<p style="text-align: justify;">Reverzno-faznom tečnom hromatografijom pod visokim pritiskom primenom dva sistema<br />rastvarača ispitano je pona&scaron;anje i hromatografska lipofilnost prirodnih stiril laktona 7-(+)-<br />goniofufurona, 7-epi-(+)-goniofufurona, krasalaktona B i C i dvadeset njihovih<br />novosintetizovanih derivata i analoga. U ranijim ispitivanjima pokazalo se da ova jedinjenja<br />imaju veliki biolo&scaron;ki potencijal jer pokazuju zapaženu citotoksičnost prema vi&scaron;e humanih<br />tumorskih ćelijskih linija. Hromatografsko pona&scaron;anje jedinjenja uglavnom je u skladu sa<br />njihovom strukturom. Ustanovljene su linearne veze između hromatografskih retencionih<br />konstanti i većine in silico parametara lipofilnosti. Primenom hemometrijske QSRR analize<br />utvrđeni su veoma dobri multi linearni regresioni prediktivni modeli kvantitativne zavisnosti<br />između eksperimentalno dobijene hromatografske retencione konstante, koja defini&scaron;e<br />retenciju jedinjenja u čistoj vodi i in silico molekulskih deskriptora odnosno strukture<br />jedinjenja. Lipofilnost jedinjenja ima najveći uticaj na njihove farmakokinetičke, tj. ADME<br />(apsorpcija, distribucija, metabolizam, eliminacija) osobine. Definisani su i statistički<br />potvrđeni najbolji multi linearni regresioni modeli zavisnosti farmakokinetičkih parametara<br />stiril laktona i od drugih molekulskih deskriptora. In vitro citotoksična aktivnost jedinjenja<br />evaluirana je prema četiri nove humane maligne ćelijske linije: kancer prostate (PC3), kancer debelog creva (HT-29), melanom (Hs294T), adenokancer pluća (A549). Najaktivnije<br />novosintetizovano jedinjenje je triciklični 4-fluorocinamatni analog, koji ispoljava<br />nanomolarnu aktivnost (IC₅₀ 2,1 nM) prema ćelijama melanoma i aktivniji je preko 2250 puta od komercijalnog antitumorskog agensa doksorubicina (DOX). SAR analizom utvrđena je zavisnost između strukture i biolo&scaron;ke aktivnosti jedinjenja. Molekulskim dokingom ispitana je veza stiril laktona i ciljanog proteina značajnog za kancer prostate. Jedinjenja sa visokom inhibitornom aktivno&scaron;ću prema ćelijama kancera prostate imaju visok doking skor i mogu graditi koordinativno-kovalentnu vezu sa Fe²+jonom prisutnim u aktivnom centru enzima. 3D-QSAR analizom, koja je izvedena metodama komparativnih polja CoMFA i CoMSIA, formiran je značajan prediktivni model između hemijske strukture i biolo&scaron;ke aktivnosti stiril laktona.</p> / <p>The behavior and the chromatographic lipophilicity natural styryl lactone 7-(+)-<br />goniofufurone, 7-epi-(+)-goniofufurone, crassalactones B and C and twenty of their newly<br />synthesized derivatives and analogs were examined using reverse-phase high performance liquid chromatography in the two solvent systems. In previous studies it has been shown that these compounds have great biological potential toward several human tumor cell lines. Chromatographic behavior of the compounds is generally in accordance with their structure. The relationships between the chromatographic retention constants and the majority of their in silico lipophilicity parameters are linear. The application of chemometric QSRR analysis determined very good multiple linear regression predictive models of quantitative correlation between experimentally obtained chromatographic retention constant, which determines the retention of the compound in pure water and in silico molecular descriptors, i.e. the structure of the compound. The lipophilicity of the compounds has a major influence on their pharmacokinetics, i.e. ADME (absorption, distribution, metabolism, elimination) properties. The best multi-linear regression models depending on the pharmacokinetic parameters of styryl lactone and other molecular descriptors have been defined and statistically validated. In vitro cytotoxic activity of the compounds was evaluated according to four novel human malignant cell lines: prostate cancer (PC3), colon cancer (HT-29), melanoma (Hs294T), lung adenocarcinom (A549). The most active compound was tricyclic 4-fluorocinnamic analog, which exhibits a nanomolar activity (IC50 2,1 nM) toward melanoma cells. This compound is over 2250 times more active than commercial antitumor agent doxorubicin (DOX). SAR analysis has revealed a correlation between the structure and the biological activity of the compounds. Using the molecular docking the relationship of the styryl lactone and the target protein important for prostate cancer was examined. The compounds with high inhibitory activity against prostate cancer cells have a high docking score and are capable to form a coordinative-covalent bond with a Fe2+ ion present in the active centre of the enzyme. 3DQSAR analysis, which was performed by methods of comparative CoMFA and CoMSIA fields, has formed a good predictive model between chemical structure and biological activity of the styryl lactone.</p>

