Comprehensive translational profiling and STE AI uncover rapid control of protein biosynthesis during cell stress.

Translational control is important in all life, but it remains a challenge to accurately quantify. When ribosomes translate messenger (m)RNA into proteins, they attach to the mRNA in series, forming poly(ribo)somes, and can co-localize. Here, we computationally model new types of co-localized ribosomal complexes on mRNA and identify them using enhanced translation complex profile sequencing (eTCP-seq) based on rapid in vivo crosslinking. We detect long disome footprints outside regions of non-random elongation stalls and show these are linked to translation initiation and protein biosynthesis rates. We subject footprints of disomes and other translation complexes to artificial intelligence (AI) analysis and construct a new, accurate and self-normalized measure of translation, termed stochastic translation efficiency (STE). We then apply STE to investigate rapid changes to mRNA translation in yeast undergoing glucose depletion. Importantly, we show that, well beyond tagging elongation stalls, footprints of co-localized ribosomes provide rich insight into translational mechanisms, polysome dynamics and topology. STE AI ranks cellular mRNAs by absolute translation rates under given conditions, can assist in identifying its control elements and will facilitate the development of next-generation synthetic biology designs and mRNA-based therapeutics.

Virtual screening and molecular dynamics simulation study of plant-derived compounds to identify potential inhibitors of main protease from SARS-CoV-2.

The new coronavirus (SARS-CoV-2) halts the world economy and caused unbearable medical emergency due to high transmission rate and also no effective vaccine and drugs has been developed which brought the world pandemic situations. The main protease (Mpro) of SARS-CoV-2 may act as an effective target for drug development due to the conservation level. Herein, we have employed a rigorous literature review pipeline to enlist 3063 compounds from more than 200 plants from the Asian region. Therefore, the virtual screening procedure helps us to shortlist the total compounds into 19 based on their better binding energy. Moreover, the Prime MM-GBSA procedure screened the compound dataset further where curcumin, gartanin and robinetin had a score of (-59.439, -52.421 and - 47.544) kcal/mol, respectively. The top three ligands based on binding energy and MM-GBSA scores have most of the binding in the catalytic groove Cys145, His41, Met165, required for the target protein inhibition. The molecular dynamics simulation study confirms the docked complex rigidity and stability by exploring root mean square deviations, root mean square fluctuations, solvent accessible surface area, radius of gyration and hydrogen bond analysis from simulation trajectories. The post-molecular dynamics analysis also confirms the interactions of the curcumin, gartanin and robinetin in the similar binding pockets. Our computational drug designing approach may contribute to the development of drugs against SARS-CoV-2.

A molecular modelling approach for identifying antiviral selenium-containing heterocyclic compounds that inhibit the main protease of SARS-CoV-2: an in silico investigation.

Coronavirus disease 2019 (COVID-19), an infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been declared a global pandemic by the World Health Organization, and the situation worsens daily, associated with acute increases in case fatality rates. The main protease (Mpro) enzyme produced by SARS-CoV-2 was recently demonstrated to be responsible for not only viral reproduction but also impeding host immune responses. The element selenium (Se) plays a vital role in immune functions, both directly and indirectly. Thus, we hypothesised that Se-containing heterocyclic compounds might curb the activity of SARS-CoV-2 Mpro. We performed a molecular docking analysis and found that several of the selected selenocompounds showed potential binding affinities for SARS-CoV-2 Mpro, especially ethaselen (49), which exhibited a docking score of -6.7 kcal/mol compared with the -6.5 kcal/mol score for GC376 (positive control). Drug-likeness calculations suggested that these compounds are biologically active and possess the characteristics of ideal drug candidates. Based on the binding affinity and drug-likeness results, we selected the 16 most effective selenocompounds as potential anti-COVID-19 drug candidates. We also validated the structural integrity and stability of the drug candidate through molecular dynamics simulation. Using further in vitro and in vivo experiments, we believe that the targeted compound identified in this study (ethaselen) could pave the way for the development of prospective drugs to combat SARS-CoV-2 infections and trigger specific host immune responses.

Impacts of nutritive and bioactive compounds on cancer development and therapy.

