Molecular Operating Environment Software Research Articles

Design, Synthesis and Investigation of New Diphenyl Substituted Pyridazinone Derivatives as Both Cholinesterase and Aβ-Aggregation Inhibitors.

With respect to the increase in the average life expectancy, Alzheimer Disease (AD), the most common form of age-related dementia, has become a major threat to the population over the age of 65 during the past several decades. The majority of AD treatments are focused on cholinergic and amyloid hypotheses. In this study, three series of diphenyl-2-(2-(4-substitutedpiperazin-1-yl)ethyl)pyridazin- 3(2H)-one derivatives were designed, synthesized and investigated for their ability to inhibit both cholinesterase enzymes and amyloid-β aggregation. The inhibitory activities of the synthesized compounds on AChE (from electric eel) and BChE (from equine serum) were determined by the modified Ellman's method. The reported thioflavin T-based fluorometric assay was performed to investigate the effect of the selected compounds on the aggregation of Aβ1-42. The cytotoxic effect of the compounds (4g, 11g and 18g) was monitored in 3T3 cell lines to gain insight into therapeutic potential of the compounds by using MTT assay. The crystal structures of the AChE (1EVE) and BChE (1P0I) enzymes were retrieved from the RCSB Protein Data Bank and Molecular Operating Environment (MOE) software was used for molecular docking of the ligands. Among the tested compounds, 5,6-diphenyl derivative 18g was identified as the most potent and selective AChE inhibitor (IC50 = 1.75 µM, Selectivity Index for AChE > 22.857). 4,6- Diphenyl derivative 11g showed the highest and the most selectivity for BChE (IC50= 4.97 µM, SI for AChE < 0.124). Interestingly, 4,5-diphenyl derivative 4g presented dual cholinesterase inhibition (AChE IC50= 5.11 µM; BChE IC50= 14.16 µM, SI for AChE = 2.771). Based on biological activity results and low toxicity of the compounds, it can be said that diphenyl substituted pyridazinone core is a valuable scaffold. Especially, dual inhibitory potencies of 4,5-diphenylpyridazin-3(2H)-one core for the cholinesterase enzymes and Aβ- aggregation makes this core a promising disease-modifying agent.

Anti-eczematic and molecular modeling of anthraquinones isolated from the seeds of Asphodelus microcarpus salzm. viv. growing in Egypt

Background: Eczema or atopic dermatitis is a widely spread skin disorder; the topical application of corticosteroids is the first choice for treatment. Natural products have a great contribution in the treatment of this disease; Asphodelus microcarpus seeds are rich in anthraquinones and known to possess both anti-inflammatory and antidermatitis effects. Objective: The objective of the study is to investigate the anti-eczematic activity, acute toxicity, and molecular modeling of A. microcarpus seeds. Materials and Methods: Nuclear magnetic resonance, ultraviolet, and mass spectroscopy were applied for characterization of isolated metabolites; induction of eczema was conducted by 2% and 0.2% w/v dinitrochlorobenzene in acetone; eczema was treated with topical application of the different seed extracts in the form of ointments (1% w/w); Swiss albino mice (25–30 g) were used for the determination of LD50and anti-eczematic effect. Docking studies were performed by Molecular Operating Environment software. Results: A. microcarpus seed extract exhibited promising ant-eczematic activity, six anthraquinones were isolated from chloroform portion and characterized as 10,7'-bichrysophanol (1), asphodelin (2), chrysophanol-8-O-methyl ether (3), chrysophanol (4), physcion (5), and emodin (6). Compounds 1, 3, and 5 exerted significant anti-eczematic effect. Conclusion: Six known anthraquinone derivatives were isolated and characterized for the first time from the seeds of A. microcarpus. Chloroform fraction (1% w/w) showed significant anti-eczematic effect compared to standard mometasone furoate (0.1 w/w). The docking study proved the anti-eczematic activity of anthraquinone content by their affinity to the target human histamine H1receptor.

