium's survival under such harsh conditions. Given the pivotal role of medicinal plants in treating various ailments with minimal side effects, there is an urgent need for a natural drug that can effectively eliminate H. pylori by inhibiting urease. Hence, the current study aims to identify the most potent urease inhibitor among the natural compounds found in Middle Eastern medicinal plants, taking into consideration factors such as optimal affinity, drug-like properties, pharmacokinetic characteristics, and thermodynamic attributes. In total, 5599 ligand conformers from 151 medicinal plants were subjected to docking against the urease's active site. The top-ranking natural compounds, as determined by their high docking scores, were selected for further analysis. Among these compounds, D-glucosamine (PubChem code 439,213) exhibited the most interactions with the crucial amino acid residues in the urease's active site. Furthermore, D-glucosamine demonstrated superior absorption, distribution, metabolism, excretion, and toxicity properties compared to other top-ranked candidates. Molecular dynamics simulations conducted over 100 nanoseconds revealed stable root mean square deviations and fluctuations of the protein upon complexation with D-glucosamine. Additionally, the radius of gyration and solvent-accessible surface area values for the D-glucosamine-urease complex were notably lower than those observed in other typical urease-inhibitor complexes. In conclusion, this study provides valuable insights into the potential development of D-glucosamine as a novel urease inhibitor. This promising compound holds the potential to serve as an effective drug for combating H. pylori infections in the near future.

Prediction of the binding location between the nuclear inhibitor of DNA binding and differentiation 2 (ID2) and HSPA5

Glucose-regulated protein 78 (GRP78), also termed HSPA5, was widely studied in cancer. It was recently approved that GRP78 has nuclear localization potential that sheds light on its role in cancer development. The inhibitor of DNA binding and differentiation 2 (ID2) is the nuclear component that associates with GRP78. The interaction between these two proteins is not understood clearly. In the current study, the binding pattern of GRP78/ID2 is predicted using computational methods. Protein-protein docking is used along with molecular dynamics simulation. The substrate binding domain β of GRP78 can stably interact with the loop region (C42-S60) of ID2 as predicted in this study. This paves the way for a possible destabilizer for this association and cancer eradication.

In silico analysis of alpha-synuclein protein variants and posttranslational modifications related to Parkinson's disease

Parkinson's disease (PD) is among the most prevalent neurodegenerative disorders, affecting over 10 million people worldwide. The protein encoded by the SNCA gene, alpha-synuclein (ASYN), is the major component of Lewy body (LB) aggregates, a histopathological hallmark of PD. Mutations and posttranslational modifications (PTMs) in ASYN are known to influence protein aggregation and LB formation, possibly playing a crucial role in PD pathogenesis. In this work, we applied computational methods to characterize the effects of missense mutations and PTMs on the structure and function of ASYN. Missense mutations in ASYN were compiled from the literature/databases and underwent a comprehensive predictive analysis. Phosphorylation and SUMOylation sites of ASYN were retrieved from databases and predicted by algorithms. ConSurf was used to estimate the evolutionary conservation of ASYN amino acids. Molecular dynamics (MD) simulations of ASYN wild-type and variants A30G, A30P, A53T, and G51D were performed using the GROMACS package. Seventy-seven missense mutations in ASYN were compiled. Although most mutations were not predicted to affect ASYN stability, aggregation propensity, amyloid formation, and chaperone binding, the analyzed mutations received relatively high rates of deleterious predictions and predominantly occurred at evolutionarily conserved sites within the protein. Moreover, our predictive analyses suggested that the following mutations may be possibly harmful to ASYN and, consequently, potential targets for future investigation: K6N, T22I, K34E, G36R, G36S, V37F, L38P, G41D, and K102E. The MD analyses pointed to remarkable flexibility and essential dynamics alterations at nearly all domains of the studied variants, which could lead to impaired contact between NAC and the C-terminal domain triggering protein aggregation. These alterations may have functional implications for ASYN and provide important insight into the molecular mechanism of PD, supporting the design of future biomedical research and improvements in existing therapies for the disease.

An in silico approach to develop potential therapies against Middle East Respiratory Syndrome Coronavirus (MERS-CoV)

A deadly respiratory disease Middle East Respiratory Syndrome (MERS) is caused by a perilous virus known as MERS-CoV, which has a severe impact on human health. Currently, there is no approved vaccine, prophylaxis, or antiviral therapeutics for preventing MERS-CoV infection. Due to its inexorable and integral role in the maturation and replication of the MERS-CoV virus, the 3C-like protease is unavoidly a viable therapeutic target. In this study, 2369 phytoconstituents were enlisted from Japanese medicinal plants, and these compounds were screened against 3C-like protease to identify feasible inhibitors. The best three compounds were identified as Kihadanin B, Robustaflavone, and 3-beta-O- (trans-p-Coumaroyl) maslinic acid, with binding energies of -9.8, -9.4, and -9.2 kcal/mol, respectively. The top three potential candidates interacted with several active site residues in the targeted protein, including Cys145, Met168, Glu169, Ala171, and Gln192. The best three compounds were assessed by in silico technique to determine their drug-likeness properties, and they exhibited the least harmful features and the greatest drug-like qualities. Various descriptors, such as solvent-accessible surface area, root-mean-square fluctuation, root-mean-square deviation, hydrogen bond, and radius of gyration, validated the stability and firmness of the protein-ligand complexes throughout the 100ns molecular dynamics simulation. Moreover, the top three compounds exhibited better binding energy along with better stability and firmness than the inhibitor (Nafamostat), which was further confirmed by the binding free energy calculation. Therefore, this computational investigation could aid in the development of efficient therapeutics for life-threatening MERS-CoV infections.

