Quantitative structure-activity relationships and the prediction of MHC supermotifs

The underlying assumption in quantitative structure–activity relationship (QSAR) methodology is that related chemical structures exhibit related biological activities. We review here two QSAR methods in terms of their applicability for human MHC supermotif definition. Supermotifs are motifs that characterise binding to more than one allele. Supermotif definition is the initial in silico step of epitope-based vaccine design. The first QSAR method we review here—the additive method—is based on the assumption that the binding affinity of a peptide depends on contributions from both amino acids and the interactions between them. The second method is a 3D-QSAR method: comparative molecular similarity indices analysis (CoMSIA). Both methods were applied to 771 peptides binding to 9 HLA alleles. Five of the alleles (A*0201, A* 0202, A*0203, A*0206 and A*6802) belong to the HLA-A2 superfamily and the other four (A*0301, A*1101, A*3101 and A*6801) to the HLA-A3 superfamily. For each superfamily, supermotifs defined by the two QSAR methods agree closely and are supported by many experimental data.

Development, validation and uncertainty analysis of quantitative structure and activity relationship models for Log P of disinfection by -products

Hydrophobicity as measured by Log P is an important molecular property related to toxicity and carcinogenicity. With increasing public health concerns for the effects of Disinfection By-Products (DBPs), there are considerable benefits in developing Quantitative Structure and Activity Relationship (QSAR) models capable of accurately predicting Log P. In this research, Log P values of 173 DBP compounds in 6 functional classes were used to develop QSAR models, by applying 3 molecular descriptors, namely, Energy of the Lowest Unoccupied Molecular Orbital (ELUMO), Number of Chlorine (NCl) and Number of Carbon (NC) by Multiple Linear Regression (MLR) analysis. The QSAR models developed were validated based on the Organization for Economic Co-operation and Development (OECD) principles. The model Applicability Domain (AD) and mechanistic interpretation were explored. Considering the very complex nature of DBPs, the established QSAR models performed very well with respect to goodness-of-fit, robustness and predictability. The predicted values of Log P of DBPs by the QSAR models were found to be significant with a correlation coefficient R2 from 81% to 98%. The Leverage Approach by Williams Plot was applied to detect and remove outliers, consequently increasing R 2 by approximately 2% to 13% for different DBP classes. The developed QSAR models were statistically validated for their predictive power by the Leave-One-Out (LOO) and Leave-Many-Out (LMO) cross validation methods. Finally, Monte Carlo simulation was used to assess the variations and inherent uncertainties in the QSAR models of Log P and determine the most influential parameters in connection with Log P prediction. The developed QSAR models in this dissertation will have a broad applicability domain because the research data set covered six out of eight common DBP classes, including halogenated alkane, halogenated alkene, halogenated aromatic, halogenated aldehyde, halogenated ketone, and halogenated carboxylic acid, which have been brought to the attention of regulatory agencies in recent years. Furthermore, the QSAR models are suitable to be used for prediction of similar DBP compounds within the same applicability domain. The selection and integration of various methodologies developed in this research may also benefit future research in similar fields.

Chlorine contribution to quantitative structure and activity relationship models of disinfection by -products' quantum chemical descriptors and toxicities

Quantitative Structure-Activity Relationship (QSAR) has been applied extensively in predicting toxicity of Disinfection By-Products (DBPs) in drinking water. Among many toxicological properties, acute and chronic toxicities of DBPs have been widely used in health risk assessment of DBPs. These toxicities are correlated with molecular properties, which are usually correlated with molecular descriptors. The primary goals of this thesis are: (1) to investigate the effects of molecular descriptors (e.g., chlorine number) on molecular properties such as energy of the lowest unoccupied molecular orbital (E LUMO) via QSAR modelling and analysis; (2) to validate the models by using internal and external cross-validation techniques; (3) to quantify the model uncertainties through Taylor and Monte Carlo Simulation. One of the very important ways to predict molecular properties such as ELUMO is using QSAR analysis. In this study, number of chlorine (NCl ) and number of carbon (NC) as well as energy of the highest occupied molecular orbital (EHOMO) are used as molecular descriptors. There are typically three approaches used in QSAR model development: (1) Linear or Multi-linear Regression (MLR); (2) Partial Least Squares (PLS); and (3) Principle Component Regression (PCR). In QSAR analysis, a very critical step is model validation after QSAR models are established and before applying them to toxicity prediction. The DBPs to be studied include five chemical classes: chlorinated alkanes, alkenes, and aromatics. In addition, validated QSARs are developed to describe the toxicity of selected groups (i.e., chloro-alkane and aromatic compounds with a nitro- or cyano group) of DBP chemicals to three types of organisms (e.g., Fish, T. pyriformis, and P.pyosphoreum) based on experimental toxicity data from the literature. The results show that: (1) QSAR models to predict molecular property built by MLR, PLS or PCR can be used either to select valid data points or to eliminate outliers; (2) The Leave-One-Out Cross-Validation procedure by itself is not enough to give a reliable representation of the predictive ability of the QSAR models, however, Leave-Many-Out/K-fold cross-validation and external validation can be applied together to achieve more reliable results; (3) E LUMO are shown to correlate highly with the NCl for several classes of DBPs; and (4) According to uncertainty analysis using Taylor method, the uncertainty of QSAR models is contributed mostly from NCl for all DBP classes.

