RESUMO
The aim of this work was the foodinformatic (chemoinformatic) modeling of volatile organic compounds (VOCs) of different samples of peppers based on a quantitative structure-property relationship (QSPR) for the retention indices of 273 identified compounds. The experimental retention indices were measured by means of comprehensive two-dimensional gas chromatography combined with quadrupole-mass spectrometry (GC × GC/qMS) using the BPX5 and BP20 column coupled system. All the VOCs were represented by means of both conformation-independent molecular descriptors and molecular fingerprints calculated in the Dragon and PaDEL-Descriptor software. The dataset was divided into training, validation and test sets of molecules according to the Balanced Subsets Method (BSM). Subsequently, the V-WSP unsupervised variable reduction method was used to reduce the presence of multicollinearity, redundancy, and noise in the initial pool of 4,336 molecular descriptors and fingerprints. Using this method, a reduced pool of 1,664 was submitted to the supervised selection by means of the replacement method (RM) variable subset selection in order to define a four-descriptor model. The quality of the model was measured by means of the coefficient of determination and the root-mean-square deviation in fitting ( R train 2 = 0 . 879 and RMSD train = 72.1 ), validation ( R val 2 = 0 . 832 and RMSD val = 91.7 ), and prediction ( R test 2 = 0 . 915 and RMSD test = 55.4 ). The negligible differences among the parameters in the three sets indicate a stable and predictive QSPR model. This quantitative structure-activity relationship was developed keeping in mind the five principles defined by the Organization for Economic Co-operation and Development (OECD) to make it applicable. PRACTICAL APPLICATION: This predictive mathematical model developed from the retention indices of 273 volatile organic compounds (VOCs) detected in pepper samples could be useful for chromatographers working on the identification of other common VOCs in peppers or other foods by means of comprehensive two-dimensional gas chromatography combined with quadrupole-mass spectrometry (GC × GC/qMS) using a bi-dimensional stationary phase coupled system (BPX5 and BP20).
Assuntos
Capsicum/química , Compostos Orgânicos Voláteis/análise , Compostos Orgânicos Voláteis/química , Cromatografia Gasosa-Espectrometria de Massas , Relação Quantitativa Estrutura-AtividadeRESUMO
We predict the soil sorption coefficient for a heterogeneous set of 643 organic non-ionic compounds by means of Quantitative Structure-Property Relationships (QSPR). A conformation-independent representation of the chemical structure is established. The 17,538 molecular descriptors derived with PaDEL and EPI Suite softwares are simultaneously analyzed through linear regressions obtained with the Replacement Method variable subset selection technique. The best predictive three-descriptors QSPR is developed on a reduced training set of 93 chemicals, having an acceptable predictive capability on 550 test set compounds. We also establish a model with a single optimal descriptor derived from CORAL freeware. The present approach compares fairly well with a previously reported one that uses Dragon descriptors.
Assuntos
Praguicidas/química , Poluentes do Solo/química , Solo/química , Adsorção , Biodegradação Ambiental , Formaldeído/química , Modelos Químicos , Conformação Molecular , Relação Quantitativa Estrutura-Atividade , Medição de Risco , SolubilidadeRESUMO
Quantitative structure-property relationships (QSPRs) were applied to the aminograms obtained by HPLC in our laboratories for Torrontés and Merlot wines. Dragon theoretical descriptors were derived for a set of optimized amino acid structures with the purpose of establishing QSPR models. The statistical Replacement Method was used for designing the best multi-parametric linear regression models, which included structural features selected from a pool containing 1497 constitutional, topological, geometrical or electronic molecular descriptors. Predicted QSPR results were in good agreement with experimental amino acid profiles. The developed QSPR approach showed to be of practical value for distinguishing each wine varietal, and for calculating experimentally non-available amino acid concentrations of Torrontés and Merlot wines. It was also useful for assessing wine authenticity; the models were especially suitable for Merlot and Torrontés wines.
Assuntos
Aminoácidos/química , Vinho/análise , Biomarcadores/química , Relação Quantitativa Estrutura-Atividade , Vinho/classificaçãoRESUMO
In our continuing efforts to find out acceptable Absorption, Distribution, Metabolization, Elimination and Toxicity (ADMET) properties of organic compounds, we establish linear QSAR models for the carcinogenic potential prediction of 1464 compounds taken from the "Galvez data set", that include many marketed drugs. More than a thousand of geometry-independent molecular descriptors are simultaneously analyzed, obtained with the softwares E-Dragon and Recon. The variable subset selection method employed is the Replacement Method, and also the improved version Enhanced Replacement Method. The established models are properly validated through an external test set of compounds, and by means of the Leave-Group-Out Cross Validation method. In addition, we apply the Y-Randomization strategy and analyze the Applicability Domain of the developed model. Finally, we compare the results obtained in present study with the previous ones from the literature. The novelty of present work relies on the development of an alternative predictive structure-carcinogenicity relationship in a large heterogeneous set of organic compounds, by only using a reduced number of geometry independent molecular descriptors.
