High therapeutic potential of Spilanthes acmella

Spilanthes acmella, a well known antitoothache plant with high medicinal usages, has been recognized as an important medicinal plant and has an increasingly high demand worldwide. From its traditional uses in health care and food, extensive phytochemical studies have been reported. This review provides an overview and general description of the plant species, bioactive metabolites and important pharmacological activities including the preparation, purification and in vitro large-scale production. Structure-activity relationships of the bioactive compounds have been discussed. Considering data from the literature, it could be demonstrated that S. acmella possesses diverse bioactive properties and immense utilization in medicine, health care, cosmetics and as health supplements. As a health food, it is enriched with high therapeutic value with high potential for further development

Prediction of aromatase inhibitory activity using the efficient linear method (ELM)

Aromatase inhibition is an effective treatment strategy for breast cancer. Currently, several in silico methods have been developed for the prediction of aromatase inhibitors (AIs) using artificial neural network (ANN) or support vector machine (SVM). In spite of this, there are ample opportunities for further improvements by developing a simple and interpretable quantitative structure-activity relationship (QSAR) method. Herein, an efficient linear method (ELM) is proposed for constructing a highly predictive QSAR model containing a spontaneous feature importance estimator. Briefly, ELM is a linear-based model with optimal parameters derived from genetic algorithm. Results showed that the simple ELM method displayed robust performance with 10-fold cross-validation MCC values of 0.64 and 0.56 for steroidal and non-steroidal AIs, respectively. Comparative analyses with other machine learning methods (i.e. ANN, SVM and decision tree) were also performed. A thorough analysis of informative molecular descriptors for both steroidal and non-steroidal AIs provided insights into the mechanism of action of compounds. Our findings suggest that the shape and polarizability of compounds may govern the inhibitory activity of both steroidal and non-steroidal types whereas the terminal primary C(sp3) functional group and electronegativity may be required for non-steroidal AIs. The R code of the ELM method is available at http://dx.doi.org/10.6084/m9.figshare.1274030

Novel activities of 1-adamantylthiopyridines as antibacterials, antimalarials and anticancers

To discover new bioactive lead compounds for medicinal purposes, herein, 2(1-adamantylthio)pyridine and derivatives (1-10) were prepared and tested for antibacterial (agar dilution method against 27 strains of microorganisms), antimalarial (against Plasmodium falciparum) and anticancer (MOLT-3, HepG2, HuCCA-1 and A549) activities. Results showed that all the tested derivatives selectively exerted antigrowth activity against Streptococci at 15-30 µg/mL. 3-Substituted (R) thiopyridines; 3 (R = NAc2), 5 (R = OH) and 6 (R = Br) exhibited antibacterials, antimalarials and anticancers. Significantly, 6-(1-adamantylthio) nicotinonitrile (10) is a promising antibacterial which selectively displays antigrowth activity against Vibrio cholerae, Vibrio parahaemolyticus, Edwardsiella tarda and beta-hemolytic Streptococcus group A with minimum inhibitory concentration of 30 µg/mL. The findings reveal that these 1-adamantylthiopyridines represent a novel class of antibacterial, antimalarial and anticancer agents with potential medicinal values

Probing the origins of aromatase inhibitory activity of disubstituted coumarins via QSAR and molecular docking

This study investigated the quantitative structure-activity relationship (QSAR) of imidazole derivatives of 4,7-disubstituted coumarins as inhibitors of aromatase, a potential therapeutic protein target for the treatment of breast cancer. Herein, a series of 3,7- and 4,7-disubstituted coumarin derivatives (1-34) with R1 and R2 substituents bearing aromatase inhibitory activity were modeled as a function of molecular and quantum chemical descriptors derived from low-energy conformer geometrically optimized at B3LYP/6-31G(d) level of theory. Insights on origins of aromatase inhibitory activity was afforded by the computed set of 7 descriptors comprising of F10[N-O], Inflammat-50, Psychotic-80, H-047, BELe1, B10[C-O] and MAXDP. Such significant descriptors were used for QSAR model construction and results indicated that model 4 afforded the best statistical performance. Good predictive performance were achieved as verified from the internal (comprising the training and the leave-one-out cross-validation (LOO-CV) sets) and external sets affording the following statistical parameters: R2Tr = 0.9576 and RMSETr = 0.0958 for the training set; Q2CV = 0.9239 and RMSECV = 0.1304 for the LOO-CV set as well as Q2Ext = 0.7268 and RMSEExt = 0.2927 for the external set. Significant descriptors showed correlation with functional substituents, particularly, R1 in governing high potency as aromatase inhibitor. Molecular docking calculations suggest that key residues interacting with the coumarins were predominantly lipophilic or non-polar while a few were polar and positively-charged. Findings illuminated herein serve as the impetus that can be used to rationally guide the design of new aromatase inhibitors