In Silico Cholinesterase and Monoamine Oxidase Inhibitory Activities of Perillaldehyde and D-Limonene, Main Compounds of Essential Oil of Algerian Ammodaucus leucotrichus

In a continuation of our previous work for the exploration of novel enzyme inhibitors, molecular modeling was used to inspect the binding mode of perillaldehyde and D-limonene, the major compounds of essential oil of Algerian Ammodaucus leucotrichus into the active site pocket of cholinesterase (AChE and BuChE) and Monoamine Oxidase (MAO). The molecular docking was carried out using Molecular Operating Environment (MOE) software package. Docking analysis showed that this compounds (perilladehyde and D-limonene) can interact with both the Catalytic Active Site (CAS) of AChE, BuChE and MAO. For D-limonene, molecular docking showed favorable H-phi interaction with catalytic residue of AchE and BuChE. The perillaldehyde showed best interaction profile with BuChE as compared with compound D-Limonene. The best interaction between perilladehyde and monoamine oxidase was also revealed. This paper shows best correlation between the in vitro study and the in silico molecular docking study of anti-cholinesterase and anti-monoamine oxidase activities.

Design, Synthesis, and Biological Evaluation of New Azole Derivatives as Potent Aromatase Inhibitors with Potential Effects against Breast Cancer.

Some aromatase inhibitors are FDA-approved agents as first-line therapy in the treatment of endocrine-responsive breast cancer. In this study, we aimed to develop new azole derivatives with higher specificity and potency. New aromatase inhibitors were designed by Molecular Operating Environment (MOE) software and synthesized in a one-step SN2 reaction. These compounds were characterized by melting point, 1H- and 13CNMR, elemental analysis and mass spectra. The in vitro and in vivo aromatase inhibition of these compounds was evaluated using the Estrone ELISA assay, and by measuring the inhibition of androstenedione-induced uterine hypertrophy. The selectivity of aromatase inhibition was investigated by the inhibition of ACTH stimulation on the plasma concentrations of aldosterone and cortisol. Docking simulations showed that four new azole derivatives could efficiently interact with enzyme active sites. The in vitro aromatase-inhibition assay showed that the compounds 1,3,5-tris(imidazol-1- ylmethyl)benzene (3b) and 1,3-Bis(imidazole-1- ylmethyl) benzene (3d) effectively inhibited aromatase, with IC50 values of 0.2 nM and 6.8 nM, respectively; these values were similar to known aromatase inhibitor letrozole (IC50 0.3 nM). The in vivo aromatase-inhibitory potency of compound 3b was similar to letrozole, although compound 3b acted more selectively. This report introduced a new compound that can be considered as a new lead for further investigation to explore more-potent and more-selective aromatase inhibitors.

Virtual screening using covalent docking to find activators for G245S mutant p53.

TP53 is the most mutated gene in all cancers. The mutant protein also accumulates in cells. The high frequency of p53 mutations makes the protein a promising target for anti-cancer therapy. Only a few molecules have been found, using in vitro screening, to reactivate the mutant protein. APR-246 is currently the most successful mutant p53 activator, which reactivates the transcriptional activity of p53 by covalently binding to C124 of the protein. We have recently created in silico models of G245S-mp53 in its apo and DNA-bound forms. In this paper we further report on our in silico screening for potential activators of G245S-mp53. We filtered the ZINC15 database (13 million compounds) to only include drug-like molecules with moderate to standard reactivity. Our filtered database of 130,000 compounds was screened using the DOCKTITE protocol in the Molecular Operating Environment software. We performed covalent docking at C124 of G245S-mp53 to identify potential activators of the mutant protein. The docked compounds were ranked using a consensus scoring approach. We also used ADMET Predictor™ to predict pharmacokinetics and the possible toxicities of the compounds. Our screening procedure has identified compounds, mostly thiosemicarbazones and halo-carbonyls, with the best potential as G245S-mp53 activators, which are described in this work. Based on its binding scores and ADMET risk score, compound 2 is likely to have the best potential as a G245S-mp53 activator compared to the other top hits.

Identification of MMP9 as a novel key gene in mantle cell lymphoma based on bioinformatic analysis and design of cyclic peptides as MMP9 inhibitors based on molecular docking.