For persons who survive with progressive cancer, nutritional therapy and exercise may be significant factors to improve the health condition and life quality of cancer patients. Nutritional therapy and medications are essential to managing progressive cancer. Cancer survivors, as well as cancer patients, are mostly extremely encouraged to search for knowledge about the selection of diet, exercise, and dietary supplements to recover as well as maintain their treatment consequences, living quality, and survival of patients. A healthy diet plays an important role in cancer treatment. Different articles are studied to collect information and knowledge about the use of nutrients in cancer treatment as well as cancer prevention. The report deliberates nutrition and exercise strategies during the range of cancer care, emphasizing significant concerns during treatment of cancer and for patients of advanced cancer, but concentrating mostly on the requirements of the population of persons who are healthy or who have constant disease following their repossession from management. It also deliberates choice nutrition and exercise problems such as dietary supplements, food care, food selections, and weight; problems interrelated to designated cancer sites, and common questions about diet, and cancer survival. Decrease the side effects of medicines both during and after treatment.

Natural flavonoids effectively block the CD81 receptor of hepatocytes and inhibit HCV infection: a computational drug development approach.

Hepatitis C virus (HCV) infection is a major public health concern, and almost two million people are infected per year globally. This is occurred by the diverse spectrum of viral genotypes, which are directly associated with chronic liver disease (fibrosis, and cirrhosis). Indeed, the viral genome encodes three principal proteins as sequentially core, E1, and E2. Both E1 and E2 proteins play a crucial role in the attachment of the host system, but E2 plays a more fundamental role in attachment. The researchers have found the "E2-CD81 complex" at the entry site, and therefore, CD81 is the key receptor for HCV entrance in both humans, and chimpanzees. So, the researchers are trying to block the host CD81 receptor and halt the virus entry within the cellular system via plant-derived compounds. Perhaps that is why the current research protocol is designed to perform an in silico analysis of the flavonoid compounds for targeting the tetraspanin CD81 receptor of hepatocytes. To find out the best flavonoid compounds from our library, web-based tools (Swiss ADME, pKCSM), as well as computerized tools like the PyRx, PyMOL, BIOVIA Discovery Studio Visualizer, Ligplot+ V2.2, and YASARA were employed. For molecular docking studies, the flavonoid compounds docked with the targeted CD81 protein, and herein, the best-outperformed compounds are Taxifolin, Myricetin, Puerarin, Quercetin, and (-)-Epicatechin, and outstanding binding affinities are sequentially - 7.5, - 7.9, - 8.2, - 8.4, and - 8.5 kcal/mol, respectively. These compounds have possessed more interactions with the targeted protein. To validate the post docking data, we analyzed both 100 ns molecular dynamic simulation, and MM-PBSA via the YASARA simulator, and finally finds the more significant outcomes. It is concluded that in the future, these compounds may become one of the most important alternative antiviral agents in the fight against HCV infection. It is suggested that further in vivo, and in vitro research studies should be done to support the conclusions of this in silico research workflow.

Use of Next-Generation Sequencing for Identifying Mitochondrial Disorders.

Mitochondria are major contributors to ATP synthesis, generating more than 90% of the total cellular energy production through oxidative phosphorylation (OXPHOS): metabolite oxidation, such as the ß-oxidation of fatty acids, and the Krebs's cycle. OXPHOS inadequacy due to large genetic lesions in mitochondrial as well as nuclear genes and homo- or heteroplasmic point mutations in mitochondrially encoded genes is a characteristic of heterogeneous, maternally inherited genetic disorders known as mitochondrial disorders that affect multisystemic tissues and organs with high energy requirements, resulting in various signs and symptoms. Several traditional diagnostic approaches, including magnetic resonance imaging of the brain, cardiac testing, biochemical screening, variable heteroplasmy genetic testing, identifying clinical features, and skeletal muscle biopsies, are associated with increased risks, high costs, a high degree of false-positive or false-negative results, or a lack of precision, which limits their diagnostic abilities for mitochondrial disorders. Variable heteroplasmy levels, mtDNA depletion, and the identification of pathogenic variants can be detected through genetic sequencing, including the gold standard Sanger sequencing. However, sequencing can be time consuming, and Sanger sequencing can result in the missed recognition of larger structural variations such as CNVs or copy-number variations. Although each sequencing method has its own limitations, genetic sequencing can be an alternative to traditional diagnostic methods. The ever-growing roster of possible mutations has led to the development of next-generation sequencing (NGS). The enhancement of NGS methods can offer a precise diagnosis of the mitochondrial disorder within a short period at a reasonable expense for both research and clinical applications.