Computer-Aided Rational Design Strategy to Improve the Thermal Stability of Alginate Lyase AlyMc

Alginate lyase degrades alginate by the β-elimination mechanism to produce unsaturated alginate oligosaccharides (UAOS), which have better bioactivities than saturated AOS. Enhancing the thermal stability of alginate lyases is crucial for their industrial applications. In this study, a feasible and efficient rational design strategy was proposed by combining the computer-aided ΔΔG value calculation with the B-factor analysis. Two thermal stability-enhanced mutants, Q246V and K249V, were obtained by site-directed mutagenesis. Particularly, the t1/2, 50 °C for mutants Q246V and K249V was increased from 2.36 to 3.85 and 3.65 h, respectively. Remarkably, the specific activities of Q246V and K249V were enhanced to 2.41- and 2.96-fold that of alginate lyase AlyMc, respectively. Structural analysis and molecular dynamics simulations suggested that mutations enhanced the hydrogen bond networks and the overall rigidity of the molecular structure. Notably, mutant Q246V exhibited excellent thermal stability among the PL-7 alginate lyase family, especially considering the heightened enzymatic activity. Moreover, the rational design strategy used in this study can effectively improve the thermal stability of enzymes and has important significance in advancing applications of alginate lyase.

A Molecular Generative Model of COVID-19 Main Protease Inhibitors Using Long Short-Term Memory-Based Recurrent Neural Network

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a serious threat to public health and prompted researchers to find anti-coronavirus 2019 (COVID-19) compounds. In this study, the long short-term memory-based recurrent neural network was used to generate new inhibitors for the coronavirus. First, the model was trained to generate drug compounds in the form of valid simplified molecular-input line-entry system strings. Then, the structures of COVID-19 main protease inhibitors were applied to fine-tune the model. After fine-tuning, the network could generate new molecular structures as novel SARS-CoV-2 main protease inhibitors. Molecular docking exhibited that some generated compounds have the proper affinity to the active site of the protease. Molecular Dynamics simulations explored binding free energies of the compounds over simulation trajectories. In addition, in silico absorption, distribution, metabolism, and excretion studies showed that some novel compounds could be formulated as orally active agents. Based on molecular docking and molecular dynamics simulation studies, compound AADH possessed significant binding affinity and presumably inhibition against the SARS-CoV-2 main protease enzyme. Therefore, the proposed deep learning-based model was capable of generating promising anti-COVID-19 drugs.

Unveiling Therapeutic Avenues for Crohn's Disease Management: Exploring Inhibitors for Adherent-Invasive Escherichia coli Propanediol Dehydratase

INTRODUCTION

Inflammatory Bowel Disease (IBD) encompasses a group of chronic disorders distinguished by inflammation of the gastrointestinal tract. Among these, Crohn's Disease (CD) stands out as a complex and impactful condition due to challenges for both diagnosis and management, making it a cynosure of research.

METHODS

In CD, there is the predominance of proinflammatory bacteria, including the Adherentinvasive Escherichia coli (AIEC) with virulence-associated metabolic enzyme Propanediol Dehydratase (pduC), which has been identified as a therapeutic target for the management of CD. Herein, molecular modeling techniques, including molecular docking, Molecular Mechanics with Generalized Born and Surface Area (MMGBSA), drug-likeness, and pharmacokinetics profiling, were utilized to probe the potentials of eighty antibacterial compounds to serve as inhibitors of pduC.

RESULTS

The results of this study led to the identification of five compounds with promising potentials; the results of the molecular docking simulation revealed the compounds as possessing better binding affinities for the target compared to the standard drug (sulfasalazine), while Lipinski's rule of five-based assessment of their drug-likeness properties revealed them as potential oral drugs. MMGBSA free energy calculation and Molecular Dynamics (MD) simulation of the complexes formed a sequel to molecular docking, revealing the compounds as stable binders in the active site of the protein.

CONCLUSION

Ultimately, the results of this study have revealed five compounds to possess the potential to serve as inhibitors of pduC of AIEC. However, experimental studies are still needed to validate the findings of this study.

Structural Insights of PD-1/PD-L1 Axis: An In silico Approach

BACKGROUND

Interaction of PD-1 protein (present on immune T-cell) with its ligand PD-L1 (over-expressed on cancerous cell) makes the cancerous cell survive and thrive. The association of PD-1/PD-L1 represents a classical protein-protein interaction (PPI), where receptor and ligand binding through a large flat surface. Blocking the PD-1/PDL-1 complex formation can restore the normal immune mechanism, thereby destroying cancerous cells. However, the PD-1/PDL1 interactions are only partially characterized.

OBJECTIVE

We aim to comprehend the time-dependent behavior of PD-1 upon its binding with PD-L1.

METHODS

The current work focuses on a molecular dynamics simulation (MDs) simulation study of apo and ligand bound PD-1.

RESULTS

Our simulation reveals the flexible nature of the PD-1, both in apo and bound form. Moreover, the current study also differentiates the type of strong and weak interactions which could be targeted to overcome the complex formation.

CONCLUSION

The current article could provide a valuable structural insight about the target protein (PD-1) and its ligand (PD-L1) which could open new opportunities in developing small molecule inhibitors (SMIs) targeting either PD-1 or PD-L1.

In silico investigation of Komaroviquinone as a potential inhibitor of SARS-CoV-2 main protease (Mpro): Molecular docking, molecular dynamics, and QM/MM approaches

COVID-19 has highlighted the urgent need for new therapeutic agents to combat the spread of the virus. The main protease of SARS-CoV-2 (Mpro) has emerged as a promising target. In this study, we conducted an in silico investigation to explore the potential of Komaroviquinone, an icetexane diterpene, as a therapeutic agent against COVID-19. We employed molecular docking, molecular dynamics, and QM/MM methodologies to compare the binding affinity, molecular interactions, and stability of Komaroviquinone and the FDA-approved antiviral drug Nirmatrelvir with the SARS-CoV-2 Mpro protein. The study demonstrated that Komaroviquinone exhibits strong interaction with Mpro, with a binding energy comparable to Nirmatrelvir. The ADMET analysis revealed that Barbatusol, Brussonol, and Komaroviquinone possess superior solubility, permeability, and intestinal absorption compared to Nirmatrelvir, as well as more favorable distribution properties and lower toxicity profiles. Notably, Nirmatrelvir displayed toxicity and hepatotoxicity, which were not present in the natural compounds. Thus, it is suggested that Komaroviquinone may be a promising candidate for the development of effective and safer therapeutic agents against COVID-19. Experimental validation is necessary to confirm its potential as a treatment for the disease.

