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.

Prévention de l’asthme professionnel : nouvelles perspectives

L’asthme professionnel est une maladie fréquente, qui coûte cher, qui touche des travailleurs jeunes, dont le diagnostic est difficile et avec d’importantes conséquences socio-économiques. La prévention occupe une place centrale dans la gestion de l’asthme professionnel, d’un point de vue de santé publique. Ce mémoire de maîtrise présente trois articles rapportant des développements récents en matière de prévention de l’asthme professionnel. Tout d’abord, une revue de la littérature sur les agents sensibilisants de bas poids moléculaire dans l’asthme professionnel entre 2000 et 2010 recense 41 nouveaux agents et insiste sur l’importance de mettre à jour régulièrement les bases de données afin d’améliorer la prévention primaire. Ensuite, basé sur un cas clinique, la deuxième publication présente l’utilité potentielle du modèle d’analyse de risque QSAR (Quantitative Structure-Activity Relationship) dans le processus diagnostique de l’asthme professionnel, notamment lors d’une exposition multiple à des agents sensibilisants. Enfin, le troisième article présente la performance en milieu clinique du premier questionnaire de dépistage spécifique à l’asthme professionnel. Un modèle simple associant 8 items du questionnaire, l’âge des travailleurs et leur durée d’exposition professionnelle permet de discriminer 80% des 169 sujets adressés pour suspicion d’asthme professionnel. Un tel modèle pourrait être intégré dans les programmes de surveillance médicale qui constituent la base de la prévention secondaire. Ces trois publications insistent sur les possibilités d’explorer de nouveaux outils préventifs dans le domaine de l’asthme professionnel, outils qui ouvrent des perspectives de développements futurs dont les implications cliniques et socio-économiques peuvent être importantes.

Molecular quantum similarity in QSAR: applications in computer-aided molecular design

La present tesi està centrada en l'ús de la Teoria de Semblança Quàntica per a calcular descriptors moleculars. Aquests descriptors s'utilitzen com a paràmetres estructurals per a derivar correlacions entre l'estructura i la funció o activitat experimental per a un conjunt de compostos. Els estudis de Relacions Quantitatives Estructura-Activitat són d'especial interès per al disseny racional de molècules assistit per ordinador i, en particular, per al disseny de fàrmacs. Aquesta memòria consta de quatre parts diferenciades. En els dos primers blocs es revisen els fonaments de la teoria de semblança quàntica, així com l'aproximació topològica basada en la teoria de grafs. Ambdues teories es fan servir per a calcular els descriptors moleculars. En el segon bloc, s'ha de remarcar la programació i implementació de programari per a calcular els anomenats índexs topològics de semblança quàntica. La tercera secció detalla les bases de les Relacions Quantitatives Estructura-Activitat i, finalment, el darrer apartat recull els resultats d'aplicació obtinguts per a diferents sistemes biològics.

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.

Fragment-Based QSAR and Molecular Modeling Studies on a Series of Discodermolide Analogs as Microtubule-Stabilizing Anticancer Agents

Inhibition of microtubule function is an attractive rational approach to anticancer therapy. Although taxanes are the most prominent among the microtubule-stabilizers, their clinical toxicity, poor pharmacokinetic properties, and resistance have stimulated the search for new antitumor agents having the same mechanism of action. Discodermolide is an example of nontaxane natural product that has the same mechanism of action, demonstrating superior antitumor efficacy and therapeutic index. The extraordinary chemical and biological properties have qualified discodermolide as a lead structure for the design of novel anticancer agents with optimized therapeutic properties. In the present work, we have employed a specialized fragment-based method to develop robust quantitative structure - activity relationship models for a series of synthetic discodermolide analogs. The generated molecular recognition patterns were combined with three-dimensional molecular modeling studies as a fundamental step on the path to understanding the molecular basis of drug-receptor interactions within this important series of potent antitumoral agents.

Two-dimensional QSAR studies on arylpiperazines as high-affinity 5-HT(1A) receptor ligands

5-HT(1A) receptor plays an important role in the delayed onset of antidepressant action of a class of selective serotonin reuptake inhibitors. Moreover, 5-HT(1A) receptor levels have been shown to be altered in patients suffering from major depression. In this work, hologram quantitative structure-activity relationship (HQSAR) studies were performed on a series of arylpiperazine compounds presenting affinity to the 5-HT(1A) receptor. The models were constructed with a training set of 70 compounds. The most significant HQSAR model (q(2) = 0.81, r(2) = 0.96) was generated using atoms, bonds, connections, chirality, and donor and acceptor as fragment distinction, with fragment size of 6-9. Predictions for an external test set containing 20 compounds are in good agreement with experimental results showing the robustness of the model. Additionally, useful information can be obtained from the 2D contribution maps.

