The process of drug discovery is very slow and expensive. There is a need for reliable in silico methods; however the performance of these methods differs. This work presents a targeted study on how the drug discovery methods used in OpenEye’s tools ROCS, EON and FRED perform on targets with small ligands. It was examined if 12 compounds (markers) somewhat similar to AMP could be detected by ROCS in a random data set comprised of 1000 compounds. It was also examined if EON could find any electrostatic similarities between the queries and the markers. The performance of FRED with respect to re-generation of bound ligand modes was examined on ten different protein/ligand complexes from the Brookhaven Protein Data Bank. It was also examined if FRED is suitable as a screening tool since several other docking methods are used in such a way. Finally it was also examined if it was possible to reduce the time requirements of ROCS when running multiconformer queries by using a combination of single conformer queries coupled with multiconformer queries. The conclusions that could be drawn from this project were that FRED is not a good screening tool, but ROCS performs well as such. It was also found that the scoring functions are the weak spots of FRED. EON is probably very sensitive to the conformers used but can in some cases strengthen the results from ROCS. A novel and simple way to reduce the time complexity with multiconformer queries to ROCS was discovered and was shown to work well.

<p>The process of drug discovery is very slow and expensive. There is a need for reliable in silico methods; however the performance of these methods differs.</p><p>This work presents a targeted study on how the drug discovery methods used in OpenEye’s tools ROCS, EON and FRED perform on targets with small ligands. It was examined if 12 compounds (markers) somewhat similar to AMP could be detected by ROCS in a random data set comprised of 1000 compounds. It was also examined if EON could find any electrostatic similarities between the queries and the markers. The performance of FRED with respect to re-generation of bound ligand modes was examined on ten different protein/ligand complexes from the Brookhaven Protein Data Bank. It was also examined if FRED is suitable as a screening tool since several other docking methods are used in such a way. Finally it was also examined if it was possible to reduce the time requirements of ROCS when running multiconformer queries by using a combination of single conformer queries coupled with multiconformer queries.</p><p>The conclusions that could be drawn from this project were that FRED is not a good screening tool, but ROCS performs well as such. It was also found that the scoring functions are the weak spots of FRED. EON is probably very sensitive to the conformers used but can in some cases strengthen the results from ROCS. A novel and simple way to reduce the time complexity with multiconformer queries to ROCS was discovered and was shown to work well.</p>

No capítulo 1, a modelagem HQSAR, a docagem e os estudos de ROCS foram construídos utilizando uma série de 57 inibidores de cruzaína. O melhor modelo HQSAR (q2 = 0,70, r2 = 0,95, r2test = 0,62, q2rand. = 0,09 and r2rand. = 0,26) foi utilizado para predizer a potência de 121 compostos extraídos da literatura (conjunto de dados V1), resultando em um valor de r2 satisfatório de 0,65 para essa validação externa. Uma validação externa adicional foi empregada utilizando uma série de 1223 compostos extraído dos bancos de dados ChEMBL e CDD (conjunto de dados V3); nessa validação externa o valor de AUC (área sob a curva) para a curva ROC foi de 0,70. Os mapas de contribuição, obtidos para o melhor modelo HQSAR 3.4, estão de acordo com as predições do modo de interação e com as bioatividades dos compostos estudados. Nos estudos de ROCS, a forma molecular utilizada como filtro, foi útil na rápida identificação de modificações moleculares promissoras para inibidores de cruzaína. O valor de AUC obtido com a curva ROC foi de 0,72, isso indica que o método foi muito eficiente na distinção entre inibidores ativos e inativos da enzima cruzaína. Em seguida, o melhor modelo HQSAR foi utilizado para predizer os valores de pIC50 para novos compostos. Alguns dos compostos identificados, utilizando esse método, demonstraram valores de potência calculada maior do que a série de treinamento em estudo. No capítulo 2, os efeitos sobre a potência na inibição da enzima cruzaína pela substituição de um grupo nitrila como warhead por outros grupos foi avaliada. Com a síntese de 20 compostos do tipo dipeptidil, avaliou-se a relação estrutura-atividade (SAR), baseado na troca do grupo warhead na porção P1\'. O grupo oxima foi mais potente que o grupo correspondente nitrila em 0,7 unidades logarítmicas. Os compostos do tipo dipeptidil aldeídos e azanitrila obtiveram potências mais elevadas do que o correspondente dipeptidil nitrila em duas de magnitude. Os compostos dipeptidil alfa-beta insaturados foram menos potentes do que o correspondente dipeptidil nitrila. No capítulo 3, estratégias de química medicinal foram empregadas nas sínteses de 23 novos análogos, contendo o esqueleto básico de imidazopiridina. Sete e doze compostos sintetizados exibiram EC50 <= 1µM in vitro contra os parasitos Tripanosoma cruzi (T. cruzi) e brucei (T. brucei), respectivamente. Com os resultados promissores de atividade biológica in vitro, citotoxicidade, estabilidade metabólica, ligação proteica e propriedades farmacocinéticas, o composto 41 foi selecionado como candidato para os estudos de eficácia in vivo. Esse composto foi submetido em um modelo agudo da infecção com T. cruzi em ratos (cepa Tulahuen). Depois de estabelecida a infecção, os ratos foram dosados duas vezes ao dia, durante 5 dias; e monitorados por 6 semanas usando um sistema de imagem in vivo IVIS (do inglês, \"In Vivo Imaging System\"). O composto 41 demonstrou inibição parasitária comparável com o grupo de treinamento dosado com benzonidazol. O composto 41 representa um potencial líder para o desenvolvimento de novos fármacos para o tratamento de tripanossomíases. / In chapter 1, the HQSAR, molecular docking and ROCS were applied to a dataset of 57 cruzain inhibitors. The best HQSAR model (q2 = 0.70, r2 = 0.95, r2test = 0.62, q2rand. = 0.09 and r2rand. = 0.26) was then used to predict the potencies of 121 unknown compounds (the V1 database), giving rise to a satisfactory predictive r2 value of 0.65 (external validation). By employing an extra external dataset comprising 1223 compounds (the V3 database) either retrieved from the ChEMBL or CDD databases