Mantle cell lymphoma (MCL) is an aggressive disease. MCL is associated with poor patient prognosis and limited survival. To identify key genes and explore targeting cyclic peptide inhibitors for the treatment of MCL, we downloaded two gene expression profiles (GSE32018 and GSE9327) from the Gene Expression Omnibus (GEO) database. We screened 84 differentially expressed genes (DEGs). Pathway analysis showed that DEMs were mainly enriched in the ‘Pathway in cancer’, ‘PI3K-Akt signaling pathway’, ‘Cytokine-cytokine receptor interaction’, ‘Rap1 signaling pathway’, ‘NF-κB signaling pathway’ and ‘Leukocyte trans-endothelial migration’. We subsequently constructed a protein-protein interaction (PPI) network of DEGs. In addition, matrix metalloproteinase 9 (MMP9) with a high degree in the PPI network was identified as a hub gene in MCL. Meanwhile in the Molecular Complex Detection (MCODE) analysis, MMP9 was located in the important cluster. Thus, MMP9 can be used as a therapeutic target for MCL and we designed cyclic peptides as MMP9 inhibitors. MMP9 protein structure was gathered from the Protein Data Bank (PDB), with a PDB ID: 1L6J. MMP9 and cyclic peptides were docked using Molecular Operating Environment (MOE) software after structural optimization. It was revealed that cyclic peptide 2 bound deeply in the binding pocket of MMP9 and had interaction with the active-site Zn2+ ion in the catalytic domain. Cyclic peptides 1, 2, 4–6 also displayed potential interaction with active residues of MMP9; thus, these cyclic peptides can serve as potential drug candidates to block MMP9 activity and future studies are warranted to confirm their efficacy.

Design, Synthesis and Microbiological Evaluation of Novel Compounds as Potential Staphylococcus aureus Phenylalanine tRNA Synthetase Inhibitors.

AS THE RESISTANCE of Staphylococcus aureus to antibiotics represents a major threat to global health, anti-infectives with novel mechanisms must be developed. Novel compounds were generated as potential phenylalanine tRNA synthetase (PheRS) inhibitors based on the published homology model of S. aureus PheRS to aid the design process using Molecular Operating Environment (MOE) software. PheRS was selected as it is structurally unique enzyme among the aminoacyl-tRNA synthetases (aaRS), it is considerably different from human cytosolic and human mitochondrial aaRS and it is essential and conserved across bacterial species. The designed compounds were synthesized according to different clear schemes. The compounds were confirmed by 1H NMR, 13C NMR, HRMS and/or microanalysis, and they were microbiologically evaluated.

Anti-hepatitis C virus activity and synergistic effect of Nymphaea alba extracts and bioactive constituents in liver infected cells

BackgroundWithout an effective vaccine, hepatitis C virus (HCV) remains a global threat, inflicting 170–300 million carriers worldwide at risk of cirrhosis and hepatocellular carcinoma (HCC). Though various direct acting antivirals have been redeemed the hepatitis C treatment, a few restraints persist including possible side effects, viral resistance emergence, excessive cost which restricts its availability to a common person. HypothesisThere is no preventive HCV vaccine available today so the discovery of potent antiviral natural flora and their bioactive constituents may help to develop preventive cures against HCV infection. Study designIn current study, we aim to clarify anti-HCV activity of methanol and acetone extracts along with the purified fractions of Pakistani local plant, Nymphaea alba L (N. alba) using Huh-7 cell line as transfection model. Synergistic study of purified fractions with interferon was performed using MDBK cell line (expressing interferon receptors) as transfection model. Materials and methodsRecent study by our research group has observed potent anti-HCV NS3 protease activity of methanol and acetone extracts of N. alba. Effect of N. alba extracts, its fractions precisely, the N1 and N8 fractions on HCV replication was demonstrated by analyzing viral gene expression using in vitro transfection model. Considering NS3 protease as a dynamic drug target, fourteen phytochemicals of N. alba were selected as ligands for interaction with NS3 protein using Molecular Operating Environment (MOE) software. Boceprevir, FDA approved NS3 protease inhibitor, was used as standard for comparative study in docking screening. ResultsHerein we report 84% and 94% reduction of 3a genotype of HCV NS3/4A gene expression at mRNA level at non-toxic concentration. Specifically, two fractions ‘N1’ & ‘N8’ isolated from acetone extract suppressed HCV NS3 gene expression in transfected target cells with an EC50 value of 37 ± 0.03 μg/ml and 20 ± 0.02 μg/ml respectively. Similarly, viral genotype 1a replication is strongly suppressed in target cells by N. alba flower extracts and purified fractions. Moreover, combination of fractions with standard antiviral drug displayed synergistic effects for inhibition of HCV replication. Phytochemicals including Isoquercetin, Hyperoside, Quercetin, Reynoutrin, Apigenin and Isokaempferide displayed minimum binding energies as compared to standard protease inhibitor. ConclusionN. alba and its purified phytochemicals with new scaffolds might significantly serve as valuable and alternative regimen against HCV either alone or in combination with other potential anti-HCV agents.

