Effects of barakol from Cassia siamea on neuroblastoma SH-SY5Y cell line: A potential combined therapy with doxorubicin

Management of neuroblastoma is challenging because of poor response to drugs, chemotherapy resistance, high relapse, and treatment failures. Doxorubicin is a potent anticancer drug commonly used for neuroblastoma treatment. However, doxorubicin induces considerable toxicities, particularly those caused by oxidative-related damage. To minimize drug-induced adverse effects, the combined use of anticancer drugs with natural-derived compounds possessing antioxidant properties has become an interesting treatment strategy. Barakol is a major compound found in Cassia siamea, an edible plant with antioxidant and anticancer properties. Therefore, barakol could potentially be used in combination with doxorubicin to synergize the anticancer effect, while minimizing the oxidative-related toxicities. Herein, the potential of barakol (0.0043-43.0 μM) to synergize the anticancer effect of low-dose doxorubicin (0.5 and 1.0 μM) was investigated. Results indicated that barakol could enhance the cytotoxic effect of low-dose doxorubicin by affecting the cell viability of the treated cells. Furthermore, the co-treatment with barakol and low-dose doxorubicin decreased the levels of intracellular ROS when compared with the control. Moreover, the antimetastatic effect of the barakol itself was studied through its ability to inhibit metalloproteinase-3 (MMP-3) activity and prevent cell migration. Results revealed that the barakol inhibited MMP-3 activity and prevented cell migration in time- and dose-dependent manners. Additionally, barakol was a non-cytotoxic agent against the normal tested cell line (MRC-5), which suggested its selectivity and safety. Taken together, barakol could be a promising compound to be further developed for combination treatment with low-dose doxorubicin to improve therapeutic effectiveness but decrease drug-induced toxicities. The inhibitory effects of barakol on MMP-3 activity and cancer cell migration also supported its potential to be developed as an antimetastatic agent.

Promising 8-Aminoquinoline-Based Metal Complexes in the Modulation of SIRT1/3-FOXO3a Axis against Oxidative Damage-Induced Preclinical Neurons

The discovery of novel bioactive molecules as potential multifunctional neuroprotective agents has clinically drawn continual interest due to devastating oxidative damage in the pathogenesis and progression of neurodegenerative diseases. Synthetic 8-aminoquinoline antimalarial drug is an attractive pharmacophore in drug development and chemical modification owing to its wide range of biological activities, yet the underlying molecular mechanisms are not fully elucidated in preclinical models for oxidative damage. Herein, the neuroprotective effects of two 8-aminoquinoline-uracil copper complexes were investigated on the hydrogen peroxide-induced human neuroblastoma SH-SY5Y cells. Both metal complexes markedly restored cell survival, alleviated apoptotic cascades, maintained antioxidant defense, and prevented mitochondrial function by upregulating the sirtuin 1 (SIRT1)/3-FOXO3a signaling pathway. Intriguingly, in silico molecular docking and pharmacokinetic prediction suggested that these synthetic compounds acted as SIRT1 activators with potential drug-like properties, wherein the uracil ligands (5-iodoracil and 5-nitrouracil) were essential for effective binding interactions with the target protein SIRT1. Taken together, the synthetic 8-aminoquinoline-based metal complexes are promising brain-targeting drugs for attenuating neurodegenerative diseases.

Aminochalcones Attenuate Neuronal Cell Death under Oxidative Damage via Sirtuin 1 Activity

Encouraged by the lack of effective treatments and the dramatic growth in the global prevalence of neurodegenerative diseases along with various pharmacological properties of chalcone pharmacophores, this study focused on the development of aminochalcone-based compounds, organic molecules characterized by a chalcone backbone (consisting of two aromatic rings connected by a three-carbon α,β-unsaturated carbonyl system) with an amino group attached to one of the aromatic rings, as potential neuroprotective agents. Thus, the aminochalcone-based compounds in this study were designed by bearing a -OCH3 moiety at different positions on the ring and synthesized by the Claisen-Schmidt condensation. The compounds exhibited strong neuroprotective effects against hydrogen peroxide-induced neuronal death in the human neuroblastoma (SH-SY5Y) cell line (i.e., by improving cell survival, reducing reactive oxygen species production, maintaining mitochondrial function, and preventing cell membrane damage). The aminochalcone-based compounds showed mild toxicity toward a normal embryonic lung cell line (MRC-5) and a human neuroblastoma cell line, and were predicted to have preferable pharmacokinetic profiles with potential for oral administration. Molecular docking simulation indicated that the studied aminochalcones may act as competitive activators of the well-known protective protein, SIRT1, and provided beneficial knowledge regarding the essential key chemical moieties and interacting amino acid residues. Collectively, this work provides a series of four promising candidate agents that could be developed for neuroprotection.