Dominant clade-featured SARS-CoV-2 co-occurring mutations reveal plausible epistasis: An in silico based hypothetical model.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has evolved into eight fundamental clades with four of these clades (G, GH, GR, and GV) globally prevalent in 2020. To explain plausible epistatic effects of the signature co-occurring mutations of these circulating clades on viral replication and transmission fitness, we proposed a hypothetical model using in silico approach. Molecular docking and dynamics analyses showed the higher infectiousness of a spike mutant through more favorable binding of G614 with the elastase-2. RdRp mutation p.P323L significantly increased genome-wide mutations (p < 0.0001), allowing for more flexible RdRp (mutated)-NSP8 interaction that may accelerate replication. Superior RNA stability and structural variation at NSP3:C241T might impact protein, RNA interactions, or both. Another silent 5'-UTR:C241T mutation might affect translational efficiency and viral packaging. These four G-clade-featured co-occurring mutations might increase viral replication. Sentinel GH-clade ORF3a:p.Q57H variants constricted the ion-channel through intertransmembrane-domain interaction of cysteine(C81)-histidine(H57). The GR-clade N:p.RG203-204KR would stabilize RNA interaction by a more flexible and hypo-phosphorylated SR-rich region. GV-clade viruses seemingly gained the evolutionary advantage of the confounding factors; nevertheless, N:p.A220V might modulate RNA binding with no phenotypic effect. Our hypothetical model needs further retrospective and prospective studies to understand detailed molecular events and their relationship to the fitness of SARS-CoV-2.

Methyl ß-D-galactopyranoside esters as potential inhibitors for SARS-CoV-2 protease enzyme: synthesis, antimicrobial, PASS, molecular docking, molecular dynamics simulations and quantum computations.

Carbohydrate esters are significant in medicinal chemistry because of their efficacy for the synthesis of biologically active drugs. In the present study, methyl ß-D-galactopyranoside (MGP) was treated with various acyl halides to produce 6-O-acyl MGP esters by direct acylation method with an excellent yield. To obtain newer products for antimicrobial assessment studies, the 6-O-MGP esters were further modified into 2,3,4-tri-O-acyl MGP esters containing a wide variety of functionalities in a single molecular framework. The chemical structures of the newly synthesized compounds were elucidated by analyzing their physicochemical, elemental, and spectroscopic data. In vitro antimicrobial testing against five bacteria and two fungi and the prediction of activity spectra for substances (PASS) revealed that these MGP estes have promising antifungal functionality compared to their antibacterial activities. The antimicrobial tests demonstrated that the compounds 3 and 10 were the most potent against Bacillus subtilis and Escherichia coli strains, with the minimum inhibitory concentration (MIC) values ranging from 0.352 ± 0.02 to 0.703 ± 0.01 mg/ml and minimum bactericidal concentration (MBC) values ranging from 0.704 ± 0.02 to 1.408 ± 0.04 mg/ml. Density functional theory (DFT) at the B3LYP/3-21G level of theory was employed to enumerate, frontier orbital energy, enthalpy, free energy, electronic energy, MEP, dipole moment which evaluated the effect of certain groups (aliphatic and aromatic) on drug properties. They discovered that all esters were more thermodynamically stable than the parent molecule. Molecular docking is performed using AutoDock Vina to determine the binding affinities and interactions between the MGP esters and the SARS-CoV-2 main protease. The modified esters strongly interact with the prime Cys145, His41, MET165, GLY143, THR26, and ASN142 residues. The MGP esters' shape and ability to form multiple electrostatic and hydrogen bonds with the active site match other minor-groove binders' binding modes. The molecular dynamics simulation validates the molecular docking results. The pharmacokinetic characterization of the optimized inhibitor demonstrates that these MGP esters appear to be safer inhibitors and a combination of in silico ADMET (absorption, distribution, metabolism, excretion, and toxicity) prediction and drug-likeness had promising results due to their improved kinetic properties. Structure activity relationships (SAR) study including in vitro and silico results revealed that the acyl chain, palmitoyl (C16) and 4-chlorobenzoyl (4.ClC6H4CO-) in combination with sugar were found the most potential activates against human and fungal pathogens. After all, our comprehensive computational and statistical analysis shows that these selected MGP esters can be used as potential inhibitors against the SARS-CoV-2.