Efficiency of newly prepared thiazole derivatives against some cutaneous fungi

A series of fourteen novel synthesized arylazothiazole and arylhydrazothiazole derivatives were tested for their antifungal activity and structure-activity relationship. The activity of the compounds depends mainly on the side chains of the nucleus compound. The antifungal activity was more significant when both side chains are aromatic > one aromatic and one aliphatic and substituted aromatic with CH3 or OCH3 > non-substituted > substituted aromatic with chloro- or nitro-groups. Thiazole derivatives 7a, 7c, 7e, 7f, 7 g, 7i, 7 m, and 11a showed the most effective as antifungal compounds and were comparable with fluconazole as antifungal reference drug when investigated against Candida albicans, Microsporum gypseum and Trichophyton mentagrophytes. The minimum inhibitory concentration (MIC) reached 2 µg/mL in the case of C. albicans for compounds 7a, 7b, 7c and 11a and measured 4 µg/mL in the case of M. gypseum and T. mentagrophytes for the same compounds. The minimum fungicidal concentration (MFC) for the same compounds was 4 µg/mL for C. albicans and ranged from 8 to 32 µg/mL for the other two fungi. The results revealed that compounds 7c and 11a were the most antifungal compounds against the test fungi regarding keratinase activity and ergosterol biosynthesis. The in vivo efficacy of synthesized thiazoles 7c and 11a applied at their respective MFC was more effective in the treatment of skin infection of guinea pigs previously inoculated with the test fungi as compared with fluconazole. The Molecular Operating Environment (MOE) software was used to analyze the docking poses and binding energies of compound 11a and keratinase. The computational studies supported the biological activity results.

In-silico Studies of Isolated Phytoalkaloid Against Lipoxygenase: Study Based on Possible Correlation

Lipoxygenase (LOX) enzymes play an important role in the pathophysiology of several inflammatory and allergic diseases including bronchial asthma, allergic rhinitis, atopic dermatitis, allergic conjunctivitis, rheumatoid arthritis and chronic obstructive pulmonary disease. Inhibitors of the LOX are believed to be an ideal approach in the treatment of diseases caused by its over-expression. In this regard, several synthetic and natural agents are under investigation worldwide. Alkaloids are the most thoroughly investigated class of natural compounds with outstanding past in clinically useful drugs. In this article, we have discussed various alkaloids of plant origin that have already shown lipoxygenase inhibition in-vitro with possible correlation in in silico studies. Molecular docking studies were performed using MOE (Molecular Operating Environment) software. Among the ten reported LOX alkaloids inhibitors, derived from plant, compounds 4, 2, 3 and 1 showed excellent docking scores and receptor sensitivity. These compounds already exhibited in vitro lipoxygenase inhibition and the MOE results strongly correlated with the experimental results. On the basis of these in vitro assays and computer aided results, we suggest that these compounds need further detail in vivo studies and clinical trial for the discovery of new more effective and safe lipoxygenase inhibitors. In conclusion, these results might be useful in the design of new and potential lipoxygenase (LOX) inhibitors.

