Apilak Worachartcheewan

Bioactive metabolites from Spilanthes acmella Murr.

Spilanthes acmella Murr. (Compositae) has been used as a traditional medicine for toothache, rheumatism and fever. Its extracts had been shown to exhibit vasorelaxant and antioxidant activities. Herein, its antimicrobial, antioxidant and cytotoxic activities were evaluated. Agar dilution method assays against 27 strains of microorganisms were performed. Results showed that fractions from the chloroform and methanol extracts inhibited the growth of many tested organisms, e.g. Corynebacterium diphtheriae NCTC 10356 with minimum inhibitory concentration (MIC) of 64-256 μg/mL and Bacillus subtilis ATCC 6633 with MIC of 128-256 μg/mL. The tested fractions all exhibited antioxidant properties in both DPPH and SOD assays. Potent radical scavenging activity was observed in the DPPH assay. No cytotoxic effects of the extracts against KB and HuCCA-1 cell lines were evident. Bioassay-guided isolation resulted in a diverse group of bioactive compounds such as phenolics [vanillic acid (2), trans-ferulic acid (5) and trans-isoferulic acid (6)], coumarin (scopoletin, 4) and triterpenoids like 3-acetylaleuritolic acid (1), β-sitostenone (3), stigmasterol and stigmasteryl-3-O-β-D-glucopyranosides, in addition to a mixture of stigmasteryl-and β-sitosteryl-3-O-β-D-glucopyranosides. The compounds 1–6 represent bioactive metabolites of S. acmella Murr. that were never previously reported. Our findings demonstrate for the first time the potential benefits of this medicinal plant as a rich source of high therapeutic value compounds for medicines, cosmetics, supplements and as a health food.

Antimicrobial and Antioxidative Activities of Bioactive Constituents from Hydnophytum formicarum Jack.

Hydnophytum formicarum Jack. (Rubiaceae) is a medicinal plant whose tubers possesses cardiovascular, anti-inflammatory and antiparasitic effects and have been used for the treatment of hepatitis, rheumatism and diarrhea. Herein we report the isolation of its active constituents and the testing of their antimicrobial activity against 27 strains of microorganisms using an agar dilution method and of their antioxidative activity using the DPPH and SOD assays. The results show that the crude hexane, dichloromethane, ethyl acetate and methanol extracts exert such activities. Particularly, the crude ethyl acetate extract exhibits antigrowth activity against many Gram-positive and Gram-negative bacteria with MIC 256 μg/mL. Shewanella putrefaciens ATCC 8671 is completely inhibited at a lower MIC (128 μg/mL). Interestingly, Corynebacterium diphtheriae NCTC 10356 is inhibited by all the tested extracts. Significantly, the ethyl acetate extract is also the most potent antioxidant, showing 83.31% radical scavenging activity with IC50 8.40 μg/mL in the DPPH assay. The other extracts display weak to moderate antioxidative activities, ranging from 28.60-56.80% radical scavenging. The SOD assay shows that methanol extract exhibits the highest activity (74.19% inhibition of superoxide radical). The dichloromethane and ethyl acetate extracts display comparable SOD activity. The promising bioactivities of the crude ethyl acetate extract guided the first isolation of bioactive flavonoid and phenolic compounds: isoliquiritigenin (2), protocatechualdehyde (3), butin (4) and butein (5) from this species. Their structures have been fully established by 1D and 2D NMR. In addition, stigmasterol was isolated from the crude hexane and dichloromethane extracts. The antimicrobial and cytotoxic activities of compounds 3-5 were evaluated. The tested compounds were inactive against HuCCA-1 and KB cell lines, showing ED50> 10 μg/mL. Protocatechualdehyde (3) completely inhibits the growth of Plesiomonas shigelloides with MIC ≤60 μg/mL. As a result, we propose that Hydnophytum formicarum Jack. can serve as a new source enriched with potent antioxidative and antimicrobial agents.

Modeling the activity of furin inhibitors using artificial neural network.

Quantitative structure-activity relationship (QSAR) models were constructed for predicting the inhibition of furin-dependent processing of anthrax protective antigen of substituted guanidinylated aryl 2,5-dideoxystreptamines. Molecular descriptors calculated by E-Dragon and RECON were subjected to variable reduction using the Unsupervised Forward Selection (UFS) algorithm. The variables were then used as input for QSAR model generation using partial least squares and back-propagation neural network. Prediction was performed via a two-step approach: (i) perform classification to determine whether the molecule is active or inactive, (ii) develop a QSAR regression model of active molecules. Both classification and regression models yielded good results with RECON providing higher accuracy than that of E-DRAGON descriptors. The performance of the regression model using E-Dragon and RECON descriptors provided a correlation coefficient of 0.807 and 0.923 and root mean square error of 0.666 and 0.304, respectively. Interestingly, it was observed that appropriate representations of the protonation states of the molecules were crucial for good prediction performance, which coincides with the fact that the inhibitors interact with furin via electrostatic forces. The results provide good prospect of using the proposed QSAR models for the rational design of novel therapeutic furin inhibitors toward anthrax and furin-dependent diseases.