Synthesis, antimicrobial, molecular docking and molecular dynamics studies of lauroyl thymidine analogs against SARS-CoV-2: POM study and identification of the pharmacophore sites.

Nucleoside precursors and nucleoside analogs occupy an important place in the treatment of viral respiratory pathologies, especially during the current COVID-19 pandemic. From this perspective, the present study has been designed to explore and evaluate the synthesis and spectral characterisation of 5́-O-(lauroyl) thymidine analogs 2-6 with different aliphatic and aromatic groups through comprehensive in vitro antimicrobial screening, cytotoxicity assessment, physicochemical aspects, molecular docking and molecular dynamics analysis, along with pharmacokinetic prediction. A unimolar one-step lauroylation of thymidine under controlled conditions furnished the 5́-O-(lauroyl) thymidine and indicated the selectivity at C-5́ position and the development of thymidine based potential antimicrobial analogs, which were further converted into four newer 3́-O-(acyl)-5́-O-(lauroyl) thymidine analogs in reasonably good yields. The chemical structures of the newly synthesised analogs were ascertained by analysing their physicochemical, elemental, and spectroscopic data. In vitro antimicrobial tests against five bacteria and two fungi, along with the prediction of activity spectra for substances (PASS), indicated promising antibacterial functionality for these thymidine analogs compared to antifungal activity. In support of this observation, molecular docking experiments have been performed against the main protease of SARS-CoV-2, and significant binding affinities and non-bonding interactions were observed against the main protease (6LU7, 6Y84 and 7BQY), considering hydroxychloroquine (HCQ) as standard. Moreover, the 100 ns molecular dynamics simulation process was performed to monitor the behaviour of the complex structure formed by the main protease under in silico physiological conditions to examine its stability over time, and this revealed a stable conformation and binding pattern in a stimulating environment of thymidine analogs. Cytotoxicity determination confirmed that compounds were found less toxic. Pharmacokinetic predictions were investigated to evaluate their absorption, distribution, metabolism and toxic properties, and the combination of pharmacokinetic and drug-likeness predictions has shown promising results in silico. The POM analysis shows the presence of an antiviral (O1δ-, O2δ-) pharmacophore site. Overall, the current study should be of great help in the development of thymidine-based, novel, multiple drug-resistant antimicrobial and COVID-19 drugs.

A conserved subunit vaccine designed against SARS-CoV-2 variants showed evidence in neutralizing the virus.

Novel coronavirus (SARS-CoV-2) leads to coronavirus disease 19 (COVID-19), declared as a pandemic that outbreaks within almost 225 countries worldwide. For the time being, numerous mutations have been reported that led to the generation of numerous variants spread more rapidly. This study aims to establish an efficient multi-epitope subunit vaccine that could elicit both T-cell and B-cell responses sufficient to recognize three confirmed surface proteins of the virus. The sequences of the viral surface proteins, e.g., an envelope protein (E), membrane glycoprotein (M), and S1 and S2 domain of spike surface glycoprotein (S), were analyzed by an immunoinformatic approach. Top immunogenic epitopes have been selected based on the assessment of the affinity with MHC class-I and MHC class-II, population coverage, along with conservancy among wild type and new variants of SARS-CoV-2 genomes. Molecular docking and molecular dynamic simulation suggest that the proposed top peptides have the potential to interact with the highest number of both the MHC class I and MHC class II. The epitopes were assembled by the appropriate linkers to form a multi-epitope vaccine. Epitopes used in the vaccine construct are conserved in all the variants evolved till now. This in silico-designed multi-epitope vaccine is highly immunogenic and induces levels of SARS-CoV2-neutralizing antibodies in mice, which is detected by inhibition of cytopathic effect in Vero cell monolayer. Further studies are required to improve its efficiency in the prevention of virus replication in lung tissue, in addition to safety validation as a step for human application to combat SARS-CoV-2 variants. KEY POINTS: • We discovered five T-cell epitopes from three surface proteins of SARS-CoV-2. • These are conserved in the wild-type virus and variants, e.g., beta, delta, and omicron. • The multi-epitope vaccine can induce IgG in mice that can neutralize the virus.

