Primjene teorije grafova: topologijski modeli za predvi|anje CDK-1 inhibicijske aktivnosti aloizina

Relationship between the topological indices and cyclin-dependent kinase-1 (CDK-1/cyclin B) inhibitory activity of 6-phenyl[5H]pyrrolo[2,3-b]pyrazines (aloisines) was investigated. Three topological indices – the Wiener Index, a distance-based topological descriptor, the Zagreb group parameter, an adjacency based topological descriptor, and the eccentric connectivity index, an adjacency-cum-distance based topological descriptor were used in the study. A data set comprising 51 analogues of aloisine was selected for the present study. Values of the Wiener index, the Zagreb group parameter and the eccentric connectivity index for each of the 51 analogues included in the data set were computed using an in-house computer program. Resultant data was analyzed and suitable models were developed after identification of active ranges. A biological activity was then assigned to each compound using these models, which was then compared with the reported CDK-1 inhibitory activity. Accuracy of prediction using these models was found to vary from a minimum of ≈82 % to a maximum of 84 %. .Istraživan je odnos izmđ|u topologijskih indeksa i CDK-1 inhibicijske aktivnosti 5-fenil[5H]pirolo[2,3-b]- pirazina (aloizina). Upotrebljena su tri topologijska indeksa: Wienerov indeks, zagrebački indeks i ekscentrični indeks povezanosti, koji su izračunani za 51 aloizin. Dobiveni modeli predviđaju inhibijsku aktivnosti aloizina s točnošću od 82–84 %

Primjene teorije grafova: topologijski modeli za predvi|anje CDK-1 inhibicijske aktivnosti aloizina

Relationship between the topological indices and cyclin-dependent kinase-1 (CDK-1/cyclin B) inhibitory activity of 6-phenyl[5H]pyrrolo[2,3-b]pyrazines (aloisines) was investigated. Three topological indices – the Wiener Index, a distance-based topological descriptor, the Zagreb group parameter, an adjacency based topological descriptor, and the eccentric connectivity index, an adjacency-cum-distance based topological descriptor were used in the study. A data set comprising 51 analogues of aloisine was selected for the present study. Values of the Wiener index, the Zagreb group parameter and the eccentric connectivity index for each of the 51 analogues included in the data set were computed using an in-house computer program. Resultant data was analyzed and suitable models were developed after identification of active ranges. A biological activity was then assigned to each compound using these models, which was then compared with the reported CDK-1 inhibitory activity. Accuracy of prediction using these models was found to vary from a minimum of ≈82 % to a maximum of 84 %. .Istraživan je odnos izmđ|u topologijskih indeksa i CDK-1 inhibicijske aktivnosti 5-fenil[5H]pirolo[2,3-b]- pirazina (aloizina). Upotrebljena su tri topologijska indeksa: Wienerov indeks, zagrebački indeks i ekscentrični indeks povezanosti, koji su izračunani za 51 aloizin. Dobiveni modeli predviđaju inhibijsku aktivnosti aloizina s točnošću od 82–84 %

QSAR models for prediction of PPARδ agonistic activity of indanylacetic acid derivatives

Peroxisome Proliferator Activated Receptor b/d (PPAR b/d), one of three PPAR isoforms is a member of nuclear receptor superfamily and ubiquitously expressed in several metabolically active tissues such as liver, muscle, and fat. Tissue specific expression and knock-out studies suggest a role of PPARd in obesity and metabolic syndrome. Specific and selective PPARd ligands may play an important role in the treatment of metabolic disorders. Indanylacetic acid derivatives reported as potent and specific ligands against PPARd have been studied for the Quantitative Structure – Activity Relationships (QSAR). Molecules were represented by chemical descriptors that encode constitutional, topological, geometrical, and electronic structure features. Four different approaches, i.e., random selection, hierarchical clustering, k-means clustering, and sphere exclusion method were used to classify the dataset into training and test subsets. Forward stepwise Multiple Linear Regression (MLR) approach was used to linearly select the subset of descriptors and establish the linear relationship with PPARd agonistic activity of the molecules. The models were validated internally by Leave One Out (LOO) and externally for the prediction of test sets. The best subset of descriptors was then fed to the Artificial Neural Networks (ANN) to develop non-linear models. Statistically significant MLR models; with R2 varying from 0.80 to 0.87 were generated based on the different training and test set selection methods. Training of ANNs with different architectures for the different training and test selection methods resulted in models with R2 values varying from 0.83 to 0.94, which indicates the high predictive ability of the models.info:eu-repo/semantics/publishedVersio