Activities of thiotetrahydropyridines as antioxidant and antimicrobial agents

Tetrahydropyridines have been reported previously as important medicinal agents. The present study, thiotetrahydropyridines were prepared and tested for antioxidants (DPPH and SOD assays) and antimicrobials (agar dilution method). The results show that 1-acetyl-1,2,3,4- and 1,2,3,6-thiotetrahydropyridines 15a-b, 16, 17 and 18a are new antioxidants that scavenge superoxide and free radicals. Whereas the analogs 15a and 16 are novel antimicrobials. Significantly, 1-acetyl-2-(1-adamantylthio)-3,4-diacetoxy-1,2,3,4-tetrahydropyridine (15a) is the most potent compound that inhibits the growth of Streptococcus pyogenes and Moraxella catarrhalis with MIC of 32 µg/mL, of Corynebacterium diphtheriae NCTC 10356 and of Vibrio cholerae (MIC of 64 µg/mL). Remarkably, the analog 15a is the most potent antioxidant and antimicrobial agent. This finding reveals a new and unique group of 1-acetyl-1,2,3,4-thiotetrahydropyridines as interesting lead compound with potential to be further developed for medicinal applications

Effect of cranberry dietary supplements with different brands on human CYP3A4 enzyme

The use of dietary supplements has increased dramatically, making drug interactions with those supplements a major concern. Because dietary supplements are not subject to the same regulations as prescription drugs, we hypothesize that the content of their active ingredients may vary among manufacturers, potentially causing a large variation in therapeutic outcome. The current study aimed to test this hypothesis on commonly used cranberry dietary supple-ments. Activity of human CYP3A4 enzyme was used as a parameter to determine the effect of cranberry supplement from nine manufacturers. The content of a cranberry product, equivalent to one capsule, was extracted with methanol. Aliquots of the extract were tested for their ability to inhibit the metabolism of the human CYP3A4 substrate quinine, using an in vitro liver microsomal technique. Human liver microsomes and quinine were incubated with or without (i.e. as control) cranberry extract. Formation of quinine’s metabolite 3-hydroxyquinine, generated by the CYP3A4-mediated reaction was measured by a HPLC method. Of nine cranberry products tested, eight products had little or no effect but only one brand (Nature’s Herbs 600 mg) caused very strong inhibition (67.2 %) of CYP3A4. The reason for this inhibition is unknown. The effect of cranberry was varied and ranged from 4.4 % activation by Ride Aid 800 mg to 67.2% inhibition by Nature’s Herbs 600 mg. Lack of effect on human CYP3A4 activity suggests that use of cranberry dietary supplement is unlikely to cause signif-icant interactions with drugs metabolized by CYP3A4

A new sulfoxide analog of 1,2,3,6-tetrahydrophenylpyridine and antimicrobial activity

Bioactivities of thiotetrahydropyridines were previously described. Herein, a novel bioactive sulfoxide analog; N-acetyl-2-(1-adamantylsulfoxo)-3-acetoxy-4-phenyl-6-hydroxy-1,2,3,6-tetrahydropyridine (3) from the deoxydative substitution of 4-phenylpyridine 1-oxide is reported. Its structure was elucidated using spectral data including 2D-NMR, MS, IR and UV. The sulfoxide 3 exhibited antibacterial activity against Moraxella catarrhalis and Streptococcus pyogenes with minimum inhibitory concentration of 128 and 256 μg/mL, respectively

Aromatase inhibitory activity of 1,4-naphthoquinone derivatives and QSAR study

A series of 2-amino(chloro)-3-chloro-1,4-naphthoquinone derivatives (1-11) were investigated for their aromatase inhibitory activities. 1,4-Naphthoquinones 1 and 4 were found to be the most potent compounds affording IC50 values 5.2 times lower than the reference drug, ketoconazole. A quantitative structure-activity relationship (QSAR) model provided good predictive performance (R2 CV = 0.9783 and RMSECV = 0.0748) and indicated mass (Mor04m and H8m), electronegativity (Mor08e), van der Waals volume (G1v) and structural information content index (SIC2) descriptors as key descriptors governing the activity. To investigate the effects of structural modifications on aromatase inhibitory activity, the model was employed to predict the activities of an additional set of 39 structurally modified compounds constructed in silico. The prediction suggested that the 2,3-disubstitution of 1,4-naphthoquinone ring with halogen atoms (i.e., Br, I and F) is the most effective modification for potent activity (1a, 1b and 1c). Importantly, compound 1b was predicted to be more potent than its parent compound 1 (11.90-fold) and the reference drug, letrozole (1.03-fold). The study suggests the 1,4-naphthoquinone derivatives as promising compounds to be further developed as a novel class of aromatase inhibitors

Classification of P-glycoprotein-interacting compounds using machine learning methods

P-glycoprotein (Pgp) is a drug transporter that plays important roles in multidrug resistance and drug pharmacokinetics. The inhibition of Pgp has become a notable strategy for combating multidrug-resistant cancers and improving therapeutic outcomes. However, the polyspecific nature of Pgp, together with inconsistent results in experimental assays, renders the determination of endpoints for Pgp-interacting compounds a great challenge. In this study, the classification of a large set of 2,477 Pgp-interacting compounds (i.e., 1341 inhibitors, 913 noninhibitors, 197 substrates and 26 non-substrates) was performed using several machine learning methods (i.e., decision tree induction, artificial neural network modelling and support vector machine) as a function of their physicochemical properties. The models provided good predictive performance, producing MCC values in the range of 0.739-1 for internal cross-validation and 0.665-1 for external validation. The study provided simple and interpretable models for important properties that influence the activity of Pgp-interacting compounds, which are potentially beneficial for screening and rational design of Pgp inhibitors that are of clinical importance