De Novo Potent Peptide Nucleic Acid Antisense Oligomer Inhibitors Targeting SARS-CoV-2 RNA-Dependent RNA Polymerase via Structure-Guided Drug Design

Global reports of novel SARS-CoV-2 variants and recurrence cases continue despite substantial vaccination campaigns, raising severe concerns about COVID-19. While repurposed drugs offer some treatment options for COVID-19, notably, nucleoside inhibitors like Remdesivir stand out as curative therapies for COVID-19 that are approved by the US Food and Drug Administration (FDA). The emergence of highly contagious SARS-CoV-2 variants underscores the imperative for antiviral drugs adaptable to evolving viral mutations. RNA-dependent RNA polymerase (RdRp) plays a key role in viral genome replication. Currently, inhibiting viral RdRp function remains a pivotal strategy to tackle the notorious virus. Peptide nucleic acid (PNA) therapy shows promise by effectively targeting specific genome regions, reducing viral replication, and inhibiting infection. In our study, we designed PNA antisense oligomers conjugated with cell-penetrating peptides (CPP) aiming to evaluate their antiviral effects against RdRp target using structure-guided drug design, which involves molecular docking simulations, drug likeliness and pharmacokinetic evaluations, molecular dynamics simulations, and computing binding free energy. The in silico analysis predicts that chemically modified PNAs might act as antisense molecules in order to disrupt ribosome assembly at RdRp's translation start site, and their chemically stable and neutral backbone might enhance sequence-specific RNA binding interaction. Notably, our findings demonstrate that PNA-peptide conjugates might be the most promising inhibitors of SARS-CoV-2 RdRp, with superior binding free energy compared to Remdesivir in the current COVID-19 medication. Specifically, PNA-CPP-1 could bind simultaneously to the active site residues of RdRp protein and sequence-specific RdRp-RNA target in order to control viral replication.

Unveiling the anticancer mechanism of 1,2,3-triazole-incorporated thiazole-pyrimidine-isoxazoles: insights from docking and molecular dynamics simulations

Cancer is a major global health concern, and the constant search for novel, selective anticancer compounds with low toxicity is never ending. Nitrogen heterocyclic compounds such as pyrimidine and triazole have been identified as potential candidates for cancer treatment. A novel series of 1,2,3-triazole incorporated thiazole-pyrimidine-isoxazole derivatives 10 (a-j) were designed, synthesized and evaluated for antitumorigenic activities against human breast cancer (MCF-7), human lung cancer (A549) and human prostate (PC3 & DU-145) various cell-lines by employing MTT assay using etoposide as the positive control. The synthesized hybrids yielded decent efficacy, which was further compared with the standard drug. Among all the molecules, 10h revealed the more potent anticancerous activities, having IC50 values ranging from 0.011 ± 0.0017 µM; 0.063 ± 0.0012 µM; 0.017 ± 0.0094 µM and 0.66 ± 0.072 µM with DU145, PC3, A549, and MCF7 cell-lines, respectively. Tubulin, being a major protein involved with diverse biological actions, also serves, as a crucial target for several clinically practiced anticancer drugs, was utilized for docking analyses to evaluate the binding affinity of ligands. Docking results demonstrates that the selected hybrids 10 (g-j) exhibited good binding affinities with protein. Subsequently, drug likeness studies were carried out on the synthesized compounds to evaluate and analyze their drug like properties such as absorption, distribution, metabolism, excretion, and toxicity (ADMET) for toxicity prediction. Based on these analyses, the selected complexes were further employed for molecular dynamic simulations to analyze stability via an exhaustive cumulative 200 nanoseconds simulation. These results suggest that the selected compounds are stable and might serve as potential inhibitors to tubulin complex. In conclusion, we propose these synthesized compounds 10 (g-j) might provide new insights into cancer treatment and have potential for future development.Communicated by Ramaswamy H. Sarma.

Dynamics of water-mediated interaction effects on the stability and transmission of Omicron

SARS-Cov-2 Omicron variant and its highly transmissible sublineages amidst news of emerging hybrid variants strengthen the evidence of its ability to rapidly spread and evolve giving rise to unprecedented future waves. Owing to the presence of isolated RBD, monomeric and trimeric Cryo-EM structures of spike protein in complex with ACE2 receptor, comparative analysis of Alpha, Beta, Gamma, Delta, and Omicron assist in a rational assessment of their probability to evolve as new or hybrid variants in future. This study proposes the role of hydration forces in mediating Omicron function and dynamics based on a stronger interplay between protein and solvent with each Covid wave. Mutations of multiple hydrophobic residues into hydrophilic residues underwent concerted interactions with water leading to variations in charge distribution in Delta and Omicron during molecular dynamics simulations. Moreover, comparative analysis of interacting moieties characterized a large number of mutations lying at RBD into constrained, homologous and low-affinity groups referred to as mutational drivers inferring that the probability of future mutations relies on their function. Furthermore, the computational findings reveal a significant difference in angular distances among variants of concern due 3 amino acid insertion (EPE) in Omicron variant that not only facilitates tight domain organization but also seems requisite for characterization of mutational processes. The outcome of this work signifies the possible relation between hydration forces, their impact on conformation and binding affinities, and viral fitness that will significantly aid in understanding dynamics of drug targets for Covid-19 countermeasures. The emerging scenario is that hydration forces and hydrophobic interactions are crucial variables to probe in mutational analysis to explore conformational landscape of macromolecules and reveal the molecular origins of protein behaviors.