Chlorine Contribution to Quantitative Structure and Activity Relationship Models of Disinfection By-Products' Quantum Chemical Descriptors and Toxicities

Quantitative Structure-Activity Relationship (QSAR) has been applied extensively in predicting toxicity of Disinfection By-Products (DBPs) in drinking water. Among many toxicological properties, acute and chronic toxicities of DBPs have been widely used in health risk assessment of DBPs. These toxicities are correlated with molecular properties, which are usually correlated with molecular descriptors. The primary goals of this thesis are: 1) to investigate the effects of molecular descriptors (e.g., chlorine number) on molecular properties such as energy of the lowest unoccupied molecular orbital (ELUMO) via QSAR modelling and analysis; 2) to validate the models by using internal and external cross-validation techniques; 3) to quantify the model uncertainties through Taylor and Monte Carlo Simulation. One of the very important ways to predict molecular properties such as ELUMO is using QSAR analysis. In this study, number of chlorine (NCl) and number of carbon (NC) as well as energy of the highest occupied molecular orbital (EHOMO) are used as molecular descriptors. There are typically three approaches used in QSAR model development: 1) Linear or Multi-linear Regression (MLR); 2) Partial Least Squares (PLS); and 3) Principle Component Regression (PCR). In QSAR analysis, a very critical step is model validation after QSAR models are established and before applying them to toxicity prediction. The DBPs to be studied include five chemical classes: chlorinated alkanes, alkenes, and aromatics. In addition, validated QSARs are developed to describe the toxicity of selected groups (i.e., chloro-alkane and aromatic compounds with a nitro- or cyano group) of DBP chemicals to three types of organisms (e.g., Fish, T. pyriformis, and P.pyosphoreum) based on experimental toxicity data from the literature. The results show that: 1) QSAR models to predict molecular property built by MLR, PLS or PCR can be used either to select valid data points or to eliminate outliers; 2) The Leave-One-Out Cross-Validation procedure by itself is not enough to give a reliable representation of the predictive ability of the QSAR models, however, Leave-Many-Out/K-fold cross-validation and external validation can be applied together to achieve more reliable results; 3) ELUMO are shown to correlate highly with the NCl for several classes of DBPs; and 4) According to uncertainty analysis using Taylor method, the uncertainty of QSAR models is contributed mostly from NCl for all DBP classes.

Développement de modèles prédictifs de la toxicocinétique de substances organiques

