Estudos de QSAR baseados em dados de atividade biológica obtidos por microcalorimetria: III interação de m-alcoxifenóis e p-hidroxibenzoatos de alquila com Escherichia coli

QSAR studies based on flow microcalorimetric bioassay data for interaction of homologous series of m-alkoxyphenols and p-hydroxybenzoates with E. coli cells were carried out applying factorial design. Results for both series showed a linear relationship between log(dose)max and log Po/w. Analysis of these data allows the identification of contributions toward the derived bioactivity from the parent structures (the molecule minus n-CH2 groups present in the side-chain) and the lipophilic groups, CH2. These results are discussed with respect to drug quantitative structure-relationship.

Validação lateral em relações quantitativas entre estrutura e atividade farmacológica, QSAR

The comparative QSAR is a tool for validating any statistical model that seems to be reasonable in describing an interaction between a bioactive new chemical entity, BIONCE, and the biological system. In order to deeper the understanding of the relationships and the meaning of parameters within the model it is necessary some kind of lateral validation. This validation can be accomplished by chemical procedures using physicochemical organic reactions and by means of biological systems. In this paper we review some of such comparisons and also present a lateral validation between the same set of antimicrobial hydrazides acting against Saccharomyces cerevisiae yeast and Escherichia coli bacterium cells. QSARs are presented to shed light in this important way of stating that the QSAR model is not the endpoint, but the beginning.

Seleção de variáveis em QSAR

The process of building mathematical models in quantitative structure-activity relationship (QSAR) studies is generally limited by the size of the dataset used to select variables from. For huge datasets, the task of selecting a given number of variables that produces the best linear model can be enormous, if not unfeasible. In this case, some methods can be used to separate good parameter combinations from the bad ones. In this paper three methodologies are analyzed: systematic search, genetic algorithm and chemometric methods. These methods have been exposed and discussed through practical examples.

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: a abordagem de Hansch

The Hansch Analysis, also known by QSAR-2D, is an extremely effective tool in the identification and/or improvement of the pharmacological or toxicological profile of xenobiotics. This article presents the theme didactically and with enough detail to clarify the conceptual basis of Hansch Analysis. Besides, it shows the application of the technique in measuring the influence of physicochemical properties on the biological activity of compounds with pharmacological interest.

Estudos de QSAR 3D para um conjunto de inibidores de butirilcolinesterase humana

Alzheimer's disease (AD) is considered the main cause of cognitive decline in adults. The available therapies for AD treatment seek to maintain the activity of cholinergic system through the inhibition of the enzyme acetylcholinesterase. However, butyrylcholinesterase (BuChE) can be considered an alternative target for AD treatment. Aiming at developing new BuChE inhibitors, robust QSAR 3D models with high predictive power were developed. The best model presents a good fit (r²=0.82, q²=0.76, with two PCs) and high predictive power (r²predict=0.88). Analysis of regression vector shows that steric properties have considerable importance to the inhibition of the BuChE.

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%).

Estudos de QSAR 2D baseados em descritores topológicos e fragmentos moleculares para uma série de derivados azólicos ativos contra Candida albicans

Azole derivatives are the main therapeutical resource against Candida albicans infection in immunocompromised patients. Nevertheless, the widespread use of azoles has led to reduced effectiveness and selection of resistant strains. In order to guide the development of novel antifungal drugs, 2D-QSAR models based on topological descriptors or molecular fragments were developed for a dataset of 74 molecules. The optimal fragment-based model (r² = 0.88, q² = 0.73 and r²pred = 0.62 with 6PCs) and descriptor-based model (r² = 0.82, q² = 0.79 and r²pred = 0.70 with 2 PCs), when analysed synergically, suggested that the triazolone ring and lipophilic properties are both important to antifungal activity.

Desenhos de estruturas químicas correlacionam-se com propriedades biológicas: MIA-QSAR

Descriptors in multivariate image analysis applied to quantitative structure-activity relationship (MIA-QSAR) are pixels of bidimensional images of chemical structures (drawings), which were used to model the trichomonicidal activities of a series of benzimidazole derivatives. The MIA-QSAR model showed good predictive ability, with r², q² and r val. ext.² of 0.853, 0.519 and 0.778, respectively, which are comparable to the best values obtained by CoMFA e CoMSIA for the same series. A MIA-based analysis was also performed by using images of alphabetic letters with the corresponding numeric ordering as dependent variables, but no correlation was found, supporting that MIA-QSAR is not arbitrary.

QSAR modeling: um novo pacote computacional open source para gerar e validar modelos QSAR

QSAR modeling is a novel computer program developed to generate and validate QSAR or QSPR (quantitative structure- activity or property relationships) models. With QSAR modeling, users can build partial least squares (PLS) regression models, perform variable selection with the ordered predictors selection (OPS) algorithm, and validate models by using y-randomization and leave-N-out cross validation. An additional new feature is outlier detection carried out by simultaneous comparison of sample leverage with the respective Studentized residuals. The program was developed using Java version 6, and runs on any operating system that supports Java Runtime Environment version 6. The use of the program is illustrated. This program is available for download at lqta.iqm.unicamp.br.

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.

TOP - um programa de cálculo de descritores topológicos para uso em correlações entre estrutura e atividade

A computational interface, using sybyl format as an input file, was created in order to calculate connectivity indexes. After generation and classification of all substructures, which derive from the molecular structure, this interface calculates all possible orders from zero up to the maximun number of bonds in the molecule. Other topological indexes such as Wiener and Schultz indexes can also be calculated.

Sobre o uso de métodos quimiométricos em química combinatória

Combinatorial chemistry has emerged as a tool to circumvent a major problem of pharmaceutical industries to discover new lead compounds. A rapid and massive evaluation of a myriad of newly synthesised compounds can be carried out. Combinatorial synthesis leads to high throughput screening en masse towards another myriad of biological targets. The design of a set of compounds based upon combinatorial chemistry may be envisaged by using of QSPR-SIMCA and QSAR-SIMCA as tools for classification purposes. This work deals with the definition and establishment of a spanned substituent space (SSS) that reduces the analogue numbers with no exclusion of global content. The chemical diversity may be set properly within a specified pharmacological field. This allows a better use of its potentiality without loosing information.

Proposição, validação e análise dos modelos que correlacionam estrutura química e atividade biológica

The present paper aims to bring under discussion some theoretical and practical aspects about the proposition, validation and analysis of QSAR models based on multiple linear regression. A comprehensive approach for the derivation of extrathermodynamic equations is reviewed. Some examples of QSAR models published in the literature are analyzed and criticized.

Estrutura e propriedades de elipticinas

The ellipticines constitute a broad class of molecules with antitumor activity. In the present work we analyzed the structure and properties of a series of ellipticine derivatives in the gas phase and in solution using quantum mechanical and Monte Carlo methods. The results showed a good correlation between the solvation energies in water obtained with the continuum model and the Monte Carlo simulation. Molecular descriptors were considered in the development of QSAR models using the DNA association constant (log Kapp) as biological data. The results showed that the DNA binding is dominated by electronic parameters, with small contributions from the molecular volume and area.