Structure- and ligand-based drug design approaches for neglected tropical diseases

Drug discovery has moved toward more rational strategies based on our increasing understanding of the fundamental principles of protein-ligand interactions. Structure( SBDD) and ligand-based drug design (LBDD) approaches bring together the most powerful concepts in modern chemistry and biology, linking medicinal chemistry with structural biology. The definition and assessment of both chemical and biological space have revitalized the importance of exploring the intrinsic complementary nature of experimental and computational methods in drug design. Major challenges in this field include the identification of promising hits and the development of high-quality leads for further development into clinical candidates. It becomes particularly important in the case of neglected tropical diseases (NTDs) that affect disproportionately poor people living in rural and remote regions worldwide, and for which there is an insufficient number of new chemical entities being evaluated owing to the lack of innovation and R&D investment by the pharmaceutical industry. This perspective paper outlines the utility and applications of SBDD and LBDD approaches for the identification and design of new small-molecule agents for NTDs.

Ligand- and Structure-Based Drug Design Strategies and PPAR delta/alpha Selectivity

Peroxisome-proliferator-activated receptors are a class of nuclear receptors with three subtypes: a, ? and d. Their main function is regulating gene transcription related to lipid and carbohydrate metabolism. Currently, there are no peroxisome-proliferator-activated receptors d drugs being marketed. In this work, we studied a data set of 70 compounds with a and d activity. Three partial least square models were created, and molecular docking studies were performed to understand the main reasons for peroxisome-proliferator-activated receptors d selectivity. The obtained results showed that some molecular descriptors (log P, hydration energy, steric and polar properties) are related to the main interactions that can direct ligands to a particular peroxisome-proliferator-activated receptors subtype.

Structure-based drug design studies on a series of aldolase inhibitors

Human African trypanosomiasis, also known as sleeping sickness, is a major cause of death in Africa, and for which there are no safe and effective treatments available. The enzyme aldolase from Trypanosoma brucei is an attractive, validated target for drug development. A series of alkyl‑glycolamido and alkyl-monoglycolate derivatives was studied employing a combination of drug design approaches. Three-dimensional quantitative structure-activity relationships (3D QSAR) models were generated using the comparative molecular field analysis (CoMFA). Significant results were obtained for the best QSAR model (r2 = 0.95, non-cross-validated correlation coefficient, and q2 = 0.80, cross-validated correlation coefficient), indicating its predictive ability for untested compounds. The model was then used to predict values of the dependent variables (pKi) of an external test set,the predicted values were in good agreement with the experimental results. The integration of 3D QSAR, molecular docking and molecular dynamics simulations provided further insight into the structural basis for selective inhibition of the target enzyme.

Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data

Background: This paper addresses the prediction of the free energy of binding of a drug candidate with enzyme InhA associated with Mycobacterium tuberculosis. This problem is found within rational drug design, where interactions between drug candidates and target proteins are verified through molecular docking simulations. In this application, it is important not only to correctly predict the free energy of binding, but also to provide a comprehensible model that could be validated by a domain specialist. Decision-tree induction algorithms have been successfully used in drug-design related applications, specially considering that decision trees are simple to understand, interpret, and validate. There are several decision-tree induction algorithms available for general-use, but each one has a bias that makes it more suitable for a particular data distribution. In this article, we propose and investigate the automatic design of decision-tree induction algorithms tailored to particular drug-enzyme binding data sets. We investigate the performance of our new method for evaluating binding conformations of different drug candidates to InhA, and we analyze our findings with respect to decision tree accuracy, comprehensibility, and biological relevance. Results: The empirical analysis indicates that our method is capable of automatically generating decision-tree induction algorithms that significantly outperform the traditional C4.5 algorithm with respect to both accuracy and comprehensibility. In addition, we provide the biological interpretation of the rules generated by our approach, reinforcing the importance of comprehensible predictive models in this particular bioinformatics application. Conclusions: We conclude that automatically designing a decision-tree algorithm tailored to molecular docking data is a promising alternative for the prediction of the free energy from the binding of a drug candidate with a flexible-receptor.