Les modèles pharmacocinétiques à base physiologique (PBPK) permettent de simuler la dose interne de substances chimiques sur la base de paramètres spécifiques à l’espèce et à la substance. Les modèles de relation quantitative structure-propriété (QSPR) existants permettent d’estimer les paramètres spécifiques au produit (coefficients de partage (PC) et constantes de métabolisme) mais leur domaine d’application est limité par leur manque de considération de la variabilité de leurs paramètres d’entrée ainsi que par leur domaine d’application restreint (c. à d., substances contenant CH3, CH2, CH, C, C=C, H, Cl, F, Br, cycle benzénique et H sur le cycle benzénique). L’objectif de cette étude est de développer de nouvelles connaissances et des outils afin d’élargir le domaine d’application des modèles QSPR-PBPK pour prédire la toxicocinétique de substances organiques inhalées chez l’humain. D’abord, un algorithme mécaniste unifié a été développé à partir de modèles existants pour prédire les PC de 142 médicaments et polluants environnementaux aux niveaux macro (tissu et sang) et micro (cellule et fluides biologiques) à partir de la composition du tissu et du sang et de propriétés physicochimiques. L’algorithme résultant a été appliqué pour prédire les PC tissu:sang, tissu:plasma et tissu:air du muscle (n = 174), du foie (n = 139) et du tissu adipeux (n = 141) du rat pour des médicaments acides, basiques et neutres ainsi que pour des cétones, esters d’acétate, éthers, alcools, hydrocarbures aliphatiques et aromatiques. Un modèle de relation quantitative propriété-propriété (QPPR) a été développé pour la clairance intrinsèque (CLint) in vivo (calculée comme le ratio du Vmax (μmol/h/kg poids de rat) sur le Km (μM)), de substrats du CYP2E1 (n = 26) en fonction du PC n octanol:eau, du PC sang:eau et du potentiel d’ionisation). Les prédictions du QPPR, représentées par les limites inférieures et supérieures de l’intervalle de confiance à 95% à la moyenne, furent ensuite intégrées dans un modèle PBPK humain. Subséquemment, l’algorithme de PC et le QPPR pour la CLint furent intégrés avec des modèles QSPR pour les PC hémoglobine:eau et huile:air pour simuler la pharmacocinétique et la dosimétrie cellulaire d’inhalation de composés organiques volatiles (COV) (benzène, 1,2-dichloroéthane, dichlorométhane, m-xylène, toluène, styrène, 1,1,1 trichloroéthane et 1,2,4 trimethylbenzène) avec un modèle PBPK chez le rat. Finalement, la variabilité de paramètres de composition des tissus et du sang de l’algorithme pour les PC tissu:air chez le rat et sang:air chez l’humain a été caractérisée par des simulations Monte Carlo par chaîne de Markov (MCMC). Les distributions résultantes ont été utilisées pour conduire des simulations Monte Carlo pour prédire des PC tissu:sang et sang:air. Les distributions de PC, avec celles des paramètres physiologiques et du contenu en cytochrome P450 CYP2E1, ont été incorporées dans un modèle PBPK pour caractériser la variabilité de la toxicocinétique sanguine de quatre COV (benzène, chloroforme, styrène et trichloroéthylène) par simulation Monte Carlo. Globalement, les approches quantitatives mises en œuvre pour les PC et la CLint dans cette étude ont permis l’utilisation de descripteurs moléculaires génériques plutôt que de fragments moléculaires spécifiques pour prédire la pharmacocinétique de substances organiques chez l’humain. La présente étude a, pour la première fois, caractérisé la variabilité des paramètres biologiques des algorithmes de PC pour étendre l’aptitude des modèles PBPK à prédire les distributions, pour la population, de doses internes de substances organiques avant de faire des tests chez l’animal ou l’humain.

Relation between antioxidant activity and electronic structure of Phenols

We describe a new physicochemical descriptor of the antioxidant activity of phenols, the energy difference between the two highest occupied molecular orbitals, which we believe will improve quantitative structure-activity relationship studies about these compounds. (C) 2003 Wiley Periodicals, Inc.

ScPdZn and ScPtZn with YAlGe type structure: group-subgroup relation and 45Sc solid state NMR spectroscopy

The intermetallic compounds ScPdZn and ScPtZn were prepared from the elements by high-frequency melting in sealed tantalum ampoules. Both structures were refined from single crystal X-ray diffractometer data: YAlGe type, Cmcm, a = 429.53(8), b = 907.7(1), c = 527.86(1) pm, wR2 = 0.0375, 231 F2 values, for ScPdZn and a = 425.3(1), b = 918.4(2), c = 523.3(1) pm, wR2 = 0.0399, 213 F2 values for ScPtZn with 14 variables per refinement. The structures are orthorhombically distorted variants of the AlB2 type. The scandium and palladium (platinum atoms) build up ordered networks Sc3Pd3 and Sc3Pt3 (boron networks) which are slightly shifted with respect to each other. These networks are penetrated by chains of zinc atoms (262 pm in ScPtZn) which correspond to the aluminum positions, i.e. Zn(ScPd) and Zn(ScPt). The corresponding group-subgroup scheme and the differences in chemical bonding with respect to other AlB2-derived REPdZn and REPtZn compounds are discussed. 45Sc solid state NMR spectra confirm the single crystallographic scandium sites. From electronic band structure calculations the two compounds are found metallic with free electron like behavior at the Fermi level. A larger cohesive energy for ScPtZn suggests a more strongly bonded intermetallic than ScPdZn. Electron localization and overlap population analyses identify the largest bonding for scandium with the transition metal (Pd, Pt).