Synthesis and structure–activity relationship of 2-thiopyrimidine-4-one analogs as antimicrobial and anticancer agents

Considering that some thiopyrimidines were previously reported as potential therapeutics, the present study achieved novel analogs of bioactive 2-substituted thiopyrimidines-4-(3H)-ones via base catalyzed alkylation reaction of 2-thiouracil using alkyl and aralkyl bromides. The title compounds were 2-(1-butylthio)pyrimidine-4(3H)-one (5a), 2-(2-butylthio)pyrimidine-4(3H)-one (5b), 2-(cyclohexylmethylthio)pyrimidine-4(3H)-one (5c), 2-(benzylthio)pyrimidine-4(3H)-one (5d) and 2-(1-adamantylthio)pyrimidine-4(3H)-one (5e). Bioactivity tests revealed that thiopyrimidines 5a, 5c, 5d and 5e exhibited antimicrobial activity. The thiopyrimidine-4-one (5c) showed complete inhibition against Streptococcus pyogenes and Branhamella catarrhalis as well as antifungal action against Candida albicans. Significantly, the 1-adamantylthiopyrimidine (5e) was shown to be the most potent cytotoxic compound against multidrug-resistant small cell lung cancer (H69AR). Their structure-activity relationships were discussed.

Identification of metabolic syndrome using decision tree analysis

This study employs decision tree as a decision support system for rapid and automated identification of individuals with metabolic syndrome (MS) among a Thai population. Results demonstrated strong predictivity of the decision tree in classification of individuals with and without MS, displaying an overall accuracy in excess of 99%.

Elucidating the structure-activity relationships of the vasorelaxation and antioxidation properties of thionicotinic acid derivatives.

Nicotinic acid, known as vitamin B3, is an effective lipid lowering drug and intense cutaneous vasodilator. This study reports the effect of 2-(1-adamantylthio)nicotinic acid (6) and its amide 7 and nitrile analog 8 on phenylephrine-induced contraction of rat thoracic aorta as well as antioxidative activity. It was found that the tested thionicotinic acid analogs 6-8 exerted maximal vasorelaxation in a dose-dependent manner, but their effects were less than acetylcholine (ACh)-induced nitric oxide (NO) vasorelaxation. The vasorelaxations were reduced, apparently, in both NG-nitro-L-arginine methyl ester (L-NAME) and indomethacin (INDO). Synergistic effects were observed in the presence of L-NAME plus INDO, leading to loss of vasorelaxation of both the ACh and the tested nicotinic acids. Complete loss of the vasorelaxation was noted under removal of endothelial cells. This infers that the vasorelaxations are mediated partially by endothelium-induced NO and prostacyclin. The thionicotinic acid analogs all exhibited antioxidant properties in both 2,2-diphenyl-1-picrylhydrazyl (DPPH) and superoxide dismutase (SOD) assays. Significantly, the thionicotinic acid 6 is the most potent vasorelaxant with ED50 of 21.3 nM and is the most potent antioxidant (as discerned from DPPH assay). Molecular modeling was also used to provide mechanistic insights into the vasorelaxant and antioxidative activities. The findings reveal that the thionicotinic acid analogs are a novel class of vasorelaxant and antioxidant compounds which have potential to be further developed as promising therapeutics.

A Unified Proteochemometric Model for Prediction of Inhibition of Cytochrome P450 Isoforms

A unified proteochemometric (PCM) model for the prediction of the ability of drug-like chemicals to inhibit five major drug metabolizing CYP isoforms (i.e. CYP1A2, CYP2C9, CYP2C19, CYP2D6 and CYP3A4) was created and made publicly available under the Bioclipse Decision Support open source system at www.cyp450model.org. In regards to the proteochemometric modeling we represented the chemical compounds by molecular signature descriptors and the CYP-isoforms by alignment-independent description of composition and transition of amino acid properties of their protein primary sequences. The entire training dataset contained 63 391 interactions and the best PCM model was obtained using signature descriptors of height 1, 2 and 3 and inducing the model with a support vector machine. The model showed excellent predictive ability with internal AUC = 0.923 and an external AUC = 0.940, as evaluated on a large external dataset. The advantage of PCM models is their extensibility making it possible to extend our model for new CYP isoforms and polymorphic CYP forms. A key benefit of PCM is that all proteins are confined in one single model, which makes it generally more stable and predictive as compared with single target models. The inclusion of the model in Bioclipse Decision Support makes it possible to make virtual instantaneous predictions (∼100 ms per prediction) while interactively drawing or modifying chemical structures in the Bioclipse chemical structure editor.