A quantum chemical study on a set of non-imidazole H(3) antihistamine molecules

Molecular orbital calculations were carried out on a set of 28 non-imidazole H(3) antihistamine compounds using the Hartree-Fock method in order to investigate the possible relationships between electronic structural properties and binding affinity for H3 receptors (pK(i)). It was observed that the frontier effective-for-reaction molecular orbital (FERMO) energies were better correlated with pK(i) values than highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energy values. Exploratory data analysis through hierarchical cluster (HCA) and principal component analysis (PCA) showed a separation of the compounds in two sets, one grouping the molecules with high pK(i) values, the other gathering low pK(i) value compounds. This separation was obtained with the use of the following descriptors: FERMO energies (epsilon(FERMO)), charges derived from the electrostatic potential on the nitrogen atom (N(1)), electronic density indexes for FERMO on the N(1) atom (Sigma((FERMO))c(i)(2)). and electrophilicity (omega`). These electronic descriptors were used to construct a quantitative structure-activity relationship (QSAR) model through the partial least-squares (PLS) method with three principal components. This model generated Q(2) = 0.88 and R(2) = 0.927 values obtained from a training set and external validation of 23 and 5 molecules, respectively. After the analysis of the PLS regression equation and the values for the selected electronic descriptors, it is suggested that high values of FERMO energies and of Sigma((FERMO))c(i)(2), together with low values of electrophilicity and pronounced negative charges on N(1) appear as desirable properties for the conception of new molecules which might have high binding affinity. 2010 Elsevier Inc. All rights reserved.

A partial least squares and principal component regression study of quinone compounds with trypanocidal activity

A quantitative structure-activity relationship (QSAR) study of 19 quinone compounds with trypanocidal activity was performed by Partial Least Squares (PLS) and Principal Component Regression (PCR) methods with the use of leave-one-out crossvalidation procedure to build the regression models. The trypanocidal activity of the compounds is related to their first cathodic potential (Ep(c1)). The regression PLS and PCR models built in this study were also used to predict the Ep(c1) of six new quinone compounds. The PLS model was built with three principal components that described 96.50% of the total variance and present Q(2) = 0.83 and R-2 = 0.90. The results obtained with the PCR model were similar to those obtained with the PLS model. The PCR model was also built with three principal components that described 96.67% of the total variance with Q(2) = 0.83 and R-2 = 0.90. The most important descriptors for our PLS and PCR models were HOMO-1 (energy of the molecular orbital below HOMO), Q4 (atomic charge at position 4), MAXDN (maximal electrotopological negative difference), and HYF (hydrophilicity index).

A partial least squares regression study with antioxidant flavonoid compounds

The quantitative structure-activity relationship of a set of 19 flavonoid compounds presenting antioxidant activity was studied by means of PLS (Partial Least Squares) regression. The optimization of the structures and calculation of electronic properties were done by using the semiempirical method AMI. A reliable model (r(2) = 0.806 and q(2) = 0.730) was obtained and from this model it was possible to consider some aspects of the structure of the flavonoid compounds studied that are related with their free radical scavenging ability. The quality of the PLS model obtained in this work indicates that it can be used in order to design new flavonoid compounds that present ability to scavenge free radicals.

Lipophilicity as a determinant of binding of procaine analogs to rat alpha(3)beta(4) nicotinic acetylcholine receptor

Nicotinic acetylcholine receptors (nAChRs) have been studied in detail with regard to their interaction with therapeutic and drug addiction-related compounds. Using a structureactivity approach, we have examined the relationship among the molecular features of a set of eight para-R-substituted N,N-[(dimethylamino)ethyl] benzoate hydrochlorides, structurally related to procaine and their affinity for the a3 beta 4 nAChR heterologously expressed in KXa3 beta 4R2 cells. Affinity values (log[1/IC50]) of these compounds for the a3 beta 4 nAChR were determined by their competition with [3H]TCP binding. Log(1/IC50) values were analyzed considering different hydrophobic and electronic parameters and those related to molar refractivity. These have been experimentally determined or were taken from published literature. In accordance with literature observations, the generated cross-validated quantitative structureactivity relationship (QSAR) equations indicated a significant contribution of hydrophobic term to binding affinity of procaine analogs to the receptor and predicted affinity values for several local anesthetics (LAs) sets taken from the literature. The predicted values by using the QSAR model correlated well with the published values both for neuronal and for electroplaque nAChRs. Our work also reveals the general structure features of LAs that are important for interaction with nAChRs as well as the structural modifications that could be made to enhance binding affinity. (c) 2012 Wiley Periodicals, Inc.