Novel Galactopyranoside Esters: Synthesis, Mechanism, In Vitro Antimicrobial Evaluation and Molecular Docking Studies.

One-step direct unimolar valeroylation of methyl α-D-galactopyranoside (MDG) mainly furnished the corresponding 6-O-valeroate. However, DMAP catalyzed a similar reaction that produced 2,6-di-O-valeroate and 6-O-valeroate, with the reactivity sequence as 6-OH > 2-OH > 3-OH,4-OH. To obtain novel antimicrobial agents, 6-O- and 2,6-di-O-valeroate were converted into several 2,3,4-tri-O- and 3,4-di-O-acyl esters, respectively, with other acylating agents in good yields. The PASS activity spectra along with in vitro antimicrobial evaluation clearly indicated that these MDG esters had better antifungal activities than antibacterial agents. To rationalize higher antifungal potentiality, molecular docking was conducted with sterol 14α-demethylase (PDB ID: 4UYL, Aspergillus fumigatus), which clearly supported the in vitro antifungal results. In particular, MDG ester 7−12 showed higher binding energy than the antifungal drug, fluconazole. Additionally, these compounds were found to have more promising binding energy with the SARS-CoV-2 main protease (6LU7) than tetracycline, fluconazole, and native inhibitor N3. Detailed investigation of Ki values, absorption, distribution, metabolism, excretion, and toxicity (ADMET), and the drug-likeness profile indicated that most of these compounds satisfy the drug-likeness evaluation, bioavailability, and safety tests, and hence, these synthetic novel MDG esters could be new antifungal and antiviral drugs.

Can the SARS-CoV-2 Omicron Variant Confer Natural Immunity against COVID-19?

The coronavirus disease 2019 (COVID-19) pandemic is still ongoing, with no signs of abatement in sight. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is the causative agent of this pandemic and has claimed over 5 million lives, is still mutating, resulting in numerous variants. One of the newest variants is Omicron, which shows an increase in its transmissibility, but also reportedly reduces hospitalization rates and shows milder symptoms, such as in those who have been vaccinated. As a result, many believe that Omicron provides a natural vaccination, which is the first step toward ending the COVID-19 pandemic. Based on published research and scientific evidence, we review and discuss how the end of this pandemic is predicted to occur as a result of Omicron variants being surpassed in the community. In light of the findings of our research, we believe that it is most likely true that the Omicron variant is a natural way of vaccinating the masses and slowing the spread of this deadly pandemic. While the mutation that causes the Omicron variant is encouraging, subsequent mutations do not guarantee that the disease it causes will be less severe. As the virus continues to evolve, humans must constantly adapt by increasing their immunity through vaccination.

Molecular Docking and Dynamics Simulation of Natural Compounds from Betel Leaves (Piper betle L.) for Investigating the Potential Inhibition of Alpha-Amylase and Alpha-Glucosidase of Type 2 Diabetes.

Piper betle L. is widely distributed and commonly used medicinally important herb. It can also be used as a medication for type 2 diabetes patients. In this study, compounds of P. betle were screened to investigate the inhibitory action of alpha-amylase and alpha-glucosidase against type 2 diabetes through molecular docking, molecular dynamics simulation, and ADMET (absorption, distribution, metabolism, excretion, and toxicity) analysis. The molecule apigenin-7-O-glucoside showed the highest binding affinity among 123 (one hundred twenty-three) tested compounds. This compound simultaneously bound with the two-target proteins alpha-amylase and alpha-glucosidase, with high molecular mechanics-generalized born surface area (MM/GBSA) values (ΔG Bind = -45.02 kcal mol-1 for alpha-amylase and -38.288 for alpha-glucosidase) compared with control inhibitor acarbose, which had binding affinities of -36.796 kcal mol-1 for alpha-amylase and -29.622 kcal mol-1 for alpha-glucosidase. The apigenin-7-O-glucoside was revealed to be the most stable molecule with the highest binding free energy through molecular dynamics simulation, indicating that it could compete with the inhibitors' native ligand. Based on ADMET analysis, this phytochemical exhibited a wide range of physicochemical, pharmacokinetic, and drug-like qualities and had no significant side effects, making them prospective drug candidates for type 2 diabetes. Additional in vitro, in vivo, and clinical investigations are needed to determine the precise efficacy of drugs.