Ce travail est consacré à la modélisation QSPR des propriétés cinétiques et thermodynamiques des réactions chimiques à l'aide de l'approche Graphe Condensé de Réaction (CGR). Le CGR permet de coder des structures de réactifs et de produits en un seul graphe moléculaire pour lequel des descripteurs moléculaires peuvent être générés.Une base de données contenant plus de 11000 réactions collectées manuellement a été développée puis utilisée dans la modélisation. Les modèles prédictifs ont été construits pour les constantes de vitesse de réactions Diels-Alder, SN2 et E2 ainsi que pour les constantes d'équilibre des transformations tautomères. Ils sont rendus publics via un portail WEB. Une partie de la thèse concerne une étude de mécanique quantique des réactions entre des sydnones et des alcynes contraints pour lesquels la taille du jeux de données n'était pas suffisante pour produire des modèles statistiquement significatifs. / This work is devoted to QSPR modeling of kinetic and thermodynamic properties of chemical reactions using the Condensed Graph of Reaction (CGR) approach. CGR allows encoding structures of reactants and products into one sole molecular graph for which molecular descriptors can be generated. A comprehensive database containing some 11000 manually collected reactions has been developed then used in the modeling. Predictive models were built for rate constants of Diels-Alder, SN2 and E2 reaction as well as for equilibrium constants of tautomeric transformations. They are available for the users via WEB portal. A part of the thesis concerned quantum mechanics studies of reactions between sydnones and strained alkynes for which the size of the dataset was not sufficient to produce statistically meaningful models.

Com o surgimento da era computacional com especial aplicação em química, as substâncias de origem naturais puderam ter suas informações armazenadas em bancos de dados. Desta forma, surge a oportunidade de se empregar bancos de dados de produtos naturais e de algumas ferramentas de quimioinformática como os estudos de Quantitative Structure-Retention Relationship (QSRR) para acelerar a identificação de substâncias em estudos metabolômicos. Este trabalho propôs o desenvolvimento de três estudos de QSRR, bem como a construção de um banco de dados (AsterDB) com estruturas químicas da família Asteraceae e informações a elas associadas (ex.: ocorrências botânicas e taxonômicas, atividade biológica, informações analíticas etc.) para auxiliar a desreplicação de substâncias em extratos vegetais. O primeiro estudo foi elaborado com 39 lactonas sesquiterpênicas (LST) analisadas em dois diferentes sistemas de solventes (MeOH-H2O 55:45 e MeCN-H2O 35:65), três grupos de descritores estruturais (2D-descr, 3D-1conf e 3D-weigh), dois diferentes conjuntos para treino e teste (26:13 e 29:10), quatro algoritmos para seleção de descritores (best first, linear forward - LFS, greedy stepwise e algoritmo genético - GA), três diferentes tamanhos de modelos (quatro, cinco e seis descritores) e dois métodos de modelagem (mínimos quadrados parciais - PLS e redes neurais artificiais - ANN). O segundo foi desenvolvido com 50 substâncias de diferentes classes químicas com intuito de avaliar as diferenças entre substâncias analisadas individualmente e em mistura em três diferentes equipamentos e dois métodos cromatográficos. O terceiro foi elaborado com 2.635 estruturas químicas com um teste externo comum a todos os modelos (25%, n = 656), três métodos de separação para teste e treino (partição baseada na resposta e baseada nos preditores 2D e 3D), três diferentes tamanhos de modelos selecionados por GA e dois métodos de modelagem (MLR e redes neurais feed-forward com regularização bayesiana - BRNN). O banco de dados AsterDB foi desenvolvido para ser preenchido de forma gradual e atualmente possui cerca de 2.000 estruturas químicas. O primeiro estudo