Discovery of Novel Naphthoquinone-Chalcone Hybrids as Potent FGFR1 Tyrosine Kinase Inhibitors: Synthesis, Biological Evaluation, and Molecular Modeling

This work presents a flexible synthesis of 10 novel naphthoquinone-chalcone derivatives (1-10) by nucleophilic substitution of readily accessible aminochalcones and 2,3-dichloro-1,4-naphthoquinone. All compounds displayed broad-spectrum cytotoxic activities against all the tested cancer cell lines (i.e., HuCCA-1, HepG2, A549, MOLT-3, T47D, and MDA-MB-231) with IC50 values in the range of 0.81-62.06 μM, especially the four most potent compounds 1, 3, 8, and 9. The in vitro investigation on the fibroblast growth factor receptor 1 (FGFR1) inhibitory effect indicated that eight derivatives (1-2, 4-5, and 7-10) were active FGFR1 inhibitors (IC50 = 0.33-3.13 nM) with more potency than that of the known FGFR1 inhibitor, AZD4547 (IC50 = 12.17 nM). Promisingly, compounds 5 (IC50 = 0.33 ± 0.01 nM), 9 (IC50 = 0.50 ± 0.04 nM), and 7 (IC50 = 0.85 ± 0.08 nM) were the three most potent FGFR1 inhibitors. Molecular docking, molecular dynamics simulations, and MM/GBSA-based free energy calculation revealed that the key amino acid residues involved in the binding of the compounds 5, 7, and 9 and the target FGFR1 protein were similar with those of the AZD4547 (i.e., Val492, Lys514, Ile545, Val561, Ala640, and Asp641). These findings revealed that the newly synthesized naphthoquinone-chalcone scaffold is a promising structural feature for an efficient inhibition of FGFR1.

Neuroprotective Properties of Bis-Sulfonamide Derivatives Against 6-OHDA-Induced Parkinson's Model via Sirtuin 1 Activity and in silico Pharmacokinetic Properties

Parkinson's disease (PD) is considered one of the health problems in the aging society. Due to the limitations of currently available drugs in preventing disease progression, the discovery of novel neuroprotective agents has been challenged. Sulfonamide and its derivatives were reported for several biological activities. Herein, a series of 17 bis-sulfonamide derivatives were initially tested for their neuroprotective potential and cytotoxicity against the 6-hydroxydopamine (6-OHDA)-induced neuronal death in SH-SY5Y cells. Subsequently, six compounds (i.e., 2, 4, 11, 14, 15, and 17) were selected for investigations on underlying mechanisms. The data demonstrated that the pretreatment of selected compounds (5 μM) can significantly restore the level of cell viability, protect against mitochondrial membrane dysfunction, decrease the activity of lactate dehydrogenase (LDH), decrease the intracellular oxidative stress, and enhance the activity of NAD-dependent deacetylase sirtuin-1 (SIRT1). Molecular docking was also performed to support that these compounds could act as SIRT1 activators. In addition, in silico pharmacokinetic and toxicity profile prediction was also conducted for guiding the potential development. Thus, the six neuroprotective bis-sulfonamides were highlighted as potential agents to be further developed for PD management.

Discovery of Anilino-1,4-naphthoquinones as Potent EGFR Tyrosine Kinase Inhibitors: Synthesis, Biological Evaluation, and Comprehensive Molecular Modeling

Epidermal growth factor receptor (EGFR) has been recognized as one of the attractive targets for anticancer drug development. Herein, a set of anilino-1,4-naphthoquinone derivatives (3-18) was synthesized and investigated for their anticancer and EGFR inhibitory potentials. Among all tested compounds, three derivatives (3, 8, and 10) were selected for studying EGFR inhibitory activity (in vitro and in silico) due to their most potent cytotoxic activities against six tested cancer cell lines (i.e., HuCCA-1, HepG2, A549, MOLT-3, MDA-MB-231, and T47D; IC50 values = 1.75-27.91 μM), high selectivity index (>20), and good predicted drug-like properties. The experimental results showed that these three promising compounds are potent EGFR inhibitors with nanomolar IC50 values (3.96-18.64 nM). Interestingly, the most potent compound 3 bearing 4-methyl substituent on the phenyl ring displayed 4-fold higher potency than the known EGFR inhibitor, erlotinib. Molecular docking, molecular dynamics simulation, and MM/GBSA-based free energy calculation revealed that van der Waals force played a major role in the accommodations of compound 3 within the ATP-binding pocket of EGFR. Additionally, the 4-CH3 moiety of the compound was noted to be a key chemical feature contributing to the highly potent EGFR inhibitory activity via its formations of alkyl interactions with A743, K745, M766, and L788 residues as well as additional interactions with M766 and T790.