FIRST STUDY ON ANTI-DIABETIC EFFECT OF ROSEMARY AND SALVIA BY USING MOLECULAR DOCKING

Nowadays use of medicinal plants and traditional medicine is important research subject over the world attracting researchers from different research filed to look for less use of synthesized drugs because of their secondary effects on human health. In this paper we use molecular modeling and molecular docking as tools for valorization of natural’s plants in medicinal use. Computational chemistry permits saving time and money in studying medicinal plants role by prediction of molecules inhibition actions of enzymes. Rosemary and Salvia (it’s suitable that author use the latin name of the plants) have been the subject of many classic studies for therapeutic use (antioxidant, antiseptic...) but never (see references of some studies related to antidiabetic effect of rosemary) studied for anti-diabetic effect. In our study we predict interaction of main terpanoids from Rosemary and Salvia by investigating inhibition process of DPP-4 enzyme using Molecular Operating Environment software. Obtained results show and describe capacity of natural’s molecules from Rosemary and Salvia in inhibition of DPP-4 enzyme. The molecule from Rosemary and Salvia which is the best inhibitor of DPP-4 has been identified.

Prediction of the char formation of polybenzoxazines: The effect of heterogeneities in the crosslinked network to the prediction accuracy in quantitative structure-properties relationship (QSPR) model

Molecular Operating Environment (MOE) software has great potential when combined with the Quantitative Structure-Property Relationship (QSPR) approach, and was proven to be useful to make good prediction models for series of polybenzoxazines [1–3]. However, the effect of heterogeneities in the crosslinked network to the prediction accuracy is yet to be tested. It was found that polybenzoxazines with polymerisable functional group (e.g. acetylene-based benzoxazines) form up to 40% higher char yield compared to their analogue polybenzoxazines due to the contribution of the polymerisable functional group (e.g. ethynyl triple bond) in the cross-linked network. In order to investigate the effect of the inconsistent cross-linking network, a data set consisting of thirty-three benzoxazines containing various structures of benzoxazines was subdivided into two smaller data sets based on their functional group, either benzoxazines with polymerisable functional group (acetylene-based benzoxazines set (Ace-M)) or non-polymerisable functional group (aniline-based benzoxazines (Ani-M)). Char yield predictions for the polybenzoxazines for these data sets (Ace-M and Ani-M) were compared with the larger thirty-three polybenzoxazines data set (GM) to investigate the effect of the inconsistency in crosslink network on the quality of prediction afforded by the model. Prediction performed by Ace-M and Ani-M were found to be more accurate when compared with the GM with total prediction error of 3.15% from both models compared to the GM (4.81%). Ace-M and Ani-M are each better at predicting the char yields of similar polybenzoxazines (i.e. one model is specific for a polymerisable functional group; the other for non-polymerisable functional group), but GM is more practical as it has greater ‘general’ utility and is applicable to numerous structures. The error shown by GM is considerably small and therefore it is still a good option for prediction and should not be underestimated.

COMP presents division awards

The ACS Division of Computers in Chemistry (COMP) presented the following awards at the spring 2017 ACS national meeting in San Francisco. The OpenEye Outstanding Junior Faculty Award in Computational Chemistry assists new faculty members in gaining visibility in the COMP community. The winners are Tom Kurtzman, Lehman College; Benjamin Levine, Michigan State University; Marco De Vivo, Italian Institute of Technology; and Bryan Wong, University of California, Riverside. Each winner received a $1,000 prize. The Chemical Computing Group Excellence Award for Graduate Students recognizes outstanding research performance by a graduate student in computational chemistry. The recipients are Fiona Kearns, University of South Florida; Patrick Lestrange, University of Washington; Elvira Sayfutyarova, Princeton University; Kayla Sprenger, University of Washington; and Mingzhen Zhang, University of Akron. The winners each received $1,150 and a copy of CCG’s Molecular Operating Environment software with a one-year lic...

Optimization enhanced genetic algorithm-support vector regression for the prediction of compound retention indices in gas chromatography

A new method using genetic algorithm and support vector regression with parameter optimization (GA–SVR–PO) was developed for the prediction of compound retention indices (RI) in gas chromatography. The dataset used in this work consists of 252 compounds extracted from the Molecular Operating Environment (MOE) boiling point database. Molecular descriptors were calculated by descriptor tools of the MOE software package. After removing redundant descriptors, 151 descriptors were obtained for each compound. A genetic algorithm (GA) was used to select the best subset of molecular descriptors and the best parameters of SVR to optimize the prediction performance of compound retention indices. A 10-fold cross-validation method was used to evaluate the prediction performance. We compared the performance of our proposed model with three existing methods: GA coupled with multiple linear regression (GA–MLR), the subset selected by GA–MLR used to train SVR (GA–MLR–SVR), and GA on SVR (GA–SVR). The experimental results demonstrate that our proposed GA–SVR–PO model has better predictive performance than other existing models with R2>0.967 and RMSE=49.94. The prediction accuracy of GA–SVR–PO model is 96% at 10% of prediction variation.