Synthesis and structure-activity relationship studies of CD4 down-modulating cyclotriazadisulfonamide (CADA) analogues

HIV attachment via the CD4 receptor is an important target for developing novel approaches to HIV chemotherapy. Cyclotriazadisulfonamide (CADA) inhibits HIV at submicromolar levels by specifically down-modulating cell-surface and intracellular CD4. An effective five-step synthesis of CADA in 30% overall yield is reported. This synthesis has also been modified to produce more than 50 analogues. Many tail-group analogues have been made by removing the benzyl tail of CADA and replacing it with various alkyl, acyl, alkoxycarbonyl and aminocarbonyl substituents. A series of sidearm analogues, including two unsymmetrical compounds, have also been prepared by modifying the CADA synthesis, replacing the toluenesulfonyl sidearms with other sulfonyl groups. Testing 30 of these compounds in MT-4 cells shows a wide range of CD4 down-modulation potency, which correlates with ability to inhibit HIV-1. Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were constructed using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) approaches. The X-ray crystal structures of four compounds, including CADA, show the same major conformation of the central 12-membered ring. The solid-state structure of CADA was energy minimized and used to generate the remaining 29 structures, which were similarly minimized and aligned to produce the 3D-QSAR models. Both models indicate that steric bulk of the tail group, and, to a lesser extent, the sidearms mainly determine CD4 down-modulation potency in this series of compounds.

Effects of structure of self-knowledge on mood-incongruent effect

Some people recall more positive memories in negative moods than in neutral moods, which is called mood-incongruent effect. Although previous research suggested that structure of self-knowledge influences mood-incongruent effect (Sakaki, 2004), it is possible that motivation for mood-regulation mediates relation between structure of self-knowledge and mood-incongruent effect. The present study aimed at exploring this possibility by using self-complexity. In Study 1, participants with higher self-complexity, whose self-knowledge has more self-aspects with a higher level of differentiation, recalled more positive memories in negative moods (compared to neutral moods) than participants with lower self-complexity, whose self-knowledge has a fewer self-aspects with larger overlap. Study 1 also revealed that these effects hold even when the motivation for mood-regulation was partialed out. Study 2 examined mood-incongruent effect under positive moods, in which participants are unlikely motivated to alter their moods, and it was found that participants with higher self-complexity recalled more negative memories in positive moods (compared to neutral moods) than participants with lower self-complexity.

Classical and fragment-based hologram structure-activity relationships for a series of analgesic cyclic imides

Cyclic imides have been widely employed in drug design research due to their multiple pharmacological and biological properties. In the present study, two-dimensional quantitative structure-activity relationship (2D QSAR) studies were conducted on a series of potent analgesic cyclic imides using both classical and hologram QSAR (HQSAR) methods, yielding significant statistical models (classical QSAR, q(2) = 0.80; HQSAR, q(2) = 0.84). The models were then used to evaluate an external data test, and the predicted values were in good agreement with the experimental results, indicating their consistency for untested compounds.

Structure-activity relationships for a class of selective inhibitors of the major cysteine protease from Trypanosoma cruzi

Chagas` disease is a parasitic infection widely distributed throughout Latin America, with devastating consequences in terms of human morbidity and mortality. Cruzain, the major cysteine protease from Trypanosoma cruzi, is an attractive target for antitrypanosomal chemotherapy. In the present work, classical two-dimensional quantitative structure-activity relationships (2D QSAR) and hologram QSAR (HQSAR) studies were performed on a training set of 45 thiosemicarbazone and semicarbazone derivatives as inhibitors of T. cruzi cruzain. Significant statistical models (HQSAR, q2=0.75 and r2=0.96; classical QSAR, q2=0.72 and r2=0.83) were obtained, indicating their consistency for untested compounds. The models were then used to evaluate an external test set containing 10 compounds which were not included in the training set, and the predicted values were in good agreement with the experimental results (HQSAR, [image omitted]=0.95; classical QSAR, [image omitted]=0.91), indicating the existence of complementary between the two ligand-based drug design techniques.