Impact of a Holistic Health Intervention on the Well-Being of Elderly Thais

OBJECTIVE: Mental stress is a major risk factor of metabolic diseases and impairs quality of life in the elderly. The goal of this study was to investigate whether a mindfulness-based intervention can improve health parameters and reduce stress-related hormones in elderly Thais. METHODS: A total of 192 participants were recruited from urban (n = 96) and rural areas (n = 96) in central region of Thailand. Creative visual art relaxation and meditative movement exemplified by Dao De Xin Xi exercise were introduced as monthly workshops and individual participants were encouraged to practice regularly for three months. General health status, levels of blood pressure (BP), fasting blood sugar (FBS), cortisol and dehydroepiandrosteone (DHEA) were evaluated before and after completing the intervention. RESULTS: This mindfulness-based intervention was effective as assessed by several biological health parameters. However, the degree of effectiveness differed between participants in urban and rural groups. In urban group, BPs were significantly reduced in hypertension and pre-hypertension subgroups of participants, and levels of DHEA in low DHEA participants were significantly increased after the intervention. In contrast, FBS levels in diabetic and pre-diabetic participants in the rural group, but not in the urban group, were significantly decreased after the intervention. We found a trend toward improvement of cortisol levels in both groups. However, the levels of glycated hemoglobin in either group remained unchanged. CONCLUSION: This mindfulness-based intervention to elderly people improved health parameters related to metabolic diseases. Therefore, applying the intervention in primary healthcare may help promote the well-being in elderly.

Investigations on Anticancer and Antimalarial Activities of Indole-Sulfonamide Derivatives and In Silico Studies

A library of 44 indole-sulfonamide derivatives (1-44) were investigated for their cytotoxic activities against four cancer cell lines (i.e., HuCCA-1, HepG2, A549, and MOLT-3) and antimalarial effect. Most of the studied indoles exhibit anticancer activity against the MOLT-3 cell line, whereas only hydroxyl-containing bisindoles displayed anticancer activities against the other tested cancer cells as well as antimalarial effect. The most promising anticancer compounds were noted to be CF₃, Cl, and NO₂ derivatives of hydroxyl-bearing bisindoles (30, 31, and 36), while the most promising antimalarial compound was an OCH₃ derivative of non-hydroxyl-containing bisindole 11. Five quantitative structure-activity relationship (QSAR) models were successfully constructed, providing acceptable predictive performance (training set: R = 0.6186-0.9488, RMSE = 0.0938-0.2432; validation set: R = 0.4242-0.9252, RMSE = 0.1100-0.2785). QSAR modeling revealed that mass, charge, polarizability, van der Waals volume, and electronegativity are key properties governing activities of the compounds. QSAR models were further applied to guide the rational design of an additional set of 22 compounds (P1-P22) in which their activities were predicted. The prediction revealed a set of promising virtually constructed compounds (P1, P3, P9, P10, and P16) for further synthesis and development as anticancer and antimalarial agents. Molecular docking was also performed to reveal possible modes of bindings and interactions between the studied compounds and target proteins. Taken together, insightful structure-activity relationship information obtained herein would be beneficial for future screening, design, and structural optimization of the related compounds.

QSAR-driven rational design of novel DNA methyltransferase 1 inhibitors

DNA methylation, an epigenetic modification, is mediated by DNA methyltransferases (DNMTs), a family of enzymes. Inhibitions of these enzymes are considered a promising strategy for the treatment of several diseases. In this study, a quantitative structure-activity relationship (QSAR) modeling was employed to understand the structure-activity relationship (SAR) of currently available non-nucleoside DNMT1 inhibitors (i.e., indole and oxazoline/1,2-oxazole scaffolds). Two QSAR models were successfully constructed using multiple linear regression (MLR) and provided good predictive performance (R²_Tr = 0.850-0.988 and R²_CV = 0.672-0.869). Bond information content index (BIC1) and electronegativity (R6e+) are the most influential descriptors governing the activity of compounds. The constructed QSAR models were further applied for guiding a rational design of novel inhibitors. A novel set of 153 structurally modified compounds were designed in silico according to the important descriptors deduced from the QSAR finding, and their DNMT1 inhibitory activities were predicted. This result demonstrated that 86 newly designed inhibitors were predicted to elicit enhanced DNMT1 inhibitory activity when compared to their parent compounds. Finally, a set of promising compounds as potent DNMT1 inhibitors were highlighted to be further developed. The key SAR findings may also be beneficial for structural optimization to improve properties of the known inhibitors.

