Structural and chemical basis for anticancer activity of a series of 'beta'-tubulin ligands: molecular modeling and 3D QSAR studies

An important approach to cancer therapy is the design of small molecule modulators that interfere with microtubule dynamics through their specific binding to the ²-subunit of tubulin. In the present work, comparative molecular field analysis (CoMFA) studies were conducted on a series of discodermolide analogs with antimitotic properties. Significant correlation coefficients were obtained (CoMFA(i), q² =0.68, r²=0.94; CoMFA(ii), q² = 0.63, r²= 0.91), indicating the good internal and external consistency of the models generated using two independent structural alignment strategies. The models were externally validated employing a test set, and the predicted values were in good agreement with the experimental results. The final QSAR models and the 3D contour maps provided important insights into the chemical and structural basis involved in the molecular recognition process of this family of discodermolide analogs, and should be useful for the design of new specific ²-tubulin modulators with potent anticancer activity.

Inhibition of immune complex-mediated neutrophil oxidative metabolism: A pharmacophore model for 3-phenylcoumarin derivatives using GRIND-based 3D-QSAR and 2D-QSAR procedures

In this study, twenty hydroxylated and acetoxylated 3-phenylcoumarin derivatives were evaluated as inhibitors of immune complex-stimulated neutrophil oxidative metabolism and possible modulators of the inflammatory tissue damage found in type III hypersensitivity reactions. By using lucigenin- and luminol-enhanced chemiluminescence assays (CL-luc and CL-lum, respectively), we found that the 6,7-dihydroxylated and 6,7-diacetoxylated 3-phenylcoumarin derivatives were the most effective inhibitors. Different structural features of the other compounds determined CL-luc and/or CL-lum inhibition. The 2D-QSAR analysis suggested the importance of hydrophobic contributions to explain these effects. In addition, a statistically significant 3D-QSAR model built applying GRIND descriptors allowed us to propose a virtual receptor site considering pharmacophoric regions and mutual distances. Furthermore, the 3-phenylcoumarins studied were not toxic to neutrophils under the assessed conditions. (C) 2007 Elsevier Masson SAS. All rights reserved.

CoMFA and CoMSIA 3D QSAR Models for a Series of Cyclic Imides with Analgesic Activity

Three-dimensional quantitative structure-activity relationships (3D-QSAR) were performed for a series of analgesic cyclic imides using the CoMFA and CoMSIA methods. Significant correlation coefficients ( CoMFA, r(2) = 0.95 and q(2) = 0.72; CoMSIA, r(2) = 0.96 and q(2) = 0.76) were obtained, and the generated models were externally validated using test sets. The final QSAR models as well as the information gathered from 3D contour maps should be useful for the design of novel cyclic imides having improved analgesic activity.

Structural basis for selective inhibition of trypanosomatid glyceraldehyde-3-phosphate dehydrogenase: Molecular docking and 3D QSAR studies

The glycolytic enzyme glyceraldehyde-3 -phosphate dehydrogenase (GAPDH) is as an attractive target for the development of novel antitrypanosomatid agents. In the present work, comparative molecular field analysis and comparative molecular similarity index analysis were conducted on a large series of selective inhibitors of trypanosomatid GAPDH. Four statistically significant models were obtained (r(2) > 0.90 and q(2) > 0.70), indicating their predictive ability for untested compounds. The 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. Molecular modeling studies provided further insight into the structural basis for selective inhibition of trypanosomatid GAPDH.

Pharmacophore-based 3D QSAR studies on a series of high affinity 5-HT(1A) receptor ligands

5-HT(1A) receptor antagonists have been employed to treat depression, but the lack of structural information on this receptor hampers the design of specific and selective ligands. In this study, we have performed CoMFA studies on a training set of arylpiperazines (high affinity 5-HT(1A) receptor ligands) and to produce an effective alignment of the data set, a pharmacophore model was produced using Galahad. A statistically significant model was obtained, indicating a good internal consistency and predictive ability for untested compounds. The information gathered from our receptor-independent pharmacophore hypothesis is in good agreement with results from independent studies using different approaches. Therefore, this work provides important insights on the chemical and structural basis involved in the molecular recognition of these compounds. (C) 2010 Elsevier Masson SAS. All rights reserved.