Assuntos
Carcinógenos/toxicidade , Modelos Moleculares , Compostos Orgânicos/efeitos adversos , Testes de Carcinogenicidade , Carcinógenos/química , Humanos , Modelos Lineares , Compostos Orgânicos/química , Relação Quantitativa Estrutura-Atividade , SoftwareRESUMO
We describe the opportunities posed by computer-assisted drug design in the light of two aspects of the current drug discovery scenario: the decline of innovation due to high attrition rates at clinical stage of development and the combinatorial explosion emerging from exponential growth of feasible small molecules and genome and proteome exploration. We present an overview of recent reports from our group in the field of rational drug development, by using topological descriptors (either alone, or in combination with different 3D approaches) and a diversity of modeling techniques such as Linear Discriminant Analysis and the Replacement Method. Modeling efforts aimed at the integrated prediction of several significant molecular properties in the field of drug discovery, such as pharmacological activity, aqueous solubility, human intestinal permeability and affinity to P-glycoprotein (ABCB1, MDR1) are reviewed. The suitability of conformation-independent descriptors to explore large chemical repositories is highlighted, as well as the opportunities posed by in silico guided drug repurposing.
Assuntos
Desenho Assistido por Computador , Desenho de Fármacos , Preparações Farmacêuticas/química , Animais , Humanos , Modelos Moleculares , Conformação Molecular , Farmacologia , Relação Quantitativa Estrutura-AtividadeRESUMO
A theoretical study on the series of compounds "PhSeX", where Ph = phenyl, Se = selenium and X = Cl, Br, I, CN or SCN, is reported and compared with previously reported experimental data. The molecular geometry for these PhSeX compounds was studied at the DFT/B3LYP level of calculation by means of the 6-311G(d,p) basis set. The equilibrium structures of the molecules were dependent on the method employed to compare the known solid structures. A topological study of the calculated PhSeX species, based on the AIM theory, was carried out to gain a deeper insight into the bonding nature and to find an explanation for the structural diversity exhibited by these PhSeX compounds. The results reported herein illustrate the subtle differences in the solid-state structures of PhSeX compounds.
Assuntos
Compostos Organosselênicos/química , Fenóis/química , Halogênios/química , Modelos Teóricos , Estrutura MolecularRESUMO
The metabolic profile of Odontesthes bonariensis and its global response to the insecticide cypermethrin were studied using HPLC-MS-based metabolomics. Three experiments using either juveniles or adults of O. bonariensis were performed by exposing fish (6, 24, or 96 h) to sublethal concentrations of cypermethrin (5 or 10 µg/L). Metabolic profiling was performed on either whole bile or aqueous and organic extracts. Chromatography was performed using a C18 column and an ACN/H2O mobile phase. Electrospray ionization (ESI) and atmospheric pressure chemical ionization (APCI) interfaces were used in positive and negative modes. Full scan MS data were processed using the XCMS software, log-transformed, and analyzed using either regression analysis or principal component analysis (PCA). The highest amount of information (1163 peaks) was yielded by analyzing the whole bile with the ESIâ» interface. Complementary information, useful for metabolite confirmation, was obtained from the aqueous and organic extracts and using the ESI⺠and APCI interfaces. The bile metabolic profile of O. bonariensis was characterized by some abundant metabolite ions corresponding with taurine conjugated bile acids, which were useful as reference peaks. A characteristic global metabolic response to cypermethrin was identified in the bile of O. bonariensis. A ten-fold or higher variation in abundance was observed in the whole bile of exposed fish for a small group of peaks (32), and these peaks corresponded to an even smaller number of metabolites (nineteen). Both regression analysis and PCA were useful in identifying those peaks, better explaining differences between exposed and control groups, but slight differences were suggested by each of those methods. Using unsupervised PCA scores, we were able to distinguish organisms from each treatment on the basis of the metabolic changes induced by the cypermethrin, this variability being explained mainly by only one principal component (PC3, 17.7 percent total variance). Two cypermethrin metabolites were identified as major contributors within the augmented peaks: the known glucuronide of 4'-hydroxy-cypermethrin and the sulfate of 4'-hydroxycypermethrin, not previously reported in fish bile. The HPLC-MS-based metabolomic approach demonstrated to be a powerful ecotoxicological tool for identifying biological responses to pollutants, discovering new metabolic pathways and proposing specific biomarkers using non model organisms.