Antioxidant, cytotoxicity, and QSAR study of 1-adamantylthio derivatives of 3-picoline and phenylpyridines

A series of isomeric α- and β-(1-adamantylthio)pyridines were previously documented to possess interesting antimicrobial and antimalarial activities. In this study, the antioxidant and cytotoxic potentials of 1-adamantylthio-3-methyl and 2-,3-,4-phenylpyridines (1–10) were investigated. The tested compounds were shown to exhibit interesting superoxide (SOD)- and free radical (DPPH)-scavenging activities as well as cytotoxic activities. Particularly, β-(1-adamantylthio)-4-phenylpyridine (8) was shown to be the most potent antioxidant and cytotoxic compound. QSAR studies revealed that dipole moment (μ) and electrophilic index (ωi) were the most important descriptors accounting for the observed SOD activities. Compounds with high μ and ωi values were observed to display high SOD activity. Inversely, compounds with the lowest atomic polarizability (MATS4p) exhibited the highest DPPH activity. Other quantum chemical descriptors such as atomic masses (GATS4m), ωi, and LUMO energy were also well correlated with cytotoxicity. The findings demonstrated that thiopyridine 8 is a potential lead compound that should be further investigated in drug discovery efforts. The QSAR results offer good prospect for the rational design of novel compounds with robust bioactivities.

QSAR Study of H1N1 Neuraminidase Inhibitors from Influenza A Virus

Neuraminidase (NA) is a glycoprotein found on the surface of influenza A virus that is used for releasing new progeny of virions by cleaving the terminal sialic acid residue from the surface of infected cells. Therefore, NA is an in- teresting potential target to design promising NA inhibitiors to serve as antiviral agents for preventing viral propagation. In this study, a data set of 61 H1N1 neuraminidase inhibitors of influenza A virus was employed in the construction of quantitative structure-activity relationship (QSAR) model using the CORrelation And Logic (CORAL) software available at http://www.insilico.eu/coral. The chemical structure of compounds in the SMILES format was used as input to CORAL in discerning the correlation between an endpoint (i.e. neuraminidase inhibitory activity) and their corresponding molecu- lar descriptors. Three random splits of the data into sub-training, calibration and testing sets were carried out. The optimal threshold and number of epoch to use in building the QSAR models were derived from the CORAL software. Results in- dicated that the QSAR models displayed good prediction performance as deduced from statistical parameters affording r 2 = 0.7783-0.9166, 0.7609-0.8336 and 0.8384-0.9069 and q 2 = 0.7453-0.8924, and 0.7311-0.7939 and 0.8051-0.8843 for sub-training, calibration and test set, respectively. Furthermore, F value and standard error of estimation provided good statistical results for the predictive performance of QSAR models. Interpretations of the derived structure-activity rela- tionship provided pertinent knowledge on the origins of good and poor neuraminidase inhibitory activity. Therefore, the QSAR model holds great potential for the rational design of novel neuraminidase inhibitors.

Exploring the chemical space of aromatase inhibitors

Aromatase, a rate-limiting enzyme catalyzing the conversion of androgen to estrogen, is overexpressed in human breast cancer tissue. Aromatase inhibitors (AIs) have been used for the treatment of estrogen-dependent breast cancer in post-menopausal women by blocking the biosynthesis of estrogen. The undesirable side effects in current AIs have called for continued pursuit for novel candidates with aromatase inhibitory properties. This study explores the chemical space of all known AIs as a function of their physicochemical properties by means of univariate (i.e., statistical and histogram analysis) and multivariate (i.e., decision tree and principal component analysis) approaches in order to understand the origins of aromatase inhibitory activity. Such a non-redundant set of AIs spans a total of 973 compounds encompassing both steroidal and non-steroidal inhibitors. Substructure analysis of the molecular fragments provided pertinent information on the structural features important for ligands providing high and low aromatase inhibition. Analyses were performed on data sets stratified according to their structural scaffolds (i.e., steroids and non-steroids) and bioactivities (i.e., actives and inactives). These analyses have uncover a set of rules characteristic to active and inactive AIs as well as revealing the constituents giving rise to potent aromatase inhibition.