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.

Um novo modelo para os sítios de interação dos antagonistas H2, baseado na caracterização química dos sítios primário e secundário por QSAR- 3D

A new model for the H2 antagonists binding site is postulated based on adsorption coefficient values of sixteen antagonists, in the affinities constants of the primary and secondary binding sites, and in the chemical characterization of these sites by 3D-QSAR. All study compounds are in the extended conformation and deprotonated form. The lateral validation of the QSARs, CoMFA analysis, affinity constants and chemical similarity data suggest that the antagonists block the proton pump in the H2 receptor interacting with two tyrosines - one in the helix 5, and other in the helix 6.

QSAR-3D/CoMFA em compostos imídicos com atividade antinociceptiva

Imide compounds have shown biological activity. These compounds can be easily synthesized with good yields. The objective of this paper was the rational planning of imides and sulfonamides with antinociceptive activity using the 3D-QSAR/CoMFA approach. The studies were performed using two data sets. The first set consisted of 39 cyclic imides while the second set consisted of 39 imides and 15 sulfonamides. The 3D- QSAR/CoMFA models have shown that the steric effect is important for the antinociceptive activity of imide and sulphonamide compounds. Ten new compounds with improved potential antinociceptive activity have been proposed by de novo design leapfrog simulations.

Estudos de relações estrutura-atividade quantitativas (QSAR) de bis-benzamidinas com atividade antifúngica

This paper describes 2D-QSAR and 3D-QSAR studies against Candida albicans and Cryptococcus neofarmans for a set of 20 bisbenzamidines. In the studies of 2D-QSAR with C. albicans it was obtained a correlation between log MIC-1 and lipolo component-Z (r² = 0.68; Q² = 0.51). In the case of C. neofarmans a correlation between log MIC-1 and lipolo component-Z and of Balaban index (r² = 0.85; Q² = 0.6) was obtained. 3D-QSAR studies using CoMFA showed that the steric fields contributed more to the predicted activities for Candida albicans (94.9%) and Cryptococcus neofarmans (97.9%).

3D-Pharmacophore mapping of thymidine-based inhibitors of TMPK as potential antituberculosis agents

Tuberculosis (TB) is the primary cause of mortality among infectious diseases. Mycobacterium tuberculosis monophosphate kinase (TMPKmt) is essential to DNA replication. Thus, this enzyme represents a promising target for developing new drugs against TB. In the present study, the receptor-independent, RI, 4D-QSAR method has been used to develop QSAR models and corresponding 3D-pharmacophores for a set of 81 thymidine analogues, and two corresponding subsets, reported as inhibitors of TMPKmt. The resulting optimized models are not only statistically significant with r (2) ranging from 0.83 to 0.92 and q (2) from 0.78 to 0.88, but also are robustly predictive based on test set predictions. The most and the least potent inhibitors in their respective postulated active conformations, derived from each of the models, were docked in the active site of the TMPKmt crystal structure. There is a solid consistency between the 3D-pharmacophore sites defined by the QSAR models and interactions with binding site residues. Moreover, the QSAR models provide insights regarding a probable mechanism of action of the analogues.

Estudos de relações estrutura-atividade quantitativas (QSAR) de bis-benzamidinas com atividade antifúngica

This paper describes 2D-QSAR and 3D-QSAR studies against Candida albicans and Cryptococcus neofarmans for a set of 20 bisbenzamidines. In the studies of 2D-QSAR with C. albicans it was obtained a correlation between log MIC-1 and lipolo component-Z (r² = 0.68; Q² = 0.51). In the case of C. neofarmans a correlation between log MIC-1 and lipolo component-Z and of Balaban index (r² = 0.85; Q² = 0.6) was obtained. 3D-QSAR studies using CoMFA showed that the steric fields contributed more to the predicted activities for Candida albicans (94.9%) and Cryptococcus neofarmans (97.9%).

