Interactions of chitosan/genipin hydrogels during drug delivery: a QSPR approach

A hydrogel comprised of chitosan crosslinked using the low-toxicity crosslinker genipin was prepared, and the absorption of glibenclamide by the hydrogel was investigated. Optimized structures and their molecular electrostatic potentials were calculated using the AM1 method, and the results were used to evaluate the molecular interactions between the three compounds. The quantitative structure-property relationship model was also used to estimate the activity of the chemicals on the basis their molecular structures. In addition, theoretical Fourier transform infrared spectra were calculated to analyze the intermolecular interactions in the proposed system. Finally, the hydrophilicity of the hydrogel and its influence on the absorption process were also estimated.

PREDICTING THE BOILING POINT OF PCDD/Fs BY THE QSPR METHOD BASED ON THE MOLECULAR DISTANCE-EDGE VECTOR INDEX

The quantitative structure property relationship (QSPR) for the boiling point (Tb) of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs) was investigated. The molecular distance-edge vector (MDEV) index was used as the structural descriptor. The quantitative relationship between the MDEV index and Tb was modeled by using multivariate linear regression (MLR) and artificial neural network (ANN), respectively. Leave-one-out cross validation and external validation were carried out to assess the prediction performance of the models developed. For the MLR method, the prediction root mean square relative error (RMSRE) of leave-one-out cross validation and external validation was 1.77 and 1.23, respectively. For the ANN method, the prediction RMSRE of leave-one-out cross validation and external validation was 1.65 and 1.16, respectively. A quantitative relationship between the MDEV index and Tb of PCDD/Fs was demonstrated. Both MLR and ANN are practicable for modeling this relationship. The MLR model and ANN model developed can be used to predict the Tb of PCDD/Fs. Thus, the Tb of each PCDD/F was predicted by the developed models.

Anti-leishmanial and structure-activity relationship of ring substituted 3-phenyl-1-(1,4-di-N-oxide quinoxalin-2-yl)-2-propen-1-one derivatives

A series of ring substituted 3-phenyl-1-(1,4-di-N-oxide quinoxalin-2-yl)-2-propen-1-one derivatives were synthesized and tested for in vitro leishmanicidal activity against amastigotes of Leishmania amazonensis in axenical cultures and murine infected macrophages. Structure-activity relationships demonstrated the importance of a radical methoxy at position R3', R4' and R5'. (2E)-3-(3,4,5-trimethoxy-phenyl)-1-(3,6,7-trimethyl-1,4-dioxy-quinoxalin-2-yl)-propenone was the most active. Cytotoxicity on macrophages revealed that this product was almost six times more active than toxic.

Quantitative structure-retention relationships analysis of retention index of essential oils

Genetic algorithm and multiple linear regression (GA-MLR), partial least square (GA-PLS), kernel PLS (GA-KPLS) and Levenberg-Marquardt artificial neural network (L-M ANN) techniques were used to investigate the correlation between retention index (RI) and descriptors for 116 diverse compounds in essential oils of six Stachys species. The correlation coefficient LGO-CV (Q²) between experimental and predicted RI for test set by GA-MLR, GA-PLS, GA-KPLS and L-M ANN was 0.886, 0.912, 0.937 and 0.964, respectively. This is the first research on the QSRR of the essential oil compounds against the RI using the GA-KPLS and L-M ANN.

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.

Application of GA-PLS and GA-KPLS calculations for the prediction of the retention indices of essential oils

Genetic algorithm and partial least square (GA-PLS) and kernel PLS (GA-KPLS) techniques were used to investigate the correlation between retention indices (RI) and descriptors for 117 diverse compounds in essential oils from 5 Pimpinella species gathered from central Turkey which were obtained by gas chromatography and gas chromatography-mass spectrometry. The square correlation coefficient leave-group-out cross validation (LGO-CV) (Q²) between experimental and predicted RI for training set by GA-PLS and GA-KPLS was 0.940 and 0.963, respectively. This indicates that GA-KPLS can be used as an alternative modeling tool for quantitative structure-retention relationship (QSRR) studies.