de QSRR gerou bons modelos capazes de estimar o logaritmo do fator de retenção (logk) das LST com P2>0,81 para o sistema MeCN-H2O. O segundo estudo mostrou que não houve diferença estatística entre as substâncias analisadas individualmente e em mistura (p-valor>0,95) e que a correlação entre os dois métodos cromatográficos e equipamentos utilizados foi reprodutível (R>0,95). Estas análises mostraram que foi possível desenvolver modelos de QSRR para um método cromatográfico e equipamento e transpô-los para outro equipamento seguindo o uso de substâncias em comum. O terceiro estudo produziu modelos com boa capacidade de predição (P2>0,81) utilizando alta amplitude de espaço químico e rigor estatístico. Conclui-se que, estas informações podem ser utilizadas como uma plataforma piloto para análises de dados com objetivo de auxiliar na desreplicação de extratos de plantas em estudos metabolômicos / After the emergence of the computing era with special application in chemistry, all substances from natural sources might have their information stored in databases. Therefore, the opportunity arises to employ natural product databases and some chemoinformatic tools such as QSRR studies to speed up the identification of substances from metabolomic studies. This paper proposes the development of three QSRR studies as well as the building of a database (AsterDB) with chemical structures from the Asteraceae family and related information (i.e.: botanical and taxonomic occurrences, biological activity, analytical information, etc.) aiming to assist the dereplication of substances in plant extracts. The first study was carried out with 39 sesquiterpene lactones (STLs) analysed using two different solvent systems (MeOH-H2O 55:45 and MeCN-H2O 35:65), three groups of structural descriptors (2D-descr, 3D-1conf, and 3D-weigh), two different sets for training and testing (26:13 and 29:10), four algorithms for selection of descriptors (best first, LFS, greedy stepwise, and GA), three different model sizes (four, five, and six descriptors) and two modelling methods (PLS and ANN). The second study was developed with 50 compounds of different chemical classification in order to assess the differences between individual and mixed compounds analysed in three different equipments and two chromatographic methods. The third was elaborated with 2,635 chemical structures with a common external test to all models (25%, n = 656), three separation methods for testing- and training-set (based on response and on 2D and 3D predictors partitions), three different sizes of models selected by GA and two modelling methods (MLR and BrNN). The AsterDB database was developed to be populated gradually and currently, it has about 2,000 chemical structures. The first QSRR study generated good models, able to estimate the logarithm of the retention factor (logk) of STLs with P2>0.81 for the MeCN-H2O system. The second study showed that there was no statistical difference between the substances analysed individually and mixed (p-value>0.95) and the correlation between the two chromatographic methods and equipments used was reproducible (R>0.95). These analyses showed that it was possible to develop QSRR models for a chromatographic method and equipment and translate them into other equipment following the use of substances in common. The third study produced models with good predictive capacity (P2>0.81) using a high range of chemical space and statistical accuracy. In conclusion, this information can be used as a pilot platform for data analysis in order to assist in plant dereplication in metabolomics studies

Com o surgimento da era computacional com especial aplicação em química, as substâncias de origem naturais puderam ter suas informações armazenadas em bancos de dados. Desta forma, surge a oportunidade de se empregar bancos de dados de produtos naturais e de algumas ferramentas de quimioinformática como os estudos de Quantitative Structure-Retention Relationship (QSRR) para acelerar a identificação de substâncias em estudos metabolômicos. Este trabalho propôs o desenvolvimento de três estudos de QSRR, bem como a construção de um banco de dados (AsterDB) com estruturas químicas da família Asteraceae e informações a elas associadas (ex.: ocorrências botânicas e taxonômicas, atividade biológica, informações analíticas etc.) para auxiliar a desreplicação de substâncias em extratos vegetais. O