Effects of physical habitat degradation on the stream fish assemblage structure in a pasture region

We compared the fish assemblage structure from streams with different intensities of physical habitat degradation and chemical water pollution by domestic sewage in southeastern Brazil. Eight streams (R1-R8) showing less disturbed or more disturbed conditions of chemical water quality and of physical habitat quality were selected. Cumulative abundance and biomass, combined in ABC plots, revealed (i) biomass curves above the abundance curves, represented by the streams R1-R2 (water and habitat less disturbed) and R5-R6 (water more disturbed and habitat less disturbed), and (ii) biomass curves below the abundance curves, represented by the streams R3-R4 (water less disturbed and habitat more disturbed) and R7-R8 (water and habitat more disturbed). The quantitative structure of the ichthyofauna showed significant correspondence with physical habitat condition but not with chemical water quality. The most significant species to cause the dissimilarity between less disturbed and more disturbed physical habitats was the exotic Poecilia reticulata. Such results indicate that in the focused region-with little influence of industrial pollution, noncritical domestic sewage discharge, and soil predominantly used for pasture-streams with high physical habitat integrity possess a differently structured ichthyofauna than streams with relatively low physical habitat integrity, reinforcing the importance of the physical habitat quality and riparian conservation along these water courses, warranting the conservation of these systems. Indeed, our results also reinforce the importance of including biotic descriptors, particularly of the ichthyo-fauna, in water-monitoring programs designed to reveal signs of human interference.

Structure and feeding of a stream fish assemblage in southeastern Brazil: evidence of low seasonal influences

Aim: The present study was developed in a deforested stream located in a region that exhibits marked seasonality with the purpose to investigate whether ecological descriptors of the quantitative structure (i.e., composition, abundance, biomass, species richness, diversity) and feeding of fishes do change between the dry and wet periods. Methods: Sampling was conducted bimonthly from April 2004 to February 2005 by using a standardized effort with electrofishing equipment and environmental variables measurements. Results: We collected 713 fishes belonging to 23 species. The most abundant species were Gymnotus carapo (24.0%) and Poecilia reticulata (23.8%). Species richness, abundance, and biomass showed to be higher in the wet period, but these differences were not significant and did not influence the multivariate pattern of the assemblage (ANOSIM, R = 0.148). Nevertheless, average dissimilarity between community structure in the dry and wet periods was 52.7%, mainly due to the differential contribution of P. reticulata, notably more abundant in the wet season, under quasi-hypoxic water conditions. Examination of 333 gastric contents of 12 species evidenced that food variety was higher in the dry period. of these species, 67% (Astyanax altiparanae, Astyanax fasciatus, Geophagus brasiliensis, Gymnotus carapo, Hypostomus ancistroides, Phalloceros harpagos, Poecilia reticulata, and Rhamdia quelen) kept the diet throughout the year, being classified in the same trophic groups in both periods, and detritus was the most important item for half of them, followed by aquatic insects. Overall, no significant differences in the community's diet between periods were registered (ANOSIM, R = [long dash]0.04). Conclusions: This relative constancy suggests a quite regular availability of resources (mainly shelters in submerged marginal grasses and detritus) along the year.

Influência da estrutura do hábitat sobre a ictiofauna de um riacho em uma micro-bacia de pastagem, São Paulo, Brasil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Toxicidade de fármacos nitrofurânicos

During the structural designing of new drugs, it is possible predict the influence of specific chemical groups on pharmacological activity. Among these, the nitro group has potential antiparasitic activity, being present in many antimicrobial drugs, such as metronidazole, nitrofurazone, furazolidone, oxamniquine and chloramphenicol. Also, the introduction of the nitro group into a molecule can modify the physicochemical and electronic properties of the substance. Besides antimicrobial drugs, this group is also found in other drug classes, such as antiulcer, anti-inflamatory and anxiolytic. However, the use of the nitro group in drug design has encountered restrictions, due to the associated toxicity. This article is a review of the toxicity of nitrofuran compounds, as well the possible mechanisms involved and the strategy of latentiation by molecular modification to decrease their toxicity.