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.

Genetic relationship of diarrheagenic Escherichia coli pathotypes among the enteropathogenic Escherichia coli O serogroup

The genetic relationship among the Escherichia coli pathotypes was investigated. We used random amplified polymorphic DNA (RAPD) data for constructing a dendrogram of 73 strains of diarrheagenic E. coli. A phylogenetic tree encompassing 15 serotypes from different pathotypes was constructed using multilocus sequence typing data. Phylogram clusters were used for validating RAPD data on the clonality of enteropathogenic E. coli (EPEC) O serogroup strains. Both analyses showed very similar topologies, characterized by the presence of two major groups: group A includes EPEC H6 and H34 strains and group B contains the other EPEC strains plus all serotypes belonging to atypical EPEC, enteroaggregative E. coli (EAEC) and enterohemorrhagic E. coli (EHEC). These results confirm the existence of two evolutionary divergent groups in EPEC: one is genetically and serologically very homogeneous whereas the other harbors EPEC and non-EPEC serotypes. The same situation was found for EAEC and EHEC.

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.

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.

The evolution of purinergic receptors involved in recognition of a blood meal by hematophagous insects

Many blood feeders use adenine nucleotides as cues for locating blood meal. Structure-activity relationship of adenine nucleotides as phagostimulants varies between closely-related species of blood feeders. It is suggested that a preexisting diverse pool of nucleotide-binding proteins present in all living cells, serves as a source of receptor proteins for the gustatory receptors involved in blood detection. It is proposed that the selection of any such nucleotide-binding protein is random.

Molecular Modeling Approaches for Determining Gene Function: application to a Putative Poly-A Binding Protein from Leishmania amazonensis (LaPABP)

The great expansion in the number of genome sequencing projects has revealed the importance of computational methods to speed up the characterization of unknown genes. These studies have been improved by the use of three dimensional information from the predicted proteins generated by molecular modeling techniques. In this work, we disclose the structure-function relationship of a gene product from Leishmania amazonensis by applying molecular modeling and bioinformatics techniques. The analyzed sequence encodes a 159 aminoacids polypeptide (estimated 18 kDa) and was denoted LaPABP for its high homology with poly-A binding proteins from trypanosomatids. The domain structure, clustering analysis and a three dimensional model of LaPABP, basically obtained by homology modeling on the structure of the human poly-A binding protein, are described. Based on the analysis of the electrostatic potential mapped on the model's surface and conservation of intramolecular contacts responsible for folding stabilization we hypothesize that this protein may have less avidity to RNA than it's L. major counterpart but still account for a significant functional activity in the parasite. The model obtained will help in the design of mutagenesis experiments aimed to elucidate the mechanism of gene expression in trypanosomatids and serve as a starting point for its exploration as a potential source of targets for a rational chemotherapy.

Computational drug design strategies applied to the modelling of human immunodeficiency virus-1 reverse transcriptase inhibitors

Reverse transcriptase (RT) is a multifunctional enzyme in the human immunodeficiency virus (HIV)-1 life cycle and represents a primary target for drug discovery efforts against HIV-1 infection. Two classes of RT inhibitors, the nucleoside RT inhibitors (NRTIs) and the nonnucleoside transcriptase inhibitors are prominently used in the highly active antiretroviral therapy in combination with other anti-HIV drugs. However, the rapid emergence of drug-resistant viral strains has limited the successful rate of the anti-HIV agents. Computational methods are a significant part of the drug design process and indispensable to study drug resistance. In this review, recent advances in computer-aided drug design for the rational design of new compounds against HIV-1 RT using methods such as molecular docking, molecular dynamics, free energy calculations, quantitative structure-activity relationships, pharmacophore modelling and absorption, distribution, metabolism, excretion and toxicity prediction are discussed. Successful applications of these methodologies are also highlighted.

Ambergris: perfume e síntese

Rules for the occurence of the ambergris odor is presented and discussed in terms of the relationship between chemical structure and odor. A general overview of the major approaches in the synthesis of Ambrox® , the key ambergris-type compound, is also presented.

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.