Exploring the binding sites of Staphylococcus aureus phenylalanine tRNA synthetase: A homology model approach

Increased resistance of MRSA (multidrug resistance Staphylococcus aureus) to anti-infective drugs is a threat to global health necessitating the development of anti-infectives with novel mechanisms of action. Phenylalanine tRNA synthetase (PheRS) is a unique enzyme of the aminoacyl-tRNA synthetases (aaRSs), which are essential enzymes for protein biosynthesis. PheRS is an (αb)2 tetrameric enzyme composed of two alpha subunits (PheS) and two larger beta subunits (PheT). Our potential target in the drug development for the treatment of MRSA infections is the phenylalanine tRNA synthetase alpha subunit that contains the binding site for the natural substrate. There is no crystal structure available for S. aureus PheRS, therefore comparative structure modeling is required to establish a putative 3D structure for the required enzyme enabling development of new inhibitors with greater selectivity. The S. aureus PheRS alpha subunit homology model was constructed using Molecular Operating Environment (MOE) software. Staphylococcus haemolyticus PheRS was the main template while Thermus thermophilus PheRS was utilised to predict the enzyme binding with tRNAphe. The model has been evaluated and compared with the main template through Ramachandran plots, Verify 3D and Protein Statistical Analysis (ProSA). The query protein active site was predicted from its sequence using a conservation analysis tool. Docking suitable ligands using MOE into the constructed model were used to assess the predicted active sites. The docked ligands involved the PheRS natural substrate (phenylalanine), phenylalanyl-adenylate and several described S. aureus PheRS inhibitors.

A Note Study on Antidiabetic Effect of Main Molecules Contained in Clove Using Molecular Modeling Interactions with DPP-4 Enzyme

Clove (<i>Syzygium aromaticum</i>) is precious spice used over the world in cuisine and medical treatment. Essential clove oil contains many bioactive molecules which have therapeutic interest. In this work we study interactions of DPP-4 enzyme (responsible of diabetes type 2) with main molecules contained in clove essential oil using molecular mechanic, molecular dynamics and molecular docking (method which predicts the preferred orientation of one molecule to a second when bound to each other to form a stable complex). Molecular Operating Environment software was used. The obtained results show that Acetyleugenol molecule is the best inhibitor of DPP-4 enzyme according to score energy. As a conclusion we can say that clove has a significant influence on diabetes treatment.

Molecular Modeling and Biological Activities of New Potent Antimicrobial, Anti-Inflammatory and Anti-Nociceptive of 5-Nitro Indoline-2-One Derivatives

In recent years, molecular modeling has become an important technique for drug discovery and pharmaceutical science. The objective of this study is to determine the molecular modeling of the antibacterial, anti-inflammatory and anti-nociceptive activities of a new series of pyrazoles, oxadiazoles and sugar hydrazines of 5-nitroindolin-2- one derivatives. The molecular modeling protocol was applied using the MOE (Molecular Operating Environment) software. Synthetic compounds 1, 3, 8, 9, 10 and 12 were the most active compounds, as antibacterial, antiinflammatory and anti-nociceptive activities were studied for the binding affinity of the cyclooxygenase1 (COX1), The glucocorticoid receptor (GR), the cytochrome P450 receptor of 14alfa-sterol demethylases (CYP51) and the dihydroprotease synthase receptor. Molecular modeling studies revealed that the [(methylbenzyl)-5-nitro-2- oxoindolin-3-ylideneamino-benzohydrazide derivative (3) gave a score of (-15.8587 kcal/mol), while 1,3,4-oxadiazol- 2-yl) phenylimino)-1-(methylbenzyl)-5-nitroindolin-2-one derivative (9) gave a higher score (-16.8038 kcal/mol) than flucanazole Co-crystallized gave a score of (-10.2837 kcal/mol). However, the compound (12), D-Arabinose- (methylbenzyl)-5-nitro-2-oxoindolin-(3-ylideneamino) hydrazone derivative gave a score of (-24.6577 kcal/mol) greater than the co-crystallized ligand which gave a score of (-16.6717 kcal/mol).