Rational design of novel coumarins: A potential trend for antioxidants in cosmetics

Coumarins are well-known for their antioxidant effect and aromatic property, thus, they are one of ingredients commonly added in cosmetics and personal care products. Quantitative structure-activity relationships (QSAR) modeling is an in silico method widely used to facilitate rational design and structural optimization of novel drugs. Herein, QSAR modeling was used to elucidate key properties governing antioxidant activity of a series of the reported coumarin-based antioxidant agents (1-28). Several types of descriptors (calculated from 4 softwares i.e., Gaussian 09, Dragon, PaDEL and Mold2 softwares) were used to generate three multiple linear regression (MLR) models with preferable predictive performance (Q 2 LOO-CV = 0.813-0.908; RMSE LOO-CV = 0.150-0.210; Q 2 Ext = 0.875-0.952; RMSE Ext = 0.104-0.166). QSAR analysis indicated that number of secondary amines (nArNHR), polarizability (G2p), electronegativity (D467, D580, SpMin2_Bhe, and MATS8e), van der Waals volume (D491 and D461), and H-bond potential (SHBint4) are important properties governing antioxidant activity. The constructed models were also applied to guide in silico rational design of an additional set of 69 structurally modified coumarins with improved antioxidant activity. Finally, a set of 9 promising newly design compounds were highlighted for further development. Structure-activity analysis also revealed key features required for potent activity which would be useful for guiding the future rational design. In overview, our findings demonstrated that QSAR modeling could possibly be a facilitating tool to enhance successful development of bioactive compounds for health and cosmetic applications.

ThalPred: a web-based prediction tool for discriminating thalassemia trait and iron deficiency anemia

Background

The hypochromic microcytic anemia (HMA) commonly found in Thailand are iron deficiency anemia (IDA) and thalassemia trait (TT). Accurate discrimination between IDA and TT is an important issue and better methods are urgently needed. Although considerable RBC formulas and indices with various optimal cut-off values have been developed, distinguishing between IDA and TT is still a challenging problem due to the diversity of various anemic populations. To address this problem, it is desirable to develop an improved and automated prediction model for discriminating IDA from TT.

Methods

We retrospectively collected laboratory data of HMA found in Thai adults. Five machine learnings, including k-nearest neighbor (k-NN), decision tree, random forest (RF), artificial neural network (ANN) and support vector machine (SVM), were applied to construct a discriminant model. Performance was assessed and compared with thirteen existing discriminant formulas and indices.

Results

The data of 186 patients (146 patients with TT and 40 with IDA) were enrolled. The interpretable rules derived from the RF model were proposed to demonstrate the combination of RBC indices for discriminating IDA from TT. A web-based tool ‘ThalPred’ was implemented using an SVM model based on seven RBC parameters. ThalPred achieved prediction results with an external accuracy, MCC and AUC of 95.59, 0.87 and 0.98, respectively.

Conclusion

ThalPred and an interpretable rule were provided for distinguishing IDA from TT. For the convenience of health care team experimental scientists, a web-based tool has been established at http://codes.bio/thalpred/ by which users can easily get their desired screening test result without the need to go through the underlying mathematical and computational details.

Rational design of novel sirtuin 1 activators via structure-activity insights from application of QSAR modeling