Phytochemical Compound Screening to Identify Novel Small Molecules against Dengue Virus: A Docking and Dynamics Study.

The spread of the Dengue virus over the world, as well as multiple outbreaks of different serotypes, has resulted in a large number of deaths and a medical emergency, as no viable medications to treat Dengue virus patients have yet been found. In this paper, we provide an in silico virtual screening and molecular dynamics-based analysis to uncover efficient Dengue infection inhibitors. Based on a Google search and literature mining, a large phytochemical library was generated and employed as ligand molecules. In this investigation, the protein target NS2B/NS3 from Dengue was employed, and around 27 compounds were evaluated in a docking study. Phellodendroside (-63 kcal/mole), quercimeritrin (-59.5 kcal/mole), and quercetin-7-O-rutinoside (-54.1 kcal/mole) were chosen based on their binding free energy in MM-GBSA. The tested compounds generated numerous interactions at Lys74, Asn152, and Gln167 residues in the active regions of NS2B/NS3, which is needed for the protein's inhibition. As a result, the stable mode of docked complexes is defined by various descriptors from molecular dynamics simulations, such as RMSD, SASA, Rg, RMSF, and hydrogen bond. The pharmacological properties of the compounds were also investigated, and no toxicity was found in computational ADMET properties calculations. As a result, this computational analysis may aid fellow researchers in developing innovative Dengue virus inhibitors.

Integrated Machine Learning and Chemoinformatics-Based Screening of Mycotic Compounds against Kinesin Spindle ProteinEg5 for Lung Cancer Therapy.

Among the various types of cancer, lung cancer is the second most-diagnosed cancer worldwide. The kinesin spindle protein, Eg5, is a vital protein behind bipolar mitotic spindle establishment and maintenance during mitosis. Eg5 has been reported to contribute to cancer cell migration and angiogenesis impairment and has no role in resting, non-dividing cells. Thus, it could be considered as a vital target against several cancers, such as renal cancer, lung cancer, urothelial carcinoma, prostate cancer, squamous cell carcinoma, etc. In recent years, fungal secondary metabolites from the Indian Himalayan Region (IHR) have been identified as an important lead source in the drug development pipeline. Therefore, the present study aims to identify potential mycotic secondary metabolites against the Eg5 protein by applying integrated machine learning, chemoinformatics based in silico-screening methods and molecular dynamic simulation targeting lung cancer. Initially, a library of 1830 mycotic secondary metabolites was screened by a predictive machine-learning model developed based on the random forest algorithm with high sensitivity (1) and an ROC area of 0.99. Further, 319 out of 1830 compounds screened with active potential by the model were evaluated for their drug-likeness properties by applying four filters simultaneously, viz., Lipinski's rule, CMC-50 like rule, Veber rule, and Ghose filter. A total of 13 compounds passed from all the above filters were considered for molecular docking, functional group analysis, and cell line cytotoxicity prediction. Finally, four hit mycotic secondary metabolites found in fungi from the IHR were screened viz., (-)-Cochlactone-A, Phelligridin C, Sterenin E, and Cyathusal A. All compounds have efficient binding potential with Eg5, containing functional groups like aromatic rings, rings, carboxylic acid esters, and carbonyl and with cell line cytotoxicity against lung cancer cell lines, namely, MCF-7, NCI-H226, NCI-H522, A549, and NCI H187. Further, the molecular dynamics simulation study confirms the docked complex rigidity and stability by exploring root mean square deviations, root mean square fluctuations, and radius of gyration analysis from 100 ns simulation trajectories. The screened compounds could be used further to develop effective drugs against lung and other types of cancer.

