Veda Prachayasittikul

8-Hydroxyquinolines: a review of their metal chelating properties and medicinal applications

Metal ions play an important role in biological processes and in metal homeostasis. Metal imbalance is the leading cause for many neurodegenerative diseases such as Alzheimer’s disease, Parkinson’s disease, and multiple sclerosis. 8-Hydroxyquinoline (8HQ) is a small planar molecule with a lipophilic effect and a metal chelating ability. As a result, 8HQ and its derivatives hold medicinal properties such as antineurodegenerative, anticancer, antioxidant, antimicrobial, anti-inflammatory, and antidiabetic activities. Herein, diverse bioactivities of 8HQ and newly synthesized 8HQ-based compounds are discussed together with their mechanisms of actions and structure–activity relationships.

Synthesis and molecular docking of 1,2,3-triazole-based sulfonamides as aromatase inhibitors.

A series of 1,4-disubstituted-1,2,3-triazoles (13-35) containing sulfonamide moiety were synthesized and evaluated for their aromatase inhibitory effects. Most triazoles with open-chain sulfonamide showed significant aromatase inhibitory activity (IC50=1.3-9.4μM). Interestingly, the meta analog of triazole-benzene-sulfonamide (34) bearing 6,7-dimethoxy substituents on the isoquinoline ring displayed the most potent aromatase inhibitory activity (IC50=0.2μM) without affecting normal cell. Molecular docking of these triazoles against aromatase revealed that the compounds could snugly occupy the active site of the enzyme through hydrophobic, π-π stacking, and hydrogen bonding interactions. The potent compound 34 was able to form hydrogen bonds with Met374 and Ser478 which were suggested to be the essential residues for the promising inhibition. The study provides compound 34 as a potential lead molecule of anti-aromatase agent for further development.

Novel 1,4-naphthoquinone-based sulfonamides: Synthesis, QSAR, anticancer and antimalarial studies

A novel series of 1,4-naphthoquinones (33-44) tethered by open and closed chain sulfonamide moieties were designed, synthesized and evaluated for their cytotoxic and antimalarial activities. All quinone-sulfonamide derivatives displayed a broad spectrum of cytotoxic activities against all of the tested cancer cell lines including HuCCA-1, HepG2, A549 and MOLT-3. Most quinones (33-36 and 38-43) exerted higher anticancer activity against HepG2 cell than that of the etoposide. The open chain analogs 36 and 42 were shown to be the most potent compounds. Notably, the restricted sulfonamide analog 38 with 6,7-dimethoxy groups exhibited the most potent antimalarial activity (IC₅₀ = 2.8 μM). Quantitative structure-activity relationships (QSAR) study was performed to reveal important chemical features governing the biological activities. Five constructed QSAR models provided acceptable predictive performance (Rcv 0.5647-0.9317 and RMSEcv 0.1231-0.2825). Four additional sets of structurally modified compounds were generated in silico (34a-34d, 36a-36k, 40a-40d and 42a-42k) in which their activities were predicted using the constructed QSAR models. A comprehensive discussion of the structure-activity relationships was made and a set of promising compounds (i.e., 33, 36, 38, 42, 36d, 36f, 42e, 42g and 42f) was suggested for further development as anticancer and antimalarial agents.

Synthesis, anticancer activity and QSAR study of 1,4-naphthoquinone derivatives

A series of 2-substituted amino-3-chloro-1,4-naphthoquinone derivatives (3-12) were synthesized as anticancer agents and tested against four cancer cell lines including HepG2, HuCCA-1, A549 and MOLT-3. The most potent cytotoxic activity against the HepG2, HuCCA-1 and A549 cell lines was found to be m-acetylphenylamino-1,4-naphthoquinone (8) affording IC50 values of 4.758, 2.364 and 12.279 μM, respectively. On the other hand, p-acetylphenylamino-1,4-naphthoquinone (9) exhibited the most potent cytotoxic activity against the MOLT-3 cell line with an IC50 of 2.118 μM. Quantitative structure-activity relationship (QSAR) investigations provided good predictive performance as observed from cross-validated R of 0.9177-0.9753 and RMSE of 0.0614-0.1881. The effects of substituents at the 2-amino position on the naphthoquinone core structure and its corresponding influence on the cytotoxic activity were investigated by virtually constructing additional 1,4-naphthoquinone compounds (13-36) for which cytotoxic activities were predicted using equations obtained from the previously constructed QSAR models. Interpretation of informative descriptors from QSAR models revealed pertinent knowledge on physicochemical properties governing the cytotoxic activities of tested cancer cell lines. It is anticipated that the QSAR models developed herein could provide guidelines for further development of novel and potent anticancer agents.