Sirtuin 1 (SIRT1) enzyme regulates major cell activities, and its activation offers lucrative therapeutic potentials for aging diseases including Alzheimer's disease (AD). Regarding the global aging society, continual attention has been given to various chemical scaffolds as a source for the discovery of novel SIRT1 activators since the discovery of the pioneer activator, resveratrol. Understanding structure-activity relationship (SAR) is essential for screening, designing as well as improving the properties of drugs. In this study, an in silico approach based on quantitative structure-activity relationship (QSAR) modeling, was employed for understanding the SAR of currently available SIRT1 fused-aromatic activators (i.e., imidazothiazole, oxazolopyridine, and azabenzimidazole analogs). Three QSAR models constructed using multiple linear regression (MLR) provided good predictive performance (R ² _LOOCV = 0.729 - 0.863 and RMSE _LOOCV = 0.165 - 0.325). An additional novel set of 181 structurally modified compounds were rationally designed according to key descriptors deduced from the QSAR findings and their SIRT1 activities were predicted using the constructed models. In overview, the study provides insightful SAR findings of currently available SIRT1 activators that would be useful for guiding the rational design, screening, and development of further potent SIRT1 activators for managing age-related clinical conditions. A series of promising compounds as well as important scaffolds and molecular properties for potent SIRT1 activator were highlighted. This study demonstrated the efficacious role of QSAR-driven structural modification for the rational design of novel leads.

Multidisciplinary approaches for targeting the secretase protein family as a therapeutic route for Alzheimer's disease

The continual increase of the aging population worldwide renders Alzheimer's disease (AD) a global prime concern. Several attempts have been focused on understanding the intricate complexity of the disease's development along with the on- andgoing search for novel therapeutic strategies. Incapability of existing AD drugs to effectively modulate the pathogenesis or to delay the progression of the disease leads to a shift in the paradigm of AD drug discovery. Efforts aimed at identifying AD drugs have mostly focused on the development of disease-modifying agents in which effects are believed to be long lasting. Of particular note, the secretase enzymes, a group of proteases responsible for the metabolism of the β-amyloid precursor protein (βAPP) and β-amyloid (Aβ) peptides production, have been underlined for their promising therapeutic potential. This review article attempts to comprehensively cover aspects related to the identification and use of drugs targeting the secretase enzymes. Particularly, the roles of secretases in the pathogenesis of AD and their therapeutic modulation are provided herein. Moreover, an overview of the drug development process and the contribution of computational (in silico) approaches for facilitating successful drug discovery are also highlighted along with examples of relevant computational works. Promising chemical scaffolds, inhibitors, and modulators against each class of secretases are also summarized herein. Additionally, multitarget secretase modulators are also taken into consideration in light of the current growing interest in the polypharmacology of complex diseases. Finally, challenging issues and future outlook relevant to the discovery of drugs targeting secretases are also discussed.

Correction: Privileged substructures for anti-sickling activity via cheminformatic analysis

Correction for ‘Privileged substructures for anti-sickling activity via cheminformatic analysis’ by Chuleeporn Phanus-umporn et al., RSC Adv., 2018, 8, 5920–5935.

Privileged substructures for anti-sickling activity via cheminformatic analysis

Sickle cell disease (SCD), an autosomal recessive genetic disorder, has been recognized by the World Health Organization (WHO) as a major public health problem as it affects 300 000 individuals worldwide. Complications arising from SCD include anemia, microvascular occlusion, severe pain, stokes, renal dysfunction and infections. A lucrative therapeutic strategy is to employ anti-sickling agents that can disrupt the formation of the HbS polymer. This study therefore employed cheminformatic approaches, encompassing classification structure–activity relationship (CSAR) modeling, to deduce the privileged substructures giving rise to the anti-sickling activity of an investigated set of 115 compounds, followed by substructure analysis. Briefly, the compiled compounds were described by fingerprint descriptors and used in the construction of CSAR models via several machine learning algorithms. The modelability of the data set, as exemplified by the MODI index, was determined to be in the range of 0.70–0.84. The predictive performance was deduced by the accuracy, sensitivity, specificity and Matthews correlation coefficient, which was found to be statistically robust, whereby the former three parameters afforded values in excess of 0.7 while the latter statistical parameter provided a value greater than 0.5. An analysis of the top 20 important substructure descriptors for anti-sickling activity revealed that 10 important features were significant in the differentiation of actives from inactives, as illustrated by aromaticity/conjugation (e.g. SubFPC287, SubFPC171 and SubFPC5), carbonyl groups (e.g. SubFPC137, SubFPC139, SubFPC49 and SubFPC135) and miscellaneous groups (e.g. SubFPC303, SubFPC302 and SubFPC275). Furthermore, an analysis of the structure–activity relationship revealed that the length of alkyl chains, choice of functional moiety and position of substitution on the benzene ring may affect the anti-sickling activity of these compounds. Thus, this knowledge is anticipated to be useful for guiding the design of robust compounds against the gelling activity of HbS, as preliminarily demonstrated in the data-driven compound design presented herein.