primeiro estudo foi elaborado com 39 lactonas sesquiterpênicas (LST) analisadas em dois diferentes sistemas de solventes (MeOH-H2O 55:45 e MeCN-H2O 35:65), três grupos de descritores estruturais (2D-descr, 3D-1conf e 3D-weigh), dois diferentes conjuntos para treino e teste (26:13 e 29:10), quatro algoritmos para seleção de descritores (best first, linear forward - LFS, greedy stepwise e algoritmo genético - GA), três diferentes tamanhos de modelos (quatro, cinco e seis descritores) e dois métodos de modelagem (mínimos quadrados parciais - PLS e redes neurais artificiais - ANN). O segundo foi desenvolvido com 50 substâncias de diferentes classes químicas com intuito de avaliar as diferenças entre substâncias analisadas individualmente e em mistura em três diferentes equipamentos e dois métodos cromatográficos. O terceiro foi elaborado com 2.635 estruturas químicas com um teste externo comum a todos os modelos (25%, n = 656), três métodos de separação para teste e treino (partição baseada na resposta e baseada nos preditores 2D e 3D), três diferentes tamanhos de modelos selecionados por GA e dois métodos de modelagem (MLR e redes neurais feed-forward com regularização bayesiana - BRNN). O banco de dados AsterDB foi desenvolvido para ser preenchido de forma gradual e atualmente possui cerca de 2.000 estruturas químicas. O primeiro estudo de QSRR gerou bons modelos capazes de estimar o logaritmo do fator de retenção (logk) das LST com P2>0,81 para o sistema MeCN-H2O. O segundo estudo mostrou que não houve diferença estatística entre as substâncias analisadas individualmente e em mistura (p-valor>0,95) e que a correlação entre os dois métodos cromatográficos e equipamentos utilizados foi reprodutível (R>0,95). Estas análises mostraram que foi possível desenvolver modelos de QSRR para um método cromatográfico e equipamento e transpô-los para outro equipamento seguindo o uso de substâncias em comum. O terceiro estudo produziu modelos com boa capacidade de predição (P2>0,81) utilizando alta amplitude de espaço químico e rigor estatístico. Conclui-se que, estas informações podem ser utilizadas como uma plataforma piloto para análises de dados com objetivo de auxiliar na desreplicação de extratos de plantas em estudos metabolômicos / After the emergence of the computing era with special application in chemistry, all substances from natural sources might have their information stored in databases. Therefore, the opportunity arises to employ natural product databases and some chemoinformatic tools such as QSRR studies to speed up the identification of substances from metabolomic studies. This paper proposes the development of three QSRR studies as well as the building of a database (AsterDB) with chemical structures from the Asteraceae family and related information (i.e.: botanical and taxonomic occurrences, biological activity, analytical information, etc.) aiming to assist the dereplication of substances in plant extracts. The first study was carried out with 39 sesquiterpene lactones (STLs) analysed using two different solvent systems (MeOH-H2O 55:45 and MeCN-H2O 35:65), three groups of structural descriptors (2D-descr, 3D-1conf, and 3D-weigh), two different sets for training and testing (26:13 and 29:10), four algorithms for selection of descriptors (best first, LFS, greedy stepwise, and GA), three different model sizes (four, five, and six descriptors) and two modelling methods (PLS and ANN). The second study was developed with 50 compounds of different chemical classification in order to assess the differences between individual and mixed compounds analysed in three different equipments and two chromatographic methods. The third was elaborated with 2,635 chemical structures with a common external test to all models (25%, n = 656), three separation methods for testing- and training-set (based on response and on 2D and 3D predictors partitions), three different sizes of models selected by GA and two modelling methods (MLR and BrNN). The AsterDB database was developed to be populated gradually and currently, it has about 2,000 chemical structures. The first QSRR study generated good models, able to estimate the logarithm of the retention factor (logk) of STLs with P2>0.81 for the MeCN-H2O system. The second study showed that there was no statistical difference between the substances analysed individually and mixed (p-value>0.95) and the correlation between the two chromatographic methods and equipments used was reproducible (R>0.95). These analyses showed that it was possible to develop QSRR models for a chromatographic method and equipment and translate them into other equipment following the use of substances in common. The third study produced models with good predictive capacity (P2>0.81) using a high range of chemical space and statistical accuracy. In conclusion, this information can be used as a pilot platform for data analysis in order to assist in plant dereplication in metabolomics studies