Effects of gamma-radiation on microbial, nutritional, and functional properties of Katimon mango peels: A combined biochemical and in silico studies

Gamma radiation has notable impacts on the flesh of mangoes. In this research, Katimon mangoes were subjected to different levels of irradiation (0.5, 1.0, 1.5, and 2.0 kGy) using a60Co irradiator. The results showed that irradiation significantly reduced the microbial population in the mango peels, with the 1.5 kGy dose showing the most significant reduction. Irradiation also delayed ripening and extended the shelf life of the mango peels. The total fat, protein, ash, moisture, and sugar content of the mango peels were all affected by irradiation. The total protein content, ash content and moisture content increased after irradiation, while the fat content remained relatively unchanged. The sugar content increased in all samples after storage, but the non-irradiated samples had higher sugar levels than the irradiated ones. The dietary fiber content of the mango peels was not significantly affected by irradiation. The vitamin C content decreased in all samples after storage. The titratable acidity and total soluble solids content of the mango peels increased after storage, but there were no significant differences between the irradiated and non-irradiated samples. Antioxidant activity and cytotoxicity assessment highlighted the antioxidant potential and reduced toxicity of irradiated samples. Additionally, the antimicrobial effectiveness of irradiated mango peels was evaluated. The most substantial inhibitory zones (measuring 16.90 ± 0.35) against Pseudomonas sp. were observed at a radiation dose of 1.5 kGy with 150 μg/disc. To identify potential antimicrobial agents, the volatile components of mangoes irradiated with 1.5 kGy were analyzed through GC-MS. Subsequently, these compounds were subjected to in silico studies against a viable protein, TgpA, of Pseudomonas sp. (PDB ID: 6G49). Based on molecular dynamic simulations and ADMET properties, (-)-Carvone (-6.2), p-Cymene (-6.1), and Acetic acid phenylmethyl ester (-6.1) were identified as promising compounds for controlling Pseudomonas sp.

Identification of new potent agonists for toll-like receptor 8 by virtual screening methods, molecular dynamics simulation, and MM-GBSA

Toll-like receptor 8 (TLR8), as an endosomal transmembrane receptor, plays a crucial role in the innate immune response to neoplasia and viruses. Previous studies have shown that TLR8 agonists e.g. Motolimod can be used to treat patients with last-stage cancer. In this study, in order to find new suitable ligands for TLR8, 16 PBD codes related to TLR8 complexes were collected to design the pharmacophore models using the Pharmit server. Then the PubChem, and ZINC databases were screened by them. Subsequently, the ADME-Tox features of the compounds were detected using FAF-Drugs4 and the selected compounds were docked to TLR8 (PDB: 3w3j). Molecular dynamics simulation was used to compare compounds with the best docking scores, with Motolimod in complex with TLR8. Finally, two compounds were identified, PubChem: 124126919 (A) and PubChem: 18559540 (B), each with advantages over Motolimod. As the RMSD results showed that compound A has very good flexibility, in terms of energy calculated using the MM-GBSA method, complex B and TLR8 showed the lowest energy level compared to the rest of the complexes. These observations suggest that these two compounds could be used as TLR8 agonists with the desired pharmacological features in future experimental studies.Communicated by Ramaswamy H. Sarma.

Structure-based design of new N-benzyl-piperidine derivatives as multitarget-directed AChE/BuChE inhibitors for Alzheimer's disease

The pathogenic complexity of Alzheimer's disease (AD) demands the development of multitarget-directed agents aiming at improving actual pharmacotherapy. Based on the cholinergic hypothesis and considering the well-established role of butyrylcholinesterase (BuChE) in advanced stages of AD, the chemical structure of the acetylcholinesterase (AChE) inhibitor drug donepezil (1) was rationally modified for the design of new N-benzyl-piperidine derivatives (4a-d) as potential multitarget-direct AChE and BuChE inhibitors. The designed analogues were further studied through the integration of in silico and in vitro methods. ADMET predictions showed that 4a-d are anticipated to be orally bioavailable, able to cross the blood-brain barrier and be retained in the brain, and to have low toxicity. Computational docking and molecular dynamics indicated the formation of favorable complexes between 4a-d and both cholinesterases. Derivative 4a presented the lowest binding free energy estimation due to interaction with key residues from both target enzymes (-36.69 ± 4.47 and -32.23 ± 3.99 kcal/mol with AChE and BuChE, respectively). The in vitro enzymatic assay demonstrated that 4a was the most potent inhibitor of AChE (IC50 2.08 ± 0.16 µM) and BuChE (IC50 7.41 ± 0.44 µM), corroborating the in silico results and highlighting 4a as a novel multitarget-directed AChE/BuChE inhibitor.

Molecular-scale insights into confined clindamycin in nanoscale pores of mesoporous silica

Clindamycin is an antibiotic used to treat a variety of bacterial infections. The sustained release of clindamycin from the drug carrier is an important strategy to prolong the effective antibacterial duration. In this work, the microstructure and dynamics of clindamycin confined into the nanopores of mesopore silica with different pore sizes were studied using molecular dynamics simulation. It is found that there is a layering behavior for clindamycin distribution as a function of distance from the pore surface to the pore center with preferred location near the surface of the nanopore. The radial distribution function between carbonyl oxygen and the silanol groups shows the highest intensity of the first peak with the preferred orientation of carbonyl oxygen pointing toward the pore surface, which suggests the strong interaction between the carbonyl oxygen and the silanol groups on the pore surface. The higher local diffusion coefficients for the clindamycin molecules near the pore surface can be found. In addition, the presence of water can lead to the shift of clindamycin distribution away from the surface and promote the local diffusion of clindamycin near the pore surface. The information in this work will provide the microscopic understanding for the design of the drug carriers for the controlled release of clindamycin.