In Silico Study of Alkaloids as α-Glucosidase Inhibitors: Hope for the Discovery of Effective Lead Compounds.

α-Glucosidase (extinction coefficient 3.2.1.20) is a primary carbohydrate metabolizing enzyme that acts on the 1–4 associated α-glucose residues. The inhibition of α-glucosidase slows down the process of carbohydrate digestion and avoids postprandial hyperglycemia, which is a major cause of chronic diabetes-associated complication. This study was designed to evaluate the binding capacity of isolated alkaloids with targeted receptor. For this purpose, the three-dimensional tertiary structure of the α-glucosidase was generated by using the Molecular Operating Environment (MOE). The generated model was then validated by using the RAMPAGE and ERRAT server. The molecular docking of 37 alkaloids along with standard acarbose and miglitol reported as a α-glucosidase inhibitor was performed via MOE-Dock implemented in MOE software to find the binding modes of these inhibitors. The results showed that compound 17 (oriciacridone F) and 24 (O-methylmahanine) demonstrated marked interaction with active residues and were comparable to standard inhibitors. In short, this study provided computational background to the reported α-glucosidase inhibitors and thus further detail studies could lead to novel effective compounds.

Therapeutic potential of Taraxacum officinale against HCV NS5B polymerase: In-vitro and In silico study.

Discovery of alternative and complementary regimens for HCV infection treatment is a need of time from clinical as well as economical point of views. Low cost of bioactive natural compounds production, high biochemical diversity and inexistent/milder side effects contribute to new therapies. Aim of this study is to clarify anti-HCV role of Taraxacum officinale, a natural habitat plant rich of flavonoids. In this study, methanol extract of T. officinale leaves was initially analyzed for its cytotoxic activity in human hepatoma (Huh-7) and CHO cell lines. Hepatoma cells were transfected with pCR3.1/Flagtag/HCV NS5B gene cloned vector (genotype 1a) along with T. officinale extract. Considering NS5B polymerase as potential therapeutic drug target, twelve phytochemicals of T. officinale were selected as ligands for molecular interaction with NS5B protein using Molecular Operating Environment (MOE) software. Sofosbuvir (Sovaldi: brand name) currently approved as new anti-HCV drug, was used as standard in current study for comparative analysis in computational docking screening. HCV NS5B polymerase as name indicates plays key role in viral genome replication. On the basis of which NS5B gene is targeted for determining antiviral role of T. officinale extract and 65% inhibition of NS5B expression was documented at nontoxic dose concentration (200μg/ml) using Real-time PCR. In addition, 57% inhibition of HCV replication was recorded when incubating Huh-7 cells with high titer serum of HCV infected patients along with leaves extract. Phytochemicals for instance d-glucopyranoside (-31.212 Kcal/mol), Quercetin (-29.222 Kcal/mol), Luteolin (-26.941 Kcal/mol) and some others displayed least binding energies as compared to standard drug Sofosbuvir (-21.0746 Kcal/mol). Results of our study strongly revealed that T. officinale leaves extract potentially blocked the viral replication and NS5B gene expression without posing any toxic effect on normal fibroblast cells of body.

Developing (Quantitative Structure Property Relationships) QSPR Techniques to Predict the Char Formation of Polybenzoxazines.

This study uses the Molecular Operating Environment software (MOE) to generate models to calculate the char yield of polybenzoxazines (PBz). A series of benzoxazine (Bz) monomers were constructed to which a variety of parameters relating to the structure (e.g., water accessible surface, negative van der Waals surface area and hydrophobic volume, etc.) were obtained and a quantitative structure property relationships (QSPR) model was generated. The model was used to generate data for new Bz monomers with desired properties and a comparison was made of predictions based on the QSPR model with the experimental data. This study shows the quality of predictive models and confirms how useful computational screening is prior to synthesis.