Comparative QSAR analyses of competitive CYP2C9 inhibitors using three-dimensional molecular descriptors

One of the biggest challenges in QSAR studies using three-dimensional descriptors is to generate the bioactive conformation of the molecules. Com parative QSAR analyses have been performed on a dataset of 34 structurally diverse and competitive CYP2C9 inhibitors by generating their lowest energy conformers as well as additional multiple conformers for the calculation of molecular de scriptors. Three-dimensional descriptors account ing for the spatial characteristics of the molecules calculated using E-Dragon were used as the inde pendent variables. The robustness and the predic tive performance of the developed models were verified using both the internal [leave-one-out (LOO)] and external statistical validation (test set of 12 inhibitors). The best models (MLR using GET AWAY descriptors and partial least squares using 3D-MoRSE) were obtained by using the multiple conformers for the calculation of descriptors and were selected based upon the higher external pre diction (R2 test values of 0.65 and 0.63, respectively) and lower root mean square error of prediction (0.48 and 0.48, respectively). The predictive ability of the best model, i.e., MLR using GETAWAY de scriptors was additionally verified on an external test set of quinoline-4-carboxamide analogs and resulted in an R2 test value of 0.6. These simple and alignment-independent QSAR models offer the possibility to predict CYP2C9 inhibitory activity of chemically diverse ligands in the absence of X-ray crystallographic information of target protein structure and can provide useful insights about the ADMET properties of candidate molecules in the early phases of drug discovery.info:eu-repo/semantics/publishedVersio

Quantitative structure-activity relationship models with receptor-dependent descriptors for predicting peroxisome proliferator-activated receptor activities of thiazolidinedione and oxazolidinedione derivatives

A quantitative structure–activity relationship study has been carried out, in which the relationship between the peroxisome proliferator-activated receptor a and the peroxisome proliferator activated receptor c agonistic activities of thiazo lidinedione and oxazolidinedione derivatives and quantitative descriptors, Vsite calculated in a receptor-dependent manner is modeled. These descriptors quantify the volume occupied by the optimized ligands in regions that are either com mon or specific to the superimposed binding sites of the targets under consideration. The quantita tive structure–activity relationship models were built by forward stepwise linear regression model ing for a training set of 27 compounds and vali dated for a test set of seven compounds, resulting in a squared correlation coefficient value of 0.90 for peroxisome proliferator-activated receptor a and of 0.89 for peroxisome proliferator-activated receptor c. The leave-one-out cross-validation and test set predictability squared correlation coeffi cient values for these models were 0.85 and 0.62 for peroxisome proliferator-activated receptor a and 0.89 and 0.50 for peroxisome proliferator-acti vated receptor c respectively. A dual peroxisome proliferator-activated receptor model has also been developed, and it indicates the structural features required for the design of ligands with dual peroxisome proliferator-activated receptor activity. These quantitative structure–activity relationship models show the importance of the descriptors here introduced in the prediction and interpretation of the compounds affinity and selectivity.info:eu-repo/semantics/publishedVersio

Structure based rational drug design of selective phosphodiesterase-4 ligands as anti-inflammatory molecules

Phosphodiesterase-4 enzyme (PDE4) has been gaining increasing attention for the last two decades as a pharmacotherapeutic target, as it is involved in the etiology of a variety of pathologies that comprise a majority of inflammation problems concerning respiratory pathway in major aspect. Intense efforts have been directed towards the development of effective and selective PDE4b inhibitors, but not much success has been reported till yet. This is because of the structural similarity between the two isoforms of PDE4, PDE4b (therapeutic effect) and PDE4d (side effect of emesis). Analogues of 1,2-dihydroxy-xanthen-9H-one were designed as selective ligands for PDE4b using the structure based drug design. The selectivity was determined by docking of xanthone analogues in PDE4b and PDE4d active sites respectively using GLIDE docking programme from Schrodinger Inc. ADME properties of the designed ligands were also predicted using QikProp from Schrodinger Inc. Interpretation of protein-ligand interactions and binding modes of xanthone analogues showed that these ligands are more selective for PDE4b than for PDE4d.info:eu-repo/semantics/publishedVersio

Design, Synthesis and Antidiabetic Activity of Novel Sulfamoyl Benzamide Derivatives as Glucokinase Activators