Role of Halogen Bonds in Thyroid Hormone Receptor Selectivity: Pharmacophore-Based 3D-QSSR Studies

Most physiological effects of thyroid hormones are mediated by the two thyroid hormone receptor subtypes, TR alpha and TR beta. Several pharmacological effects mediated by TR beta might be beneficial in important medical conditions such as obesity, hypercholesterolemia and diabetes, and selective TR beta activation may elicit these effects while maintaining an acceptable safety profile, To understand the molecular determinants of affinity and subtype selectivity of TR ligands, we have successfully employed a ligand- and structure-guided pharmacophore-based approach to obtain the molecular alignment of a large series of thyromimetics. Statistically reliable three-dimensional quantitative structure-activity relationship (3D-QSAR) and three-dimensional quantitative structure-selectivity relationship (3D-QSSR) models were obtained using the comparative molecular field analysis (CoMFA) method, and the visual analyses of the contour maps drew attention to a number of possible opportunities for the development of analogs with improved affinity and selectivity. Furthermore, the 3D-QSSR analysis allowed the identification of a novel and previously unmentioned halogen bond, bringing new insights to the mechanism of activity and selectivity of thyromimetics.

Advanced QSAR Studies on PPAR delta Ligands Related to Metabolic Diseases

PPAR delta is a nuclear receptor that, when activated, regulates the metabolism of carbohydrates and lipids and is related to metabolic syndrome and type 2 diabetes. To understand the main interactions between ligands and PPAR delta, we have constructed 2D and 3D QSAR models and compared them with HOMO, LUMO and electrostatic potential maps of the compounds studied, as well as docking results. All QSAR models showed good statistical parameters and prediction outcomes. The QSAR models were used to predict the biological activity of an external test set, and the predicted values are in good agreement with the experimental results. Furthermore, we employed all maps to evaluate the possible interactions between the ligands and PPAR delta. These predictive QSAR models, along with the HOMO, LUMO and MEP maps, can provide insights into the structural and chemical properties that are needed in the design of new PPAR delta ligands that have improved biological activity and can be employed to treat metabolic diseases.