Lamivudine salts with improved solubilities

To optimize solubility of drugs, current strategies mainly focus on engineering and screening of smart crystal phases. Two salts of the anti-human immunodeficiency virus (HIV) drug lamivudinenamely, lamivudine hydrochloride and lamivudine hydrochloride monohydrate, were prepared in the course of screening the crystallization conditions of lamivudine duplex, an uncommon DNA-mimic, double-stranded helical structure made up of partially protonated drug pairs. Here, water solubilities of lamivudine hydrochloride, lamivudine hydrochloride monohydrate, and lamivudine duplex are reported. The aqueous solubility of this anti-HIV drug was significantly increased in both salts and also in lamivudine duplex in relation to the water solubility of lamivudine form II. In comparison with the lamivudine form II incorporated into therapeutic formulations, the drug solubility was increased at a temperature of 299 +/- 2 K by factors of 1.2, 3.3, and 4.5 in lamivudine hydrochloride, lamivudine hydrochloride monohydrate, and lamivudine duplex, respectively, demonstrating that this solid-state property of lamivudine can be improved by crystal engineering strategies. Solubility profiles were understood on the basis of structural and solventsolute interaction approaches. At last, correlations between solubility and crystal structures allowed for a rational approach to understand how this physicochemical feature could be enhanced by engineering new salts of the drug. (C) 2012 Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci 101:21432154, 2012

Inhibitors of Trypanosoma brucei trypanothione reductase: comparative molecular field analysis modeling and structural basis for selective inhibition

Background: Sleeping sickness is a major cause of death in Africa. Since no secure treatment is available, the development of novel therapeutic agents is urgent. In this context, the enzyme trypanothione reductase (TR) is a prominent molecular target that has been investigated in drug design for sleeping sickness. Results: In this study, comparative molecular field analysis models were generated for a series of Trypanosoma brucei TR inhibitors. Statistically significant results were obtained and the models were applied to predict the activity of external test sets, with good correlation between predicted and experimental results. We have also investigated the structural requirements for the selective inhibition of the parasite's enzyme over the human glutathione reductase. Conclusion: The quantitative structure-activity relationship models provided valuable information regarding the essential molecular requirements for the inhibitory activity upon the target protein, providing important insights into the design of more potent and selective TR inhibitors.

Spin polarized transport in manganese oxide double-perovskite thin films

Gegenstand dieser Arbeit war die Untersuchung von metallischen gemischtvalenten Manganaten und magnetischen Doppelperowskiten. Aufgrund ihres großen negativen Magnetowiderstandes (MW) sind diese halbmetallischen Oxide interessant für mögliche technische Anwendungen, z.B. als Leseköpfe in Festplatten. Es wurden die kristallographischen, elektronischen und magnetischen Eigenschaften von epitaktischen Dünnschichten und polykristallinen Pulverproben bestimmt.Epitaktische Dünnschichten der Verbindungen La_0.67Ca_0.33MnO₃ und La_0.67Sr_0.33MnO₃ wurdenmit Kaltkathodenzerstäubung und Laserablation auf einkristallinen Substraten wie SrTiO₃abgeschieden. Mit Hall-Effekt Messungen wurde ein Zusammenbruch der Ladungsträgerdichte bei der Curie-Temperatur T_C beobachtet.Mit dem Wechsel des Dotierungsatoms A von Ca (T_C=232 K) zu Sr (T_C=345 K)in La_0.67A_0.33MnO₃ konnte die Feldsensitivität des Widerstandes bei Raumtemperatur gesteigert werden. Um die Sensitivität weiter zu erhöhen wurde die hohe Spinpolarisation von nahezu 100% in Tunnelexperimenten ausgenutzt. Dazu wurden biepitaktische La_0.67Ca_0.33MnO₃ Schichten auf SrTiO₃ Bikristallsubstraten hergestellt. Die Abhängigkeit des Tunnelmagnetowiderstandes (TMW) vom magnetischen Feld, Temperatur und Strum war ein Schwerpunkt der Untersuchung. Mittels spinpolarisierten Tunnelns durch die künstliche Korngrenze konnte ein hysteretischer TMW von 70% bei 4 K in kleinen Magnetfeldern von 120 Oe gemessen werden. Eine weitere magnetische Oxidverbindung, der Doppelperowskit Sr₂FeMoO₆ miteine Curie-Temperatur oberhalb 400 K und einem großen MW wurde mittels Laserablation hergestellt. Die Proben zeigten erstmals das Sättigunsmoment, welches von einer idealen ferrimagnetischen Anordnung der Fe und Mo Ionen erwartet wird. Mit Hilfe von Magnetotransportmessungen und Röntgendiffraktometrie konnte eine Abhängigkeit zwischen Kristallstruktur (Ordnung oder Unordnung im Fe, Mo Untergitter) und elektronischem Transport (metallisch oder halbleitend) aufgedeckt werden.Eine zweiter Doppelperowskit Ca₂FeReO₆ wurde im Detail als Pulverprobe untersucht. Diese Verbindung besitzt die höchste Curie-Temperatur von 540 K, die bis jetzt in magnetischen Perowskiten gefunden wurde. Mit Neutronenstreuung wurde eine verzerrte monoklinische Struktur und eine Phasenseparation aufgedeckt.