Targeting of HPV E6 at the binding sites to the host-cell E6AP, p53, and the endoplasmic reticulum-resident chaperone, GRP78

Background: Human papillomavirus (HPV) represents an etiological factor for many cancer types, especially cervical cancer. Its oncoprotein E6 sheds drug designers who aim to stop its cellular protein associations, such as p53 and E6AP. Recently, it was discovered that the host-cell chaperone glucose-regulated protein 78 (GRP78) plays a crucial function in HPV infectivity by association with the viral E6 and E7 proteins. Therefore, we aimed to test small molecules inhibitor that could contradict the association between E6 and cellular factors E6AP, GRP78, and p53. Methods: In this study, molecular docking protocol was elaborated to test 115 small molecule compounds against the three binding sites of HPV E6 to the host-cell proteins; E6AP, p53, and GRP78. After that, molecular dynamics simulation and free energy calculations were performed on the best three complexes. Results: The results reveal the potency of 18 compounds against the HPV E6 at different binding sites, which give lower free energies than paclitaxel (positive control). The best two compounds, hypericin, and anabsinthin, could bind effectively and stably during the 100 ns MD simulation period to HPV E6. The calculated average free energies for hypericin and anabsinthin are -18.76 and -14.40 kcal/mol, respectively. They formed stable complexes with the three binding sites by forming hydrophobic contacts. The key residues that stabilize the two ligands in HPV E6 binding sites are V31, Y32, V62, and Y70 (E6AP), P13, C16, T22, I23 and A46 (p53), and M1, V31, L50, L67, and Q107 (GRP78). Conclusions: The best two compounds, hypericin, and anabsinthin, are potential candidates against HPV E6 at the host-cell factors binding sites, hence could block the oncoprotein activity of E6 in infected cells. Further experimental validation is yet to be performed and suggested as future work.Communicated by Ramaswamy H. Sarma.

Antimalarial drug discovery against malaria parasites through haplopine modification: An advanced computational approach

The widespread emergence of antimalarial drug resistance has created a major threat to public health. Malaria is a life-threatening infectious disease caused by Plasmodium spp., which includes Apicoplast DNA polymerase and Plasmodium falciparum cysteine protease falcipain-2. These components play a critical role in their life cycle and metabolic pathway, and are involved in the breakdown of erythrocyte hemoglobin in the host, making them promising targets for anti-malarial drug design. Our current study has been designed to explore the potential inhibitors from haplopine derivatives against these two targets using an in silico approach. A total of nine haplopine derivatives were used to perform molecular docking, and the results revealed that Ligands 03 and 05 showed strong binding affinity compared to the control compound atovaquone. Furthermore, these ligand-protein complexes underwent molecular dynamics simulations, and the results demonstrated that the complexes maintained strong stability in terms of RMSD (root mean square deviation), RMSF (root mean square fluctuation), and Rg (radius of gyration) over a 100 ns simulation period. Additionally, PCA (principal component analysis) analysis and the dynamic cross-correlation matrix showed positive outcomes for the protein-ligand complexes. Moreover, the compounds exhibited no violations of the Lipinski rule, and ADMET (absorption, distribution, metabolism, excretion, and toxicity) predictions yielded positive results without indicating any toxicity. Finally, density functional theory (DFT) and molecular electrostatic potential calculations were conducted, revealing that the mentioned derivatives exhibited better stability and outstanding performance. Overall, this computational approach suggests that these haplopine derivatives could serve as a potential source for developing new, effective antimalarial drugs to combat malaria. However, further in vitro or in vivo studies might be conducted to determine their actual effectiveness.

Integrated gene expression profiling and functional enrichment analyses to discover biomarkers and pathways associated with Guillain-Barré syndrome and autism spectrum disorder to identify new therapeutic targets

Guillain-Barré syndrome (GBS) is one of the most prominent and acute immune-mediated peripheral neuropathy, while autism spectrum disorders (ASD) are a group of heterogeneous neurodevelopmental disorders. The complete mechanism regarding the neuropathophysiology of these disorders is still ambiguous. Even after recent breakthroughs in molecular biology, the link between GBS and ASD remains a mystery. Therefore, we have implemented well-established bioinformatic techniques to identify potential biomarkers and drug candidates for GBS and ASD. 17 common differentially expressed genes (DEGs) were identified for these two disorders, which later guided the rest of the research. Common genes identified the protein-protein interaction (PPI) network and pathways associated with both disorders. Based on the PPI network, the constructed hub gene and module analysis network determined two common DEGs, namely CXCL9 and CXCL10, which are vital in predicting the top drug candidates. Furthermore, coregulatory networks of TF-gene and TF-miRNA were built to detect the regulatory biomolecules. Among drug candidates, imatinib had the highest docking and MM-GBSA score with the well-known chemokine receptor CXCR3 and remained stable during the 100 ns molecular dynamics simulation validated by the principal component analysis and the dynamic cross-correlation map. This study predicted the gene-based disease network for GBS and ASD and suggested prospective drug candidates. However, more in-depth research is required for clinical validation.Communicated by Ramaswamy H. Sarma.

Exploring the Interaction of New Pyridoquinazoline Derivatives with G-Quadruplex in the c-MYC Promoter Region

Novel amino-substituted pyridoquinazolinone derivatives have been designed and synthesized as potential c-MYC G-quadruplex (G4) ligands, employing an efficient methodology. All the new compounds exhibited moderate to good antiproliferative activity against the human osteosarcoma U2OS cell line. NMR and docking experiments revealed that the recently synthesized compounds interact with the Pu22 G-quadruplex in the c-MYC promoter region, establishing a 2:1 complex, with each molecule positioned over the tetrads at the 3'- and 5'-ends.