A Combined Study Using Ligand-Based Design, Synthesis, and Pharmacological Evaluation of Analogues of the Acetaminophen Ortho-Regioisomer with Potent Analgesic Activity

A ligand-based drug design study was performed to acetaminophen regioisomers as analgesic candidates employing quantum chemical calculations at the DFT/B3LYP level of theory and the 6-31G* basis set. To do so, many molecular descriptors were used such as highest occupied molecular orbital, ionization potential, HO bond dissociation energies, and spin densities, which might be related to quench reactivity of the tyrosyl radical to give N-acetyl-p-benzosemiquinone-imine through an initial electron withdrawing or hydrogen atom abstraction. Based on this in silico work, the most promising molecule, orthobenzamol, was synthesized and tested. The results expected from the theoretical prediction were confirmed in vivo using mouse models of nociception such as writhing, paw licking, and hot plate tests. All biological results suggested an antinociceptive activity mediated by opioid receptors. Furthermore, at 90 and 120 min, this new compound had an effect that was comparable to morphine, the standard drug for this test. Finally, the pharmacophore model is discussed according to the electronic properties derived from quantum chemistry calculations.

Pharmacokinetic properties and in silico ADME modeling in drug discovery

The discovery and development of a new drug are time-consuming, difficult and expensive. This complex process has evolved from classical methods into an integration of modern technologies and innovative strategies addressed to the design of new chemical entities to treat a variety of diseases. The development of new drug candidates is often limited by initial compounds lacking reasonable chemical and biological properties for further lead optimization. Huge libraries of compounds are frequently selected for biological screening using a variety of techniques and standard models to assess potency, affinity and selectivity. In this context, it is very important to study the pharmacokinetic profile of the compounds under investigation. Recent advances have been made in the collection of data and the development of models to assess and predict pharmacokinetic properties (ADME - absorption, distribution, metabolism and excretion) of bioactive compounds in the early stages of drug discovery projects. This paper provides a brief perspective on the evolution of in silico ADME tools, addressing challenges, limitations, and opportunities in medicinal chemistry.

Novel aryl beta-aminocarbonyl derivatives as inhibitors of Trypanosoma cruzi trypanothione reductase: binding mode revised by docking and GRIND2-based 3D-QSAR procedures

Trypanothione reductase has long been investigated as a promising target for chemotherapeutic intervention in Chagas disease, since it is an enzyme of a unique metabolic pathway that is exclusively present in the pathogen but not in the human host, which has the analog Glutathione reductase. In spite of the present data-set includes a small number of compounds, a combined use of flexible docking, pharmacophore perception, ligand binding site prediction, and Grid-Independent Descriptors GRIND2-based 3D-Quantitative Structure-Activity Relationships (QSAR) procedures allowed us to rationalize the different biological activities of a series of 11 aryl beta-aminocarbonyl derivatives, which are inhibitors of Trypanosoma cruzi trypanothione reductase (TcTR). Three QSAR models were built and validated using different alignments, which are based on docking with the TcTR crystal structure, pharmacophore, and molecular interaction fields. The high statistical significance of the models thus obtained assures the robustness of this second generation of GRIND descriptors here used, which were able to detect the most important residues of such enzyme for binding the aryl beta-aminocarbonyl derivatives, besides to rationalize distances among them. Finally, a revised binding mode has been proposed for our inhibitors and independently supported by the different methodologies here used, allowing further optimization of the lead compounds with such combined structure- and ligand-based approaches in the fight against the Chagas disease.

Structural role of the active-site metal in the conformation of Trypanosoma brucei phosphoglycerate mutase

Phosphoglycerate mutases (PGAMs) participate in both the glycolytic and the gluconeogenic pathways in reversible isomerization of 3-phosphoglycerate and 2-phosphoglycerate. PGAMs are members of two distinct protein families: enzymes that are dependent on or independent of the 2,3-bisphosphoglycerate cofactor. We determined the X-ray structure of the monomeric Trypanosoma brucei independent PGAM (TbiPGAM) in its apoenzyme form, and confirmed this observation by small angle X-ray scattering data. Comparing the TbiPGAM structure with the Leishmania mexicana independent PGAM structure, previously reported with a phosphoglycerate molecule bound to the active site, revealed the domain movement resulting from active site occupation. The structure reported here shows the interaction between Asp319 and the metal bound to the active site, and its contribution to the domain movement. Substitution of the metal-binding residue Asp319 by Ala resulted in complete loss of independent PGAM activity, and showed for the first time its involvement in the enzymes function. As TbiPGAM is an attractive molecular target for drug development, the apoenzyme conformation described here provides opportunities for its use in structure-based drug design approaches.