L’énantiomérisme est un sujet majeur dans des domaines divers, en particulier celui de la pharmacie (principe actifs et métabolites). La commercialisation de médicaments sous forme racémique a longtemps été privilégiée au dépend d’éventuels effets secondaires. Depuis les années 90, le développement du nombre d’entités énantiomériquement pures est en hausse, notamment grâce au développement des techniques de séparation. La chromatographie chirale, à l’aide de support énantiosélectif, s’est très vite imposée pour la résolution rapide et directe de stéréoisomères. Cependant, la faible compréhension des mécanismes intervenant dans la reconnaissance chirale limite un choix rationnel reposant sur la structure des composés chiraux, conduisant à une procédure de développement de méthode de séparation chirale systématique, fastidieuse et coûteuse d’essais et erreurs. Ce projet de recherche se situe à l’interface des sciences analytiques et de la chémo-informatique. Il consiste en une amélioration de nos connaissances sur le mécanisme de reconnaissance chirale afin d’aborder le développement de méthode chirale de manière plus rigoureuse. / The subject of enantiomer separation is a major issue in various fields, particularly pharmaceuticals (metabolites and active principle). To prepare pharmaceutical formulations, the racemic form has long been favored at the expense of possible side effects. Since the 90s, the development of the number of enantiomerically pure entities is rising, particularly through the development of separation techniques. Chiral chromatography using enantioselective stationary phases is an excellent technique for fast and direct resolution of stereoisomers. However, limited understanding of the mechanism leads to tedious and expensive trial-and-error systematic chiral method development. No clear guideline for choosing a chromatographic system is available for a new chiral drug. In this project, we wish to achieve a better knowledge of enantioselective separation techniques in order to help in the choice of separation method that will be the most appropriate for any given chiral separation. This project is based on the rationalization of large amounts of experimental data with the help of modelling and chemometric techniques to unravel the enantioselective recognition mechanism.

Cette thèse vise à développer une approche basée sur le concept de Graphe Condensé de Réaction (GCR) capable de (i) sélectionner un espace optimal de descripteurs séparant au mieux différentes classes de réactions, et (ii) de préparer de nouveaux descripteurs pour la modélisation « structure–réactivité ». Cette méthodologie a été appliquée à la recherche par similarité dans une base de données contenant 8 classes de réaction différentes; et à la cartographie de son espace chimique en utilisant des cartes de Kohonen et de cartes topographiques génératives. La seconde partie de la thèse porte sur le développement de modèles prédictifs pour le pKa et pour des conditions optimales pour différents types de réaction de Michael impliquant à la fois les descripteurs d’effet électronique et des descripteurs calculés sur les GCR. / This thesis aims to develop an approach based on the Condensed Graph of Reaction (CGR) method able to (i) select an optimal descriptor space the best separating different reaction classes, and (ii) to prepare special descriptors to be used in obtaining predictive structure-reactivity models. This methodology has been applied to similarity search studies in a database containing 8 different reaction classes, and to visualization of its chemical space using Kohonen maps and Generative Topographic Mapping. Another part of the thesis concerns development of predictive models for pKa and for optimal conditions for different types of Michael reaction involving both CGR-based and Electronic Effect Descriptors.