Singular and Combined Effects of Essential Oil and Honey of Eucalyptus Globulus on Anti-Inflammatory, Antioxidant, Dermatoprotective, and Antimicrobial Properties: In Vitro and In Vivo Findings.

Eucalyptus globulus is a plant widely used by the world population, including Morocco, in the treatment of several pathologies. The aim of this work is to evaluate the antioxidant, anti-inflammatory, dermatoprotective, and antimicrobial effects of essential oil and honey from E. globulus, as well as their combination. Chemical composition was determined by GC-MS analysis. The antioxidant activity was evaluated by three tests, namely, DPPH, reducing power, and the ß-carotene/linoleic acid assay. The anti-inflammatory activity was investigated in vitro (5-lipoxygenase inhibition) and in vivo (carrageenan-induced paw edema model), while the dermatoprotective activity was tested in vitro (tyrosinase inhibition). Moreover, the antibacterial activity was assessed using agar well diffusion and microdilution methods. The results showed that eucalyptol presents the main compound of the essential oil of E. globulus (90.14%). The mixture of essential oil with honey showed the best antioxidant effects for all the tests used (0.07 < IC50 < 0.19 mg/mL), while the essential oil was the most active against tyrosinase (IC50 = 38.21 ± 0.13 µg/mL) and 5-lipoxygenase (IC50 = 0.88 ± 0.01 µg/mL), which corroborated the in vivo test. Additionally, the essential oil showed the best bactericidal effects against all strains tested, with inhibition diameter values ranging from 12.8 to 21.6 mm. The findings of this work showed that the combination of the essential oil with honey showed important results in terms of biological activity, but the determination of the underlying mechanisms of action remains a major prospect to be determined.

Synthesis, Antimicrobial, Anticancer, PASS, Molecular Docking, Molecular Dynamic Simulations & Pharmacokinetic Predictions of Some Methyl ß-D-Galactopyranoside Analogs.

A series of methyl ß-D-galactopyranoside (MGP, 1) analogs were selectively acylated with cinnamoyl chloride in anhydrous N,N-dimethylformamide/triethylamine to yield 6-O-substitution products, which was subsequently converted into 2,3,4-tri-O-acyl analogs with different acyl halides. Analysis of the physicochemical, elemental, and spectroscopic data of these analogs revealed their chemical structures. In vitro antimicrobial testing against five bacteria and two fungi and the prediction of activity spectra for substances (PASS) showed promising antifungal functionality comparing to their antibacterial activities. Minimum inhibition concentration (MIC) and minimum bactericidal concentration (MBC) tests were conducted for four compounds (4, 5, 6, and 9) based on their activity. MTT assay showed low antiproliferative activity of compound 9 against Ehrlich's ascites carcinoma (EAC) cells with an IC50 value of 2961.06 µg/mL. Density functional theory (DFT) was used to calculate the thermodynamic and physicochemical properties whereas molecular docking identified potential inhibitors of the SARS-CoV-2 main protease (6Y84). A 150-ns molecular dynamics simulation study revealed the stable conformation and binding patterns in a stimulating environment. In-silico ADMET study suggested all the designed molecules to be non-carcinogenic, with low aquatic and non-aquatic toxicity. In summary, all these antimicrobial, anticancer and in silico studies revealed that newly synthesized MGP analogs possess promising antiviral activity, to serve as a therapeutic target for COVID-19.

In Silico Evaluation of Iranian Medicinal Plant Phytoconstituents as Inhibitors against Main Protease and the Receptor-Binding Domain of SARS-CoV-2.