Discovery of novel 1,2,3-triazole derivatives as anticancer agents using QSAR and in silico structural modification

AbstractConsiderable attention has been given on the search for novel anticancer drugs with respect to the disease sequelae on human health and well-being. Triazole is considered to be an attractive scaffold possessing diverse biological activities. Structural modification on the privileged structures is noted as an effective strategy towards successful design and development of novel drugs. The quantitative structure–activity relationships (QSAR) is well-known as a powerful computational tool to facilitate the discovery of potential compounds. In this study, a series of thirty-two 1,2,3-triazole derivatives (1–32) together with their experimentally measured cytotoxic activities against four cancer cell lines i.e., HuCCA-1, HepG2, A549 and MOLT-3 were used for QSAR analysis. Four QSAR models were successfully constructed with acceptable predictive performance affording RCV ranging from 0.5958 to 0.8957 and RMSECV ranging from 0.2070 to 0.4526. An additional set of 64 structurally modified triazole compounds (1A–1R, 2A–2R, 7A–7R and 8A–8R) were constructed in silico and their predicted cytotoxic activities were obtained using the constructed QSAR models. The study suggested crucial moieties and certain properties essential for potent anticancer activity and highlighted a series of promising compounds (21, 28, 32, 1P, 8G, 8N and 8Q) for further development as novel triazole-based anticancer agents.

Nicotinic acid and derivatives as multifunctional pharmacophores for medical applications

Cardiovascular disease is one of the major health problems worldwide. It is a vascular condition known as an atherosclerosis referring to the accumulation of immune cells and lipids in vascular walls that finally obstructs blood flow to trigger heart attack. To prevent and treat the atherosclerosis is to control blood lipid level. Diverse classes of lipid-lowering drug have been used. Nicotinic acid (niacin or vitamin B3) is the first drug that has been used for over five decades. Nicotinic acid and its derivatives play important role as multifunctional pharmacophores exerting a variety of biological activities. This review focuses on the redox and non-redox reactions as well as antioxidant activity of nicotinic acid derivatives and drugs acting on nicotinic acid receptor including therapeutic and cosmetic applications. Structure–activity relationship of nicotinic acid derivatives has been discussed. This article could provide insight into the rational design and development of novel bioactive compounds with therapeutic potential.Graphical Abstract

Navigating the chemical space of dipeptidyl peptidase-4 inhibitors

This study represents the first large-scale study on the chemical space of inhibitors of dipeptidyl peptidase-4 (DPP4), which is a potential therapeutic protein target for the treatment of diabetes mellitus. Herein, a large set of 2,937 compounds evaluated for their ability to inhibit DPP4 was compiled from the literature. Molecular descriptors were generated from the geometrically optimized low-energy conformers of these compounds at the semiempirical AM1 level. The origins of DPP4 inhibitory activity were elucidated from computed molecular descriptors that accounted for the unique physicochemical properties inherently present in the active and inactive sets of compounds as defined by their respective half maximal inhibitory concentration values of less than 1 μM and greater than 10 μM, respectively. Decision tree analysis revealed the importance of molecular weight, total energy of a molecule, topological polar surface area, lowest unoccupied molecular orbital, and number of hydrogen-bond donors, which correspond to molecular size, energy, surface polarity, electron acceptors, and hydrogen bond donors, respectively. The prediction model was subjected to rigorous independent testing via three external sets. Scaffold and chemical fragment analysis was also performed on these active and inactive sets of compounds to shed light on the distinguishing features of the functional moieties. Docking of representative active DPP4 inhibitors was also performed to unravel key interacting residues. The results of this study are anticipated to be useful in guiding the rational design of novel and robust DPP4 inhibitors for the treatment of diabetes.

Roles of Pyridine and Pyrimidine Derivatives as Privileged Scaffolds in Anticancer Agents.

BACKGROUND Cancer has been considered to be a global health concern due to the impact of disease on the quality of life. The continual increase of cancer cases as well as the resistance of cancer cells to the existing drugs have driven the search for novel anticancer drugs with better potency and selectivity, improved pharmacokinetic profiles, and minimum toxicities. Pyridine and pyrimidine are presented in natural products and genetic materials. These pyridine/pyrimidine core structures have been noted for their roles in many biological processes as well as in cancer pathogenesis, which make such compounds become attractive scaffolds for discovery of novel drugs. RESULTS & CONCLUSION In the recent years, pyridine- and pyrimidine-based anticancer drugs have been developed based on structural modification of these core structures (i.e., substitution with moieties and rings, conjugation with other compounds, and coordination with metal ions). Detailed discussion is provided in this review to highlight the potential of these small molecules as privileged scaffolds with attractive properties and biological activities for the search of novel anticancer agents.

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.

Large-scale classification of P-glycoprotein inhibitors using SMILES-based descriptors

Abstract P-glycoprotein (Pgp) inhibition has been considered as an effective strategy towards combating multidrug-resistant cancers. Owing to the substrate promiscuity of Pgp, the classification of its interacting ligands is not an easy task and is an ongoing issue of debate. Chemical structures can be represented by the simplified molecular input line entry system (SMILES) in the form of linear string of symbols. In this study, the SMILES notations of 2254 Pgp inhibitors including 1341 active, and 913 inactive compounds were used for the construction of a SMILE-based classification model using CORrelation And Logic (CORAL) software. The model provided an acceptable predictive performance as observed from statistical parameters consisting of accuracy, sensitivity and specificity that afforded values greater than 70% and MCC value greater than 0.6 for training, calibration and validation sets. In addition, the CORAL method highlighted chemical features that may contribute to increased and decreased Pgp inhibitory activities. This study highlights the potential of CORAL software for rapid screening of prospective compounds from a large chemical space and provides information that could aid in the design and development of potential Pgp inhibitors.