Cheminformatic approaches (classification structure–activity relationship models based on 12 fingerprint classes) were employed for deducing privileged substructures giving rise to the anti-sickling activity of an investigated set of 115 compounds.

Coriander (Coriandrum sativum): A promising functional food toward the well-being

Coriandrum sativum (C. sativum) or coriander is one of the most popularly used spices in culinary worldwide, and its medicinal values has been recognized since ancient time. C. sativum contains bioactive phytochemicals that are accounted for a wide range of biological activities including antioxidant, anticancer, neuroprotective, anxiolytic, anticonvulsant, analgesic, migraine-relieving, hypolipidemic, hypoglycemic, hypotensive, antimicrobial, and antiinflammatory activities. The major compound, linalool, abundantly found in seeds is remarked for its abilities to modulate many key pathogenesis pathways of diseases. Apart from the modulating effects, the potent antioxidant property of the C. sativum provides a key mechanism behind its protective effects against neurodegenerative diseases, cancer, and metabolic syndrome. This review shed light on comprehensive aspects regarding the therapeutic values of the C. sativum, which indicate its significance of being a promising functional food for promoting the well-being in the era of aging and lifestyle-related diseases.

Exploring the Chemical Space of P-Glycoprotein Interacting Compounds

BACKGROUND

P-glycoprotein (Pgp) is well known for its clinical importance in the pharmacokinetics of drugs and its role in multidrug resistance. The promiscuity of Pgp that arises from its ability to extrude a wide range of lipophilic and structurally unrelated compounds from cells, render the classification and understanding of its interacting compounds a great challenge.

METHOD

In this study, a data set of Pgp-interacting compounds including 1463 inhibitors, 1085 noninhibitors, 308 substrates and 126 non-substrates was retrieved and subjected to a combination of analyses, including exploration of chemical space, statistical analysis of descriptor values and molecular fragment analysis, to obtain insight into distinct physicochemical properties and important chemical substructures which may govern the biological activity of investigated compounds toward Pgp. Statistical analysis of descriptor values and molecular fragment analysis indicated that particular size, shape, functional groups and molecular fragments may govern the classification of Pgp-interacting compounds by influencing their physicochemical properties and their interaction with Pgp. Overall, the interacting compounds (i.e., substrates and inhibitors) are larger in size, more flexible, more lipophilic, and less charged than non-interacting compounds (i.e., non-substrates and non-inhibitors).

CONCLUSION

The fragment analysis suggested that methyl and amino groups may be involved in Pgp inhibition and/or transport. The 2-methoxyphenol fragment was noted to be a potential substructure for designing Pgp inhibitors, whereas the 2-sulfanylidene-1-[3,4,5-trihydroxy-6-(hydroxymethyl)oxan-2- yl]-1,2-dihydropyridine-3-carbonitrile substructure was implied for avoiding transport by Pgp. Hence, this study could provide a comprehensive understanding of this drug transporter, which could benefit an early ADMET screening as well as drug design and development.

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.

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 RMSE_CV = 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.

Exploring the epigenetic drug discovery landscape

INTRODUCTION

Epigenetic modification has been implicated in a wide range of diseases and the ability to modulate such systems is a lucrative therapeutic strategy in drug discovery. Areas covered: This article focuses on the concepts and drug discovery aspects of epigenomics. This is achieved by providing a survey of the following concepts: (i) factors influencing epigenetics, (ii) diseases arising from epigenetics, (iii) epigenetic enzymes as druggable targets along with coverage of existing FDA-approved drugs and pharmacological agents, and (iv) drug repurposing/repositioning as a means for rapid discovery of pharmacological agents targeting epigenetics. Expert opinion: Despite significant interests in targeting epigenetic modifiers as a therapeutic route, certain classes of target proteins are heavily studied while some are less characterized. Thus, such orphan target proteins are not yet druggable with limited report of active modulators. Current research points towards a great future with novel drugs directed to the many complex multifactorial diseases of humans, which are still often poorly understood and difficult to treat.

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

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.