The novel coronavirus disease 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which initially appeared in Wuhan, China, in December 2019. Elderly individuals and those with comorbid conditions may be more vulnerable to this disease. Consequently, several research laboratories continue to focus on developing drugs to treat this infection because this disease has developed into a global pandemic with an extremely limited number of specific treatments available. Natural herbal remedies have long been used to treat illnesses in a variety of cultures. Modern medicine has achieved success due to the effectiveness of traditional medicines, which are derived from medicinal plants. The objective of this study was to determine whether components of natural origin from Iranian medicinal plants have an antiviral effect that can prevent humans from this coronavirus infection using the most reliable molecular docking method; in our case, we focused on the main protease (Mpro) and a receptor-binding domain (RBD). The results of molecular docking showed that among 169 molecules of natural origin from common Iranian medicinal plants, 20 molecules (chelidimerine, rutin, fumariline, catechin gallate, adlumidine, astragalin, somniferine, etc.) can be proposed as inhibitors against this coronavirus based on the binding free energy and type of interactions between these molecules and the studied proteins. Moreover, a molecular dynamics simulation study revealed that the chelidimerine-Mpro and somniferine-RBD complexes were stable for up to 50 ns below 0.5 nm. Our results provide valuable insights into this mechanism, which sheds light on future structure-based designs of high-potency inhibitors for SARS-CoV-2.

Chemical Profiles and Pharmacological Properties with in Silico Studies on Elatostema papillosum Wedd.

The current study attempted, for the first time, to qualitatively and quantitatively determine the phytochemical components of Elatostema papillosum methanol extract and their biological activities. The present study represents an effort to correlate our previously reported biological activities with a computational study, including molecular docking, and ADME/T (absorption, distribution, metabolism, and excretion/toxicity) analyses, to identify the phytochemicals that are potentially responsible for the antioxidant, antidepressant, anxiolytic, analgesic, and anti-inflammatory activities of this plant. In the gas chromatography-mass spectroscopy analysis, a total of 24 compounds were identified, seven of which were documented as being bioactive based on their binding affinities. These seven were subjected to molecular docking studies that were correlated with the pharmacological outcomes. Additionally, the ADME/T properties of these compounds were evaluated to determine their drug-like properties and toxicity levels. The seven selected, isolated compounds displayed favorable binding affinities to potassium channels, human serotonin receptor, cyclooxygenase-1 (COX-1), COX-2, nuclear factor (NF)-κB, and human peroxiredoxin 5 receptor proteins. Phytol acetate, and terpene compounds identified in E. papillosum displayed strong predictive binding affinities towards the human serotonin receptor. Furthermore, 3-trifluoroacetoxypentadecane showed a significant binding affinity for the KcsA potassium channel. Eicosanal showed the highest predicted binding affinity towards the human peroxiredoxin 5 receptor. All of these findings support the observed in vivo antidepressant and anxiolytic effects and the in vitro antioxidant effects observed for this extract. The identified compounds from E. papillosum showed the lowest binding affinities towards COX-1, COX-2, and NF-κB receptors, which indicated the inconsequential impacts of this extract against the activities of these three proteins. Overall, E. papillosum appears to be bioactive and could represent a potential source for the development of alternative medicines; however, further analytical experiments remain necessary.

Elucidating the Glucokinase Activating Potentials of Naturally Occurring Prenylated Flavonoids: An Explicit Computational Approach.

Glucokinase activators are considered as new therapeutic arsenals that bind to the allosteric activator sites of glucokinase enzymes, thereby maximizing its catalytic rate and increasing its affinity to glucose. This study was designed to identify potent glucokinase activators from prenylated flavonoids isolated from medicinal plants using molecular docking, molecular dynamics simulation, density functional theory, and ADMET analysis. Virtual screening was carried out on glucokinase enzymes using 221 naturally occurring prenylated flavonoids, followed by molecular dynamics simulation (100 ns), density functional theory (B3LYP model), and ADMET (admeSar 2 online server) studies. The result obtained from the virtual screening with the glucokinase revealed arcommunol B (-10.1 kcal/mol), kuwanon S (-9.6 kcal/mol), manuifolin H (-9.5 kcal/mol), and kuwanon F (-9.4 kcal/mol) as the top-ranked molecules. Additionally, the molecular dynamics simulation and MM/GBSA calculations showed that the hit molecules were stable at the active site of the glucokinase enzyme. Furthermore, the DFT and ADMET studies revealed the hit molecules as potential glucokinase activators and drug-like candidates. Our findings suggested further evaluation of the top-ranked prenylated flavonoids for their in vitro and in vivo glucokinase activating potentials.