<p>Steroidna jedinjenja spadaju u grupu supstanci sa &scaron;irokim spektrom biolo&scaron;kog delovanja i predstavljaju dobru polaznu osnovu za sintezu mnogih derivata sa željenim biolo&scaron;kim potencijalom. Organskim sintezama se do&scaron;lo do velikog broja steroidnih derivata, od kojih su neki pokazali značajnu biolo&scaron;ku aktivnost, kao &scaron;to je citotoksičnost prema različitim ćelijskim linijama kancera. Karakterizacija novosintetisanih jedinjenja može se izvesti eksperimentalnim i računarskim (in silico) metodama. U ovoj doktorskoj disertaciji predstavljeno je eksperimentalno određivanje lipofilnosti 17&alpha;-pikolil i 17(E)-pikoliniliden androstanskih derivata primenom visokopritisne tečne hromatografije na obrnutim fazama, a potom hemometrijska analiza hromatografskog pona&scaron;anja (hromatografske lipofilnosti) QSRR pristupom. Hemijska struktura analiziranih derivata opisana je numerički, pomoću izračunatih molekulskih deskriptora. U drugom delu doktorske disertacija predstavljena je QSAR analiza citotoksične aktivnosti 17&alpha;-pikolil i 17(E)-pikoliniliden androstanskih derivata prema ćelijama androgen-receptor negativnog kancera prostate (AR-neg. PC-3). Odabir najkvalitetnijih QSRR i QSAR modela obavljen je na osnovu izračunatih statističkih parametara, a njihovo rangiranje izvedeno je primenom metode sume razlika rangova (SRD). Pored regresionih QSRR i QSAR hemometrijskih metoda, primenjene su i klaster analiza i analiza glavnih komponenata sa ciljem utvrđivanja sličnosti ili razlika između analiziranih derivata na<br />osnovu izračunatih molekulskih deskriptora.</p> / <p>Steroidal compounds belong to the group of substances with wide spectrum of biological activity and represent the basic material for synthesis of many derivatives<br />with preferred biological potential. A grate number of steroidal derivatives have been<br />obtained through organic syntheses, many of which have demonstrated significant<br />biological activity, such as cytotoxicity toward various cancer cell lines. Characterization of newly synthesized compounds can be achieved experimentally<br />and by computational approach (in silico). This doctoral dissertation describes<br />experimental determination of lipophilicity of 17&alpha;-picolyl and 17(E)-picolinylidene<br />androstane derivatives applying reversed-phase high pressure liquid chromatography followed by quantitative structure-retention relationship (QSRR)<br />chemometric analysis of chromatographic behaviour (chromatographic lipophilicity).<br />Chemical structure of the analyzed derivatives was described numerically by in silico<br />molecular descriptors. The second part of this dissertation describes quantitative<br />structure-activity relationship (QSAR) analysis of cytotoxic activity of 17&alpha;-picolyl and<br />17(E)-picolinylidene androstane derivatives toward androgen-receptor negative<br />prostate cancer cell line (AR-neg. PC-3). Selection of the best QSRR and QSAR<br />models was carried out based on their statistical parameters, and their ranking was<br />done by sum of ranking differences (SRD) method. Besides the regression QSRR and QSAR chemometric methods, cluster analysis and principal components analysis were conducted in order to reveal possible similarities and dissimilarities among the studied derivatives on the basis of calculated molecular descriptors.</p>

Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2016-10-11T22:51:16Z No. of bitstreams: 1 LilianGraceDaSilvaSolon_TESE.pdf: 7051337 bytes, checksum: 79a5b10c1ce003624bdd49bff3af8afd (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2016-10-18T00:03:19Z (GMT) No. of bitstreams: 1 LilianGraceDaSilvaSolon_TESE.pdf: 7051337 bytes, checksum: 79a5b10c1ce003624bdd49bff3af8afd (MD5) / Made available in DSpace on 2016-10-18T00:03:19Z (GMT). No. of bitstreams: 1 LilianGraceDaSilvaSolon_TESE.pdf: 7051337 bytes, checksum: 79a5b10c1ce003624bdd49bff3af8afd (MD5) Previous issue date: 2016-02-04 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior (CAPES) / A