Isatin-pyrimidine hybrid derivatives as enoyl acyl carrier protein reductase (InhA) inhibitors against Mycobacterium tuberculosis

Tuberculosis is a worldwide problem that impose a burden on the economy due to continuous development of resistant strains. The development of new antitubercular drugs is a need and can be achieved through inhibition of druggable targets. Mycobacterium tuberculosis enoyl acyl carrier protein (ACP) reductase (InhA) is an important enzyme for Mycobacterium tuberculosis survival. In this study, we report the synthesis of isatin derivatives that could treat TB through inhibition of this enzyme. Compound 4l showed IC50 value (0.6 ± 0.94 µM) similar to isoniazid but is also effective against MDR and XDR Mycobacterium tuberculosis strains (MIC of 0.48 and 3.9 µg/mL, respectively). Molecular docking studies suggest that this compound binds through the use of relatively unexplored hydrophobic pocket in the active site. Molecular dynamics was used to investigate and support the stability of 4l complex with the target enzyme. This study paves the way for the design and synthesis of novel antitubercular drugs.

Anti-parasitic drug discovery against Babesia microti by natural compounds: an extensive computational drug design approach

Tick-borne Babesiosis is a parasitic infection caused by Babesia microti that can infect both animals and humans and may spread by tick, blood transfusions, and organ transplantation. The current therapeutic options for B. microti are limited, and drug resistance is a concern. This study proposes using computational drug design approaches to find and design an effective drug against B. microti. The study investigated the potentiality of nine natural compounds against the pathogenic human B. microti parasite and identified Vasicinone and Evodiamine as the most promising drugs. The ligand structures were optimized using density functional theory, molecular docking, molecular dynamics simulations, quantum mechanics such as HOMO-LUMO, drug-likeness and theoretical absorption, distribution, metabolism, excretion, and toxicity (ADMET), and pharmacokinetics characteristics performed. The results showed that Vasicinone (-8.6 kcal/mol and -7.8 kcal/mol) and Evodiamine (-8.7 kcal/mol and -8.5 kcal/mol) had the highest binding energy and anti-parasitic activity against B. microti lactate dehydrogenase and B. microti lactate dehydrogenase apo form. The strongest binding energy was reported by Vasicinone and Evodiamine; the compounds were evaluated through molecular dynamics simulation at 100 ns, and their stability when they form complexes with the targeted receptors was determined. Finally, the pkCSM web server is employed to predict the ADMET qualities of specific molecules, which can help prevent negative effects that arise from taking the treatment. The SwissADME web server is used to assess the Lipinski rule of five and drug-likeness properties including topological polar surface area and bioavailability. The Lipinski rule is used to estimate significant drug-likeness. The theoretical pharmacokinetics analysis and drug-likeness of the selected compounds are confirmed to be accepted by the Lipinski rule and have better ADMET features. Thus, to confirm their experimental value, these mentioned molecules should be suggested to carry out in wet lab, pre-clinical, and clinical levels.

mPGES-1 Inhibitor Discovery Based on Computer-Aided Screening: Pharmacophore Models, Molecular Docking, ADMET, and MD Simulations

mPGES-1 is an enzyme, which, when activated by inflammatory factors, can cause prostaglandin E synthesis. Traditional non-steroidal anti-inflammatory drugs are capable of inhibiting prostaglandin production, yet they can also cause gastrointestinal reactions and coagulation disorders. mPGES-1, the enzyme at the conclusion of prostaglandin production, does not cause any adverse reactions when inhibited. Numerous studies have demonstrated that mPGES-1 is more abundant in cancerous cells than in healthy cells, indicating that decreasing the expression of mPGES-1 could be a potential therapeutic strategy for cancer. Consequently, the invention of mPGES-1 inhibitors presents a fresh avenue for the treatment of inflammation and cancer. Incorporating a database of TCM compounds, we collected a batch of compounds that had an inhibitory effect on mPGES-1 and possessed IC50 value. Firstly, a pharmacophore model was constructed, and the TCM database was screened, and the compounds with score cut-off values of more than 1 were retained. Then, the compounds retained after being screened via the pharmacodynamic model were screened for docking at the mPGES-1 binding site, followed by high-throughput virtual screening [HTVS] and standard precision [SP] and super-precision [XP] docking, and the compounds in the top 20% of the XP docking score were selected to calculate the total free binding energy of MM-GBSA. The best ten compounds were chosen by comparing their score against the reference ligand 4U9 and the MM-GBSA_dG_Bind score. ADMET analysis resulted in the selection of ten compounds, three of which had desirable medicinal properties. Finally, the binding energy of the target protein mPGES-1 and the candidate ligand compound was analyzed using a 100 ns molecular dynamics simulation of the reference ligand 4U9 and three selected compounds. After a gradual screening study and analysis, we identified a structure that is superior to the reference ligand 4U9 in all aspects, namely compound 15643. Taken together, the results of this study reveal a structure that can be used to inhibit mPGES-1 compound 15643, thereby providing a new option for anti-inflammatory and anti-tumor drugs.

Insights into Omicron's Low Fusogenicity through In Silico Molecular Studies on Spike-Furin Interactions

The Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant and its subvariants have a unique set of mutations. Two of those mutations (N679 K and P681 H) reside close to the S1 /S2 furin cleavage site (FCS; 685-686). When these mutations reside together, they exert less-efficient membrane fusion than wild type and most other variants of concern such as the Delta variant. Here, we in silico targeted these mutations to find out which of the amino acids and interactions change plays the key role in fusion. To comprehend the epistatic effect of N679 K and P681 H mutations on the spike protein, we in silico constructed three types of spike protein sequences by changing the respective amino acids on 679 and 681 positions (P681 H, N679 K, K679 N-H681 P variants). We then analyzed the binding affinity of furin and spike (Furin-Wild, Furin-Omicron, Furin-P681 H, Furin-N679 K, and Furin-K679 N/H681 P) complexes. Omicron and P681 H variants showed a similar higher binding energy trend compared to the wild type and N679 K. The variation in hydrogen, hydrophobic, and salt bridge bonds between spike protein and furin provided an explanation for the observed low fusogenicity of Omicron. The fate of the epistasis in furin binding and possible cleavage depends on the efficient interaction between FCS in spike and furin catalytic triad, and in addition, the loss of the hydrogen bond between Arg 681 (spike) and Asn 295 (furin) along with inhibitor-like ineffective higher affinity plays an important role in the enzymatic activity.