Sesquiterpene Lactones with Anti-Hepatitis C Virus Activity Using Molecular Descriptors

Hepatitis C is a worldwide public health problem. The available therapies are limited by their partial effectiveness and with meaningful side-effects. Sesquiterpene lactones (SLs) are a group of natural products with a wide variety of chemical structures and biological activities associated. There are few studies about the influence of the molecular structure of SLs for the anti-hepatitis C virus activity. In the present work, SLs are investigated in a subgenomic RNA replicon assay system and were analyzed using multiple linear regression along with self-organizing maps with DRAGON descriptors in order to identify the structural requirements for their biological activity and to predict the inhibitory potency of SLs. Characteristics such as stereochemistry and electronic effects demonstrated to be important for their anti-HCV activity, and the SOM produced a clear separation betwenn active and inactive compounds. Therefore, it is possible to use this map as a filter for virtual screening to predict the anti-HCV activity of SLs.

Leishmanicidal activity of an alkenylphenol from Piper malacophyllum is related to plasma membrane disruption

Leishmaniasis and Chagas disease are parasitic protozoan infections that affect the poorest population in the world, causing high mortality and morbidity. As a result of highly toxic and long-duration treatments, novel, safe and more efficacious drugs are essential. In this work, the methanol (MeOH) extract from the leaves of Piper malacophyllum (Piperaceae) was fractioned to afford one alkenylphenol, which was characterized as 4-[(3'E)-decenyl]phenol (gibbilimbol B) by spectroscopic methods. Anti-protozoan in vitro assays demonstrated for the first time that Leishmania (L.) infantum chagasi was susceptible to gibbilimbol B. with an in vitro EC50 of 23 mu g/mL against axenic promastigotes and an EC50 of 22 mu g/mL against intracellular amastigotes. Gibbilimbol B was also tested for anti-trypanosomal activity (Trypanosoma cruzi) and showed an EC50 value of 17 mu g/mL against trypomastigotes. To evaluate the cytotoxic parameters, this alkenylphenol was tested in vitro against NCTC cells, showing a CC50 of 59 mu g/mL and absent hemolytic activity at the highest concentration of 75 mu g/mL. Using the fluorescent probe SYTOX Green suggested that the alkenylphenol disrupted the Leishmania plasma membrane upon initial incubation. Further drug design studies aiming at derivatives could be a promising tool for the development of new therapeutic agents for leishmaniasis and Chagas disease. (C) 2012 Elsevier Inc. All rights reserved.

Antioxidant Activity of Resveratrol Analogs

This study evaluated the antioxidant activity of five resveratrol analogs by relating the activity of the molecule with its chemical structure. The five resveratrol analogs were synthesized and the antioxidant activity was evaluated using the DPPH method. The resveratrol was used as the reference standard. A descriptive statistical analysis and ANOVA followed by the Tukey test, with the aid of software. The antioxidant activity of resveratrol analogs was considered statistically different, with the analog A which showed activity superior to the others. The five analogs presented lower antioxidant activity than the reference standard (p <0.001). According to the findings, hydroxylation was the molecular modification that gave the best evaluated antioxidant activity result. Resveratrol analogs may have an important antioxidative activity, but with the one with the higher IC50 was presented by the natural compound.