ind?stria farmac?utica e laborat?rios anal?ticos de todo o mundo tem focado na qualidade, seguran?a e efic?cia de seus produtos. Processos utilizados para minimizar os riscos, como o Quality by Design (QbD), recentemente tem sido atribu?do ao desenvolvimento de m?todos anal?ticos, principalmente os m?todos cromatogr?ficos. O Analytical Quality by Design ou Qualidade Anal?tica Baseada no Projeto (aQbD), utiliza ferramentas de planejamento de experimentos, an?lise de risco e monitoramento cont?nuo. Para isso, faz-se uso de softwares simuladores, ferramentas estat?sticas e quimiom?tricas. Sabe-se que os m?todos cromatogr?ficos de an?lise s?o bastante consolidados e exigidos pelas ag?ncias regulat?rias, aplicando-se em diversas determina??es dentro do campo farmac?utico, como identifica??o e quantifica??o de f?rmacos, metab?litos, impurezas e produtos de degrada??o. O presente estudo teve como objetivo, utilizar ferramentas aQbD para o desenvolvimento de m?todos em cromatografia l?quida de ultra efici?ncia. Foram desenvolvidos quatro m?todos, a saber: quantifica??o simult?nea de dexametasona acetato e clotrimazol em formas farmac?uticas semiss?lidas, atrav?s de transfer?ncia de m?todo de CLAE para CLUE (cap?tulo 1); determina??o simult?nea de corticosteroides e conservantes em coluna de n?cleo s?lido com tamanho de part?cula 1.3 ?m utilizando software simulador (cap?tulo 2); quantifica??o de betametasona valerato em amostras de creme, gel, lo??o e pomada ap?s desenvolvimento de m?todo por planejamento fatorial completo 33 (cap?tulo 3); e determina??o simult?nea de corticosteroides ap?s desenvolvimento de modelo de previs?o de fator de reten??o por QSRR (cap?tulo 4). Os resultados mostraram que apesar da necessidade de otimiza??o pelo analista, o uso de ferramentas aQbD, como o planejamento estat?stico ou uso de softwares, s?o promissoras no desenvolvimento de m?todos cromatogr?ficos de ultra efici?ncia, uma vez que foram capazes de promover economia de tempo, diminuir os gastos e riscos. Os ensaios apresentaram resultados satisfat?rios em termos de velocidade anal?tica e diminui??o no consumo de solventes. / The pharmaceutical industry and analytical laboratories around the world have focused on quality, safety and efficacy of their products. Processes used to minimize risks, such as Quality by Design (QbD), which recently has been attributed to the development of analytical methods, especially chromatographic methods. The Analytical Quality by Design (aQbD) uses planning tools experiments, risk analysis and continuous monitoring. For this, it makes use of simulation software, statistical tools and chemometrics. It is known that chromatographic methods are well consolidated and required by the regulatory agencies. It has been applied in various determinations in the pharmaceutical field, such as identification and quantification of drugs, metabolites, degradation products and impurities. The aim of this study was to use aQbD tools for the development of methods for ultra high performance liquid chromatography (UHPLC). Four methods were developed, namely: simultaneous quantification of dexamethasone acetate and clotrimazole in semisolid dosage forms, via HPLC to UHPLC method transfer (Chapter 1); simultaneous determination of corticosteroids and preservatives in solid core column with particle size of 1.3 ?m by using simulation software (Chapter 2); betamethasone valerate quantification in samples of cream, gel, lotion and ointment after method development by full factorial design 33 (Chapter 3); and simultaneous determination of corticosteroids after retention factor prediction model by QSRR (Chapter 4). The results showed that despite the need for optimization by the analyst, the use of aQbD tools such as statistical design or use of software, the aQbD is promising in the development of chromatographic methods of ultra efficiency, since they were able to promote time savings, lower costs and risks. The tests showed satisfactory results in terms of analysis speed and decrease of solvent consumption.