The present work has been planned to design, synthesize and evaluate the antidiabetic potential of a series of sulfamoyl benzamide derivatives as potential glucokinase (GK) activators. A new series of sulfamoyl benzamide derivatives was synthesized starting from 3-nitrobenzoic acid and characterized. In silico docking studies were performed to determine the binding interactions for the best fit conformations in the allosteric site of GK enzyme. Based on the results of in silico studies, the selected molecules were tested for their antidiabetic activity in animal studies (alloxan induced diabetic animal model). Compound 7 exhibited highest antidiabetic activity in animal studies. The results of in vivo antidiabetic activity studies were found to be in parallel to that of docking studies. These newly synthesized sulfamoyl benzamide derivatives thus can be treated as the initial hits for the development of novel, safe, effective and orally bioavailable GK activators as therapeutic agents for the treatment of type 2 diabetes

Therapeutic potential of catechin as an IKK-β inhibitor for the management of arthritis: In vitro and In vivo approach

Background: Rheumatoid arthritis (RA) is associated with increased levels of cytokines, for instance, nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) and interleukin-1 (IL-1), which exhibit potent pro-inflammatory effects and are contributing factors to disease progression. A range of cytokines, cell adhesion molecules, and enzymes that are implicated in the debilitating effects of RA are transcribed by nuclear factor kappa. Objectives: The purpose of this research was to characterize the efficacy of “catechin” as an IkappaB kinase-beta (IKK-β) inhibitor in collagen-induced arthritis (CIA) model in mice, as IKK-β is crucial in the transmission of signal-inducible NF-κβ activation. Methods: Arthritis was brought on in Bagg and Albino, but it is written BALB/c (BALB/c) male mice through subcutaneous immunization with bovine type II collagen on days 0 and 21. Catechin is given orally every day after the onset of the disease. Clinical evaluation of the prevalence and severity of the condition was done throughout the trial, and biochemical testing was done at the end (day 42). Results: In vitro findings of the study demonstrated catechin as a potent inhibitor of IKK-β with Half maximal Inhibitory Concentration (IC50) values of 2.90 μM and 4.358 μM in IKK-β and NF-κβ transactivation activity assay, respectively. Furthermore, catechin (dose range of 10–100 mg/kg, p.o.) was effective in reducing disease incidence and clinical signs in a dose-dependent manner, with an Effective Dose for 50% of the population (ED50) value of 79.579 mg/kg. The findings of this study demonstrate dose-dependent efficacy in terms of both disease severity (clinical scoring) and inflammatory markers (biochemical evaluation of the serum and joints). Conclusions: IKK inhibitors are a prospective target for the creation of new therapeutics for arthritis and other inflammatory diseases because it has been suggested that this enzyme is crucial in the pathophysiology of RA. The finding of this study suggests that “catechin” represents a novel inhibitor of IKK-β with promising anti-inflammatory activity

Targeting matrix metalloproteinases with novel diazepine substituted cinnamic acid derivatives: design, synthesis, in vitro and in silico studies

Abstract Lung cancer is the notable cause of cancer associated deaths worldwide. Recent studies revealed that the expression of matrix metalloproteinases (MMPs) is extremely high in lung tumors compared with non-malignant lung tissue. MMPs (-2 and -9) play an important part in tumor development and angiogenesis, which suggests that creating potent MMP-2 and -9 inhibitors, should be an important goal in lung cancer therapy. In the present study, an effort has been made to develop new anti-metastatic and anti-invasive agents, wherein a series of novel diazepine substituted cinnamic acid derivatives were designed, synthesized and assayed for their inhibitory activities on MMP-2 and MMP-9. These derivatives were prepared via microwave assisted reaction of tert-butyl (3-cinnamamidopropyl)carbamate derivatives mixed with 2,3-dibromopropanoic acid and potassium carbonate was added to obtain 4-(tert-butoxycarbonyl)-1-cinnamoyl-1,4-diazepane-2-carboxylic acid derivatives. The newly synthesized compounds were characterized by IR, NMR and mass spectroscopy. All the tested compounds showed good to excellent cytotoxic potential against A549 human lung cancer cells. The active compounds displaying good activity were further examined for the inhibitory activity against MMPs (-2 and -9). In addition, the structure and anticancer activity relationship were further supported by in silico docking studies of the active compounds against MMP-2 and MMP-9