Assuntos
Bile/metabolismo , Inseticidas/toxicidade , Metaboloma/fisiologia , Piretrinas/toxicidade , Smegmamorpha/metabolismo , Animais , Biomarcadores/metabolismo , Cromatografia Líquida de Alta Pressão , Metabolômica , Análise de Componente Principal , Poluentes Químicos da Água/toxicidadeRESUMO
Selective inhibitors of target serine proteinases have a potential therapeutic role for the treatment of various inflammatory and related diseases. We develop a comparative quantitative structure-activity relationships based analysis on compounds embodying the 1,2,5-thiadiazolidin-3-one 1,1-dioxide scaffold. By means of classical Molecular Dynamics we obtain the conformation of each lowest-energy molecular structure from which we derive more than a thousand of structural descriptors necessary for building predictive QSAR models. We resort to two different modeling approaches with the purpose of testing the consistency of our results: (a) multivariable linear regressions based on the replacement method and forward stepwise regression, and (b) the calculation of flexible descriptors with the CORAL program. All the models are properly validated by means of standard procedures. The resulting QSAR models are supposed to be of great utility for the rational search and design (including synthesis and/or in vitro biochemical studies) of new effective non-peptidyl inhibitors of serine proteinases.
Assuntos
Óxidos S-Cíclicos/química , Óxidos S-Cíclicos/farmacologia , Serina Proteases/química , Serina Proteases/metabolismo , Inibidores de Serina Proteinase/química , Inibidores de Serina Proteinase/farmacologia , Tiazóis/química , Tiazóis/farmacologia , Desenho de Fármacos , Humanos , Modelos Lineares , Conformação Molecular , Simulação de Dinâmica Molecular , Relação Quantitativa Estrutura-AtividadeRESUMO
A thermodynamic study of the inclusion process between 2-chlorobenzophenone (2ClBP) and cyclomaltoheptaose (ß-cyclodextrin, ß-CD) was performed using UV-vis spectroscopy, reversed-phase liquid chromatography (RP-HPLC), and molecular modeling (PM6). Spectrophotometric measurements in aqueous solutions were performed at different temperatures. The stoichiometry of the complex is 1:1 and its apparent formation constant (K(c)) is 3846M(-1) at 30°C. Temperature dependence of K(c) values revealed that both enthalpy (ΔH°=-10.58kJ/mol) and entropy changes (ΔS°=33.76J/Kmol) are favorable for the inclusion process in an aqueous medium. Encapsulation was also investigated using RP-HPLC (C18 column) with different mobile-phase compositions, to which ß-CD was added. The apparent formation constants in MeOH-H(2)O (K(F)) were dependent of the proportion of the mobile phase employed (50:50, 55:45, 60:40 and 65:35, v/v). The K(F) values were 419M(-1) (50% MeOH) and 166M(-1) (65% MeOH) at 30°C. The thermodynamic parameters of the complex in an aqueous MeOH medium indicated that this process is largely driven by enthalpy change (ΔH°=-27.25kJ/mol and ΔS°=-45.12J/Kmol). The results of the study carried out with the PM6 semiempirical method showed that the energetically most favorable structure for the formation of the complex is the 'head up' orientation.
Assuntos
Benzofenonas/química , Solventes/química , beta-Ciclodextrinas/química , Cromatografia Líquida de Alta Pressão , Modelos Químicos , TemperaturaRESUMO
The selection of an optimal set of molecular descriptors from a much greater pool of such regression variables is a crucial step in the development of QSAR and QSPR models. The aim of this work is to further improve this important selection process. For this reason three different alternatives for the initial steps of our recently developed enhanced replacement method (ERM) and replacement method (RM) are proposed. These approaches had previously proven to yield near optimal results with a much smaller number of linear regressions than the full search. The algorithms were tested on four different experimental data sets, formed by collections of 116, 200, 78, and 100 experimental records from different compounds and 1268, 1338, 1187, and 1306 molecular descriptors, respectively. The comparisons showed that one of the new alternatives further improves the ERM, which has shown to be superior to genetic algorithms for the selection of an optimal set of molecular descriptors from a much greater pool. The new proposed alternative also improves the simpler and the lower computational demand algorithm RM.