<p>Испитивано је хроматографско понашање (хроматографска липофилност) 29 стероидних једињења (триазола и тетразола, толуенсулфонилхидразида, диона, нитрила и динитрила) од потенцијалног биомедицинског значаја, испитивано је помоћу течне хроматографије високих перформанси на обрнутим фазама, применом две стационарне и две мобилне фазе. Липофилност, изражена преко ретенционог параметра logk, моделована је QSRR приступом. Формирани линеарни и нелинеарни модели омогућили су испитивање односа између ретенционих параметара и in silico молекулских дескриптора, који су израчунати на основу структуре испитиваних једињења. Добра предиктивна моћ формираних модела, добијених за калибрациони сет, потврђена је и применом екстерног тест сета и валидационог сета. Предиктивна моћ формираних модела потврђује могућност њиховог коришћења за предвиђање липофилности нових, структурно сличних, једињења. Примењене су и класификационе хемометријске методе (анализа главних компоненти и хијерархијска кластер анализа) како би се уочиле сличности и разлика између једињења. Поред тога, представљена је in vitro анализа антимикробног потенцијала испитиваних стероидних једињења према Staphylococcus aureus, Escherichia coli и Candida albicans. Два једињења, са епоксидном групом у положају 4,5, испољила су бактериостатски ефекат према S. aureus. Такође, приказана је докинг анализа одабраних испитиваних једињења са антипролиферативном активношћу према ћелијама андроген-рецептор негативног канцера простате (AR-нег. PC-3). На основу визуелизације оптималних положаја и анализе постојећих интеракција, идентификовано је једињење са највећим потенцијалом као инхибитор хуманог цитохрома P450 CYP17A1.</p> / <p>Ispitivano je hromatografsko ponašanje (hromatografska lipofilnost) 29 steroidnih jedinjenja (triazola i tetrazola, toluensulfonilhidrazida, diona, nitrila i dinitrila) od potencijalnog biomedicinskog značaja, ispitivano je pomoću tečne hromatografije visokih performansi na obrnutim fazama, primenom dve stacionarne i dve mobilne faze. Lipofilnost, izražena preko retencionog parametra logk, modelovana je QSRR pristupom. Formirani linearni i nelinearni modeli omogućili su ispitivanje odnosa između retencionih parametara i in silico molekulskih deskriptora, koji su izračunati na osnovu strukture ispitivanih jedinjenja. Dobra prediktivna moć formiranih modela, dobijenih za kalibracioni set, potvrđena je i primenom eksternog test seta i validacionog seta. Prediktivna moć formiranih modela potvrđuje mogućnost njihovog korišćenja za predviđanje lipofilnosti novih, strukturno sličnih, jedinjenja. Primenjene su i klasifikacione hemometrijske metode (analiza glavnih komponenti i hijerarhijska klaster analiza) kako bi se uočile sličnosti i razlika između jedinjenja. Pored toga, predstavljena je in vitro analiza antimikrobnog potencijala ispitivanih steroidnih jedinjenja prema Staphylococcus aureus, Escherichia coli i Candida albicans. Dva jedinjenja, sa epoksidnom grupom u položaju 4,5, ispoljila su bakteriostatski efekat prema S. aureus. Takođe, prikazana je doking analiza odabranih ispitivanih jedinjenja sa antiproliferativnom aktivnošću prema ćelijama androgen-receptor negativnog kancera prostate (AR-neg. PC-3). Na osnovu vizuelizacije optimalnih položaja i analize postojećih interakcija, identifikovano je jedinjenje sa najvećim potencijalom kao inhibitor humanog citohroma P450 CYP17A1.</p> / <p>Chromatographic behavior (chromatographic lipophilicity) of 29 steroid compounds (triazole and tetrazole, toluenesulfonylhydrazide, dione, dinitrile and nitrile) with potential biomedical importance was investigated by reversed-phases high-performance liquid chromatography using two stationary and two mobile phases. The lipophilicity expressed through the retention parameter logk was modeled using QSRR approach. Formed linear and non-linear models enabled the study of the relationship between the retention parameters and in silico molecular descriptors calculated from the structure of the investigated compounds. Good predictive power of the established models obtained for the calibration set was confirmed by the application of an external test set and validation set. The predictive power of the established model confirms the possibility of their use for lipophilicity prediction of new, structurally similar compounds. The classification chemometric methods (principal components analysis and hierarchical cluster analysis) were applied in order to recognize the similarities and differences between the compounds. Тhis dissertation presents the in vitro analysis of the antimicrobial potentials of the investigated steroid compounds against Staphylococcus aureus, Escherichia coli and Candida albicans. Two compounds, with epoxy group in the position 4,5, exhibited bacteriostatic effect against S. aureus. The docking analysis of selected test compounds with antiproliferative activity toward cells of androgen receptor-negative prostate cancer (AR-neg. PC-3) is showed. Based on the optimal position visualization and analysis of existing interactions a compound with the most promising potential as human cytochrome P450 CYP17A1 inhibitor is idetified.</p>