Synthesis, Biological Evaluation, And Molecular Modeling of Chalcone Derivatives As Potent Inhibitors of Mycobacterium tuberculosis Protein Tyrosine Phosphatases (PtpA and PtpB)

Tuberculosis (TB) is a major infectious disease caused by Mycobacterium tuberculosis (Mtb). According to the World Health Organization (WHO), about 1.8 million people die from TB and 10 million new cases are recorded each year. Recently, a new series of naphthylchalcones has been identified as inhibitors of Mtb protein tyrosine phosphatases (PTPs). In this work, 100 chalcones were designed, synthesized, and investigated for their inhibitory properties against MtbPtps. Structure-activity relationships (SAR) were developed, leading to the discovery of new potent inhibitors with IC50 values in the low-micromolar range. Kinetic studies revealed competitive inhibition and high selectivity toward the Mtb enzymes. Molecular modeling investigations were carried out with the aim of revealing the most relevant structural requirements underlying the binding affinity and selectivity of this series of inhibitors as potential anti-TB drugs.

The leishmanicidal flavonols quercetin and quercitrin target Leishmania (Leishmania) amazonensis arginase

Polyamine biosynthesis enzymes are promising drug targets for the treatment of leishmaniasis, Chagas' disease and African sleeping sickness. Arginase, which is a metallohydrolase, is the first enzyme involved in polyamine biosynthesis and converts arginine into ornithine and urea. Ornithine is used in the polyamine pathway that is essential for cell proliferation and ROS detoxification by trypanothione. The flavonols quercetin and quercitrin have been described as antitrypanosomal and antileishmanial compounds, and their ability to inhibit arginase was tested in this work. We characterized the inhibition of recombinant arginase from Leishmania (Leishmania) amazonensis by quercetin, quercitrin and isoquercitrin. The IC50 values for quercetin, quercitrin and isoquercitrin were estimated to be 3.8, 10 and 4.3 mu M, respectively. Quercetin is a mixed inhibitor, whereas quercitrin and isoquercitrin are uncompetitive inhibitors of L. (L.) amazonensis arginase. Quercetin interacts with the substrate L-arginine and the cofactor Mn2+ at pH 9.6, whereas quercitrin and isoquercitrin do not interact with the enzyme's cofactor or substrate. Docking analysis of these flavonols suggests that the cathecol group of the three compounds interact with Asp129, which is involved in metal bridge formation for the cofactors Mn-A(2+) and Mn-B(2+) in the active site of arginase. These results help to elucidate the mechanism of action of leishmanicidal flavonols and offer new perspectives for drug design against Leishmania infection based on interactions between arginase and flavones. (C) 2012 Elsevier Inc. All rights reserved.

Structure- and Ligand-Based Structure-Activity Relationships for a Series of Inhibitors of Aldolase

Aldolase has emerged as a promising molecular target for the treatment of human African trypanosomiasis. Over the last years, due to the increasing number of patients infected with Trypanosoma brucei, there is an urgent need for new drugs to treat this neglected disease. In the present study, two-dimensional fragment-based quantitative-structure activity relationship (QSAR) models were generated for a series of inhibitors of aldolase. Through the application of leave-one-out and leave-many-out cross-validation procedures, significant correlation coefficients were obtained (r(2) = 0.98 and q(2) = 0.77) as an indication of the statistical internal and external consistency of the models. The best model was employed to predict pK(i) values for a series of test set compounds, and the predicted values were in good agreement with the experimental results, showing the power of the model for untested compounds. Moreover, structure-based molecular modeling studies were performed to investigate the binding mode of the inhibitors in the active site of the parasitic target enzyme. The structural and QSAR results provided useful molecular information for the design of new aldolase inhibitors within this structural class.

A fragment-based approach for ligand binding affinity and selectivity for the liver X receptor beta

Selective modulation of liver X receptor beta (LXR beta) has been recognized as an important approach to prevent or reverse the atherosclerotic process. In the present work, we have developed robust conformation-independent fragment-based quantitative structure-activity and structure-selectivity relationship models for a series of quinolines and cinnolines as potent modulators of the two LXR sub-types. The generated models were then used to predict the potency of an external test set and the predicted values were in good agreement with the experimental results, indicating the potential of the models for untested compounds. The final 2D molecular recognition patterns obtained were integrated to 3D structure-based molecular modeling studies to provide useful insights into the chemical and structural determinants for increased LXR beta binding affinity and selectivity. (C) 2011 Elsevier Inc. All rights reserved.