Molecular insights of anti-diabetic compounds and its hyaluronic acid conjugates against aldose reductase enzyme through molecular modeling and simulations study-a novel treatment option for inflammatory diabetes

CONTEXT

Chronic inflammation is a risk factor for diabetes, but it can also be a complication of diabetes, leading to severe diabetes and causing many other clinical manifestations. Inflammation is a major emerging complication in both type I and type II diabetes, which causes increasing interest in targeting inflammation to improve and control diabetes. Diabetes with insulin resistance and impaired glucose utilization in humans and their underlying mechanism is not fully understood. But a growing understanding of the intricacy of the insulin signaling cascade in diabetic inflammatory cells reveals potential target genes and their proteins responsible for severe insulin resistance. With this baseline concept, the current project explores the binding affinities of the hyaluronic acid anti-diabetic compounds conjugates to such target proteins in diabetic inflammatory cells and their molecular geometries. A range of 48 anti-diabetic compounds was screened against aldose reductase binding pocket 3 protein target through in silico molecular docking, and results revealed that three compounds viz, metformin (CID:4091), phenformin (CID:8249), sitagliptin (CID:4,369,359), possess significant binding affinity out of 48 chosen drugs. Further, these three anti-diabetic compounds were conjugated with hyaluronic acid (HA), and their binding affinity and their molecular geometrics towards aldose reductase enzyme were screened compared with the free form of the drug. The molecular geometries of three shortlisted drugs (metformin, phenformin, sitagliptin) and their HA conjugates were also explored through density functional theory studies, and it proves their good molecular geometry towards pocket 3 of aldose reductase target. Further, MD simulation trajectories affirm that HA conjugates possess good binding affinity and simulation trajectories with protein target aldose reductase than a free form of the drug. Our current study unravels the new mechanism of drug targeting for diabetes through HA conjugation for inflammatory diabetes. HA conjugates act as novel drug candidates for treating inflammatory diabetes; however, it needs further human clinical trials.

METHODS

For ligand structure, PubChem, ACD chem sketch, and online structure file generator platform are utilized for ligand preparation. Target protein aldose reductase obtained from protein database (PDB). For molecular docking analysis, AutoDock Vina (Version 4) was utilized. pKCSM online server used to predict ADMET properties of the above three shortlisted drugs from the docking study. Using mol-inspiration software (version 2011.06), three shortlisted compounds' bioactivity scores were predicted. DFT analysis for three shortlisted anti-diabetic drugs and their hyaluronic acid conjugates were calculated using a functional B3LYP set of Gaussian 09 software. Molecular dynamics simulation calculations for six chosen protein-ligand complexes were done through YASARA dynamics software and AMBER14 force field.

Discrete Dynamics of Warhead Modulation on Covalent Inhibition of Oxyr: A QM/MM Study

The bacterial transcriptional factor OxyR, a peroxide sensor conserved in bacterial virulence pathways, has the capability to exhibit exceptional reactivity toward hydrogen peroxide (H₂O₂). H₂O₂ is essential for oxidizing cysteine thiolates to maintain cellular redox homeostasis and is dispensable for bacterial growth that can potentially mitigate drug resistance, thus underlining OxyR as a valuable target. We employ quantum mechanics/molecular mechanics (QM/MM) umbrella sampling (US) simulations at the DFTB3/MM level of theory and propose a reaction mechanism with four potential covalent inhibitors. The potential of mean force reveals the direct role of intrinsic reactivity of inhibitors, for instance, benzothiophenes and modified experimental inhibitors with methyl oxo-enoate warhead-activated carbonyl samples in the first step of reaction, which shed light on the significance of proton transfer indispensable for full inhibition, whereas the nitrile inhibitor undergoes a stepwise mechanism with a small proton-transfer energy barrier and lower imaginary frequencies that materialize instantly after nucleophilic attack. To unveil the molecular determinants of respective binding affinities, transition states along the reaction path are optimized and characterized with B3LYP 6-31+G(d,p). Furthermore, the post-simulation analysis indicates the catalytic triad (His130/Cys199/Thr129), thermodynamically favored for inhibition, which restricts water molecules from acting as the potential source of protonation/deprotonation. This study thus serves as a preamble to add variation in the proposed structures and unveils the impact of functional groups lying in warheads that modulate the kinetics of proton transfer, which will certainly aid to design more selective and efficient irreversible inhibitors of OxyR.

Design, synthesis and anti-Tb evaluation of chalcone derivatives as novel inhibitors of InhA

A series of halogenated chalcone derivatives were designed and developed for anti-tubercular activity. Novel molecules were designed and in-silico screening were performed using admetSAR, SwissADME, and Osiris Property Explorer. From the initial filter the top 10 compounds were docked using the Autodock tool 1.5.6. and the binding energies of the docked compounds were higher than the standard drugs Isoniazid.and Ethionamide. Based on the in-silico and docking results, the top halogenated chalcones were synthesized and characterized using FT-IR, mass spectrometry, 1H, and 13C NMR spectroscopy. The chalcones were further evaluated for anti-tubercular activity using MABA against the H37Rv strain. Among the series of compounds, DK12 and DK14 showed potent in-vitro activity, with MICs of 0.8 µg/ml, in comparison with 1.6 µg/ml of the first-line drug Isoniazid. Further molecular dynamics simulations studies for 100 ns revealed that the key interaction with TYR 158 were observed in both DK12 and DK14 in the InhA active site. The compound DK12 further showed significant interactions with PHE 149 and ARG 153 residues and is a hit molecule among the series. Further DK12 and DK14 does not show any significance toxicity. The compounds DK12 needs to be optimized and further investigation to be carried out against InhA.Communicated by Ramaswamy H. Sarma.