On the Origins of Hepatitis C Virus NS5B Polymerase Inhibitory Activity Using Machine Learning Approaches

Inhibition of non-structural protein 5B (NS5B) represents an attractive strategy for the therapeutic treatment of hepatitis C virus (HCV). In this study, machine learning classifiers such as artificial neural network (ANN), support vector machine (SVM), random forest (RF) and decision tree (DT) analyses were used to classify 970 compounds based on their physicochemical properties, including quantum chemical descriptors, constitutional descriptors, functional groups and molecular properties. Good predictive performance was obtained from all classifiers, providing accuracies ranging from 82.47-89.61% for external validation set. SVM was noted as the best classifier, indicated by its highest accuracy of 89.61%. The analyses were performed on data sets stratified by structural scaffolds (nucleoside and non-nucleoside) and bioactivities (active and inactive properties). In addition, a molecular fragment analysis was performed to investigate molecular substructures corresponding to biological activities. Furthermore, common substructures and potential functional groups governing the activities of active and inactive inhibitors were noted for the benefit of rational design and high-throughput screening towards potential HCV NS5B inhibitors.

Computer-Aided Drug Design of Bioactive Natural Products

Natural products have been an integral part of sustaining civilizations because of their medicinal properties. Past discoveries of bioactive natural products have relied on serendipity, and these compounds serve as inspiration for the generation of analogs with desired physicochemical properties. Bioactive natural products with therapeutic potential are abundantly available in nature and some of them are beyond exploration by conventional methods. The effectiveness of computational approaches as versatile tools for facilitating drug discovery and development has been recognized for decades, without exception, in the case of natural products. In the post-genomic era, scientists are bombarded with data produced by advanced technologies. Thus, rendering these data into knowledge that is interpretable and meaningful becomes an essential issue. In this regard, computational approaches utilize the existing data to generate knowledge that provides valuable understanding for addressing current problems and guiding the further research and development of new natural-derived drugs. Furthermore, several medicinal plants have been continuously used in many traditional medicine systems since antiquity throughout the world, and their mechanisms have not yet been elucidated. Therefore, the utilization of computational approaches and advanced synthetic techniques would yield great benefit to improving the world's health population and well-being.

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

Considerable 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 R_CV ranging from 0.5958 to 0.8957 and RMSE_CV 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.

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 non-inhibitors, 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.

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.

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.

Investigation of aromatase inhibitory activity of metal complexes of 8-hydroxyquinoline and uracil derivatives

PURPOSE

Estrogens play important roles in the pathogenesis and progression of breast cancer as well as estrogen-related diseases. Aromatase is a key enzyme in the rate-limiting step of estrogen production, in which its inhibition is one strategy for controlling estrogen levels to improve prognosis of estrogen-related cancers and diseases. Herein, a series of metal (Mn, Cu, and Ni) complexes of 8-hydroxyquinoline (8HQ) and uracil derivatives (4-9) were investigated for their aromatase inhibitory and cytotoxic activities.

METHODS

The aromatase inhibition assay was performed according to a Gentest™ kit using CYP19 enzyme, wherein ketoconazole and letrozole were used as reference drugs. The cytotoxicity was tested on normal embryonic lung cells (MRC-5) using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay.

RESULTS

Only Cu complexes (6 and 9) exhibited aromatase inhibitory effect with IC50 0.30 and 1.7 μM, respectively. Cytotoxicity test against MRC-5 cells showed that Mn and Cu complexes (5 and 6), as well as free ligand 8HQ, exhibited activity with IC50 range 0.74-6.27 μM.

CONCLUSION

Cu complexes (6 and 9) were found to act as a novel class of aromatase inhibitor. Our findings suggest that these 8HQ-Cu-uracil complexes are promising agents that could be potentially developed as a selective anticancer agent for breast cancer and other estrogen-related diseases.

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.

High therapeutic potential of Spilanthes acmella: A review

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.

Lipid-Membrane Affinity of Chimeric Metal-binding Green Fluorescent Protein

The Green Fluorescent Protein (GFP) is a useful marker to trace the expression of cellular proteins. However, little is known about changes in protein interaction properties after fusion to GFP. In this study, we present evidence for a binding affinity of chimeric cadmium-binding green fluorescent proteins to lipid membrane. This affinity has been observed in both cellular membranes and artificial lipid monolayers and bilayers. At the cellular level, the presence of Cd-binding peptide promoted the association of the chimeric GFP onto the lipid membrane, which declined the fluorescence emission of the engineered cells. Binding affinity to lipid membranes was further investigated using artificial lipid bilayers and monolayers. Small amounts of the chimeric GFP were found to incorporate into the lipid vesicles due to the high surface pressure of bilayer lipids. At low interfacial pressure of the lipid monolayer, incorporation of the chimeric Cd-binding GFP onto the lipid monolayer was revealed. From the measured lipid isotherms, we conclude that Cd-binding GFP mediates an increase in membrane fluidity and an expansion of the surface area of the lipid film. This evidence was strongly supported by epifluorescence microscopy, showing that the chimeric Cd-binding GFP preferentially binds to fluid-phase areas and defect parts of the lipid monolayer. All these findings demonstrate the hydrophobicity of the GFP constructs is mainly influenced by the fusion partner. Thus, the example of a metal-binding unit used here shines new light on the biophysical properties of GFP constructs.