Diseño y Desarrollo de Drogas y Medicamentos Huérfanos

Nuestro grupo de investigación trabaja desde hace unos años en plantear soluciones a problemas de medicamentos con conflictos de disponibilidad. Esta situación generalmente está asocada a las enfermedades huérfanas (raras y olvidadas). Desde la investigación básica y aplicada se intenta lograr una interacción entre la Farmacoquímica y la Farmacoepidemiología, estrategia que justamente usa la industria farmacéutica cuando quiere desarrollar un nuevo medicamento. Esto nos ha permitido consolidar un grupo de investigación con la experiencia suficiente para encarar actividades de campo y experimentales. Para los primeros se utilizan métodos descriptivos cualitativos y cuantitativos, de observación y de intervención. Se trabaja en colaboración con los 14 Hospitales Públicos de la ciudad de Córdoba y con algunas clínicas privadas (6), con ANMAT y con las bases de datos de Agencias Oficiales de Medicamentos de países de referencia (EEUU y Europa), entre otros. A continuación, se analizan los factores que causan la “orfandad” de los medicamentos, la significancia clínica y el impacto sanitario, social y económico originado por su falta de disponibilidad. Respecto al diseño y desarrollo de nuevas entidades químicas farmacológicas, se decidió enfocar el estudio en fármacos para enfermedades huérfanas, principalmente las parasitarias (malaria, Chagas, leishmaniasis). Estas enfermedades son raras en países desarrollados y olvidadas o desatendidas en países pobres o menos desarrollados como el nuestro. En este sentido, se utilizan las metodologías propias de la Química Medicinal, como son el descubrimiento y optimización de prototipos. Se recurre a las estrategias más racionales actualmente utilizadas, como son el diseño y preparación de una quimioteca focalizada, su evaluación biológica, la identificación de líderes y su optimización utilizando la farmacomodulación, el diseño directo e indirecto asistido por computadoras y el estudio de las REA, QSAR y 3D-QSAR. La quimioteca actual está compuesta de derivados bencenosulfonilos de heterocíclicos, y cuenta actualmente con 105 compuestos, muchos de los cuales demostraron actividad antiparasitaria. La quimioteca se la diseñó utilizando la estrategia denominada "diseño de fármacos basada en fragmentos". La hipótesis es que tanto la fracción bencenosulfonilo como la heterocíclica han probado ser bioactivas. El objetivo general del proyecto es contribuir al mejoramiento de la salud humana, al avance científico y tecnológico y a la formación de recursos humanos por medio del diseño y desarrollo de Drogas y Medicamentos Huérfanos. Proponemos los siguientes objetivos específicos: 1) Incrementar el número de compuestos de la quimioteca de N-bencenosulfonilos de heterociclos. 2) Evaluar la actividad antiparasitaria in vitro. 3) Estudiar las propiedades del estado sólido de los derivados. 4) Usar la información adquirida en los puntos 1-3 para estudios de cribado virtual y mejorar la solubilidad de los compuestos seleccionados. 4) Continuar con los estudios farmacoepidmiológicos sobre medicamentos huérfanos o no disponibles en nuestro país, que retroalimenta y complementa los estudios farmacoquímicos. El proyecto presenta un impacto científico y socio-económico importante, ya que abarca varios aspectos de la problemática de medicamentos no disponibles o huérfanos, desde el diagnóstico de la situación en nuestro medio, pasando por la identificación de nuevas entidades químicas y el desarrollo de posibles soluciones para su transferencia a la industria. Esto se debe a su enfoque original (en academias) al plantearse la retroalimentación entre la farmacoquímica y la farmacoepidemiología. Esta experiencia es muy estimulante, el contacto con los profesionales del equipo de salud enriquece el intercambio de opiniones y la consolidación de proyectos multidisciplinarios, permitiendo abordar el problema de un modo integral.

Prediction of cross-recognition of peptide-HLA A2 by Melan-A-specific cytotoxic T lymphocytes using three-dimensional quantitative structure-activity relationships.

The cross-recognition of peptides by cytotoxic T lymphocytes is a key element in immunology and in particular in peptide based immunotherapy. Here we develop three-dimensional (3D) quantitative structure-activity relationships (QSARs) to predict cross-recognition by Melan-A-specific cytotoxic T lymphocytes of peptides bound to HLA A*0201 (hereafter referred to as HLA A2). First, we predict the structure of a set of self- and pathogen-derived peptides bound to HLA A2 using a previously developed ab initio structure prediction approach [Fagerberg et al., J. Mol. Biol., 521-46 (2006)]. Second, shape and electrostatic energy calculations are performed on a 3D grid to produce similarity matrices which are combined with a genetic neural network method [So et al., J. Med. Chem., 4347-59 (1997)] to generate 3D-QSAR models. The models are extensively validated using several different approaches. During the model generation, the leave-one-out cross-validated correlation coefficient (q (2)) is used as the fitness criterion and all obtained models are evaluated based on their q (2) values. Moreover, the best model obtained for a partitioned data set is evaluated by its correlation coefficient (r = 0.92 for the external test set). The physical relevance of all models is tested using a functional dependence analysis and the robustness of the models obtained for the entire data set is confirmed using y-randomization. Finally, the validated models are tested for their utility in the setting of rational peptide design: their ability to discriminate between peptides that only contain side chain substitutions in a single secondary anchor position is evaluated. In addition, the predicted cross-recognition of the mono-substituted peptides is confirmed experimentally in chromium-release assays. These results underline the utility of 3D-QSARs in peptide mimetic design and suggest that the properties of the unbound epitope are sufficient to capture most of the information to determine the cross-recognition.