Effect of Cas9 Protein on the Seed-Target Base Pair of the sgRNA/DNA Hybrid Duplex

CRISPR (clustered regularly interspaced short palindromic repeats)/CRISPR-associated protein (Cas9) has been widely used for gene editing. Not all guide RNAs can cleave the DNA efficiently remains a major challenge to CRISPR/Cas9-mediated genome engineering. Therefore, understanding how the Cas9 complex successfully and efficiently identifies specific functional targets through base-pairing has great implications for such applications. The 10-nt seed sequence at the 3' end of the guide RNA is critical to target recognition and cleavage. Here, through stretching molecular dynamics simulation, we studied the thermodynamics and kinetics of the binding-dissociation process of the seed base and the target DNA base with the Cas9 protein. The results showed that in the presence of Cas9 protein, the enthalpy change and entropy change in binding-dissociation of the seed base with the target are smaller than those without the Cas9 protein. The reduction of entropy penalty upon association with the protein resulted from the pre-organization of the seed base in an A-form helix, and the reduction of enthalpy change was due to the electrostatic attraction of the positively charged channel with the negative target DNA. The binding barrier coming from the entropy loss and the dissociation barrier resulting from the destruction of the base pair in the presence of Cas9 protein were lower than those without protein, which indicates that the seed region is crucial for efficiently searching the correct target by accelerating the binding rate and dissociating fast from the wrong target.

Advances in Computational and Bioinformatics Tools and Databases for Designing and Developing a Multi-Epitope-Based Peptide Vaccine

A vaccine is defined as a biologic preparation that trains the immune system, boosts immunity, and protects against a deadly microbial infection. They have been used for centuries to combat a variety of contagious illnesses by means of subsiding the disease burden as well as eradicating the disease. Since infectious disease pandemics are a recurring global threat, vaccination has emerged as one of the most promising tools to save millions of lives and reduce infection rates. The World Health Organization reports that immunization protects three million individuals annually. Currently, multi-epitope-based peptide vaccines are a unique concept in vaccine formulation. Epitope-based peptide vaccines utilize small fragments of proteins or peptides (parts of the pathogen), called epitopes, that trigger an adequate immune response against a particular pathogen. However, conventional vaccine designing and development techniques are too cumbersome, expensive, and time-consuming. With the recent advancement in bioinformatics, immunoinformatics, and vaccinomics discipline, vaccine science has entered a new era accompanying a modern, impressive, and more realistic paradigm in designing and developing next-generation strong immunogens. In silico designing and developing a safe and novel vaccine construct involves knowledge of reverse vaccinology, various vaccine databases, and high throughput techniques. The computational tools and techniques directly associated with vaccine research are extremely effective, economical, precise, robust, and safe for human use. Many vaccine candidates have entered clinical trials instantly and are available prior to schedule. In light of this, the present article provides researchers with up-to-date information on various approaches, protocols, and databases regarding the computational designing and development of potent multi-epitope-based peptide vaccines that can assist researchers in tailoring vaccines more rapidly and cost-effectively.

Amentoflavone derivatives significantly act towards the main protease (3CLPRO/MPRO) of SARS-CoV-2: in silico admet profiling, molecular docking, molecular dynamics simulation, network pharmacology

SARS-CoV-2 is the foremost culprit of the novel coronavirus disease 2019 (nCoV-19 and/or simply COVID-19) and poses a threat to the continued life of humans on the planet and create pandemic issue globally. The 3-chymotrypsin-like protease (MPRO or 3CLPRO) is the crucial protease enzyme of SARS-CoV-2, which directly involves the processing and release of translated non-structural proteins (nsps), and therefore involves the development of virus pathogenesis along with outbreak the forecasting of COVID-19 symptoms. Moreover, SARS-CoV-2 infections can be inhibited by plant-derived chemicals like amentoflavone derivatives, which could be used to develop an anti-COVID-19 drug. Our research study is designed to conduct an in silico analysis on derivatives of amentoflavone (isoginkgetin, putraflavone, 4''''''-methylamentoflavone, bilobetin, ginkgetin, sotetsuflavone, sequoiaflavone, heveaflavone, kayaflavone, and sciadopitysin) for targeting the non-structural protein of SARS-CoV-2, and subsequently further validate to confirm their antiviral ability. To conduct all the in silico experiments with the derivatives of amentoflavone against the MPRO protein, both computerized tools and online servers were applied; notably the software used is UCSF Chimera (version 1.14), PyRx, PyMoL, BIOVIA Discovery Studio tool (version 4.5), YASARA (dynamics simulator), and Cytoscape. Besides, as part of the online tools, the SwissDME and pKCSM were employed. The research study was proposed to implement molecular docking investigations utilizing compounds that were found to be effective against the viral primary protease (MPRO). MPRO protein interacted strongly with 10 amentoflavone derivatives. Every time, amentoflavone compounds outperformed the FDA-approved antiviral medicine that is currently underused in COVID-19 in terms of binding affinity (- 8.9, - 9.4, - 9.7, - 9.1, - 9.3, - 9.0, - 9.7, - 9.3, - 8.8, and - 9.0 kcal/mol, respectively). The best-selected derivatives of amentoflavone also possessed potential results in 100 ns molecular dynamic simulation (MDS) validation. It is conceivable that based on our in silico research these selected amentoflavone derivatives more precisely 4''''''-methylamentoflavone, ginkgetin, and sequoiaflavone have potential for serving as promising lead drugs against SARS-CoV-2 infection. In consequence, it is recommended that additional in vitro as well as in vivo research studies have to be conducted to support the conclusions of this current research study.