Purification and characterization of a beta-lactamase from Haemophilus ducreyi in Escherichia coli

A pCb plasmid encoding a beta-lactamase from Haemophilus ducreyi was transferred to Escherichia coli, purified, and characterized. The beta-lactamase could be isolated from a culture filtrate and further purified by ammonium sulfate and chelating Sepharose fast flow loaded with Zn(2+). The purified enzyme resulted in a major band at approximately 30-kDa on SDS-PAGE and its pI was determined to be 5.4. The beta-lactamase could hydrolyze both penicillin antibiotics including ampicillin, benzylpenicillin, and carbenicillin as well as cephalosporin antibiotics including nitrocefin, cephalothin, cephaloridine, and cefoperazone. However, benzylpenicillin was the best substrate. The enzyme activity was inhibited by clavulanic acid but not by boric acid, cefotaxime, ethylenediaminetetraacetic acid, or phenylmethylsulfonyl fluoride. The sequence of the beta-lactamase gene was also determined. It confirmed that the enzyme belonged to a class A beta-lactamase which had 99% identity to the ampicillin resistance transposon Tn3 of pBR322. Two nucleotides were different between the E. coli (Tn3) and H. ducreyi (pCb) genes that affected the amino-acid sequence. The valine at position 82 (ABL 84) was changed to isoleucine and the alanine at position 182 (ABL 184) was changed to valine. Genetic homogeneity among beta-lactamases is remarkable. Amino acid sequencing of some beta-lactamases has shown that substitution of only a few amino acids in the bla gene leads to high-level resistance against specific cephalosporins.

Calorimetric analysis of cephalosporins using an immobilized TEM-1 beta-lactamase on Ni2+ chelating sepharose fast flow

Two beta-lactamases, penicillinase type I from Bacillus cereus and TEM-1 beta-lactamase from Haemophilus ducreyi, were immobilized on a Chelating Sepharose Fast Flow column loaded with Ni2+ in an active form. Flow-injection analysis of beta-lactams was performed by using an enzyme column reactor fitted into the enzyme thermistor. With both enzymes it was possible to monitor both penicillins and cephalosporins. Moreover, Michaelis constants of the TEM-1 beta-lactamase were markedly increased upon immobilization for all substrates, especially carbenicillin, cephaloridine, and cefoperazone.

TPA-activated transcription of the human MnSOD gene: role of transcription factors Sp-1 and Egr-1

Induction of manganese superoxide dismutase (MnSOD) in response to oxidative stress has been well established in animals, tissues, and cell culture. However, the role of the human MnSOD (hMnSOD) promoter in stimulus-dependent activation of transcription is unknown. The hMnSOD promoter lacks both a TATA and a CAAT box but possesses several GC motifs. In a previous study, we showed that the basal promoter contains multiple Sp1 and AP-2 binding sites and that Sp1 is essential for the constitutive expression of the hMnSOD gene. In this study, we identified an Egr-1 binding site in the basal promoter of hMnSOD. We also found that the basal promoter is responsive to 12-O-tetradecanoylphorbol-13-acetate (TPA)-activated hMnSOD transcription in the human hepatocarcinoma cell line HepG2. The contributions of these binding sites and the roles of the transcription factors Egr-1, AP-2, and Sp1 in the activation of hMnSOD transcription by TPA were investigated by site-directed mutation analysis, Western blotting, and overexpression of transcription factors. The results showed that Sp1 plays a positive role for both basal and TPA-activated hMnSOD transcription, whereas overexpression of Egr-1 has a negative role in the basal promoter activity without any effect on TPA-mediated activation of hMnSOD transcription.

Constituents and bioactivity of the tubers of Euphorbia sessiliflora

The diterpene ent-12-hydroxy-12[R]-abieta-8(14),13(15)-dien-16,12-olide was isolated from the tubers of Euphorbia sessiliflora Roxb., together with four known ent-abietadienolides, four known cycloartane triterpenes and ellagic acid-beta-D-glucopyranoside. Two of these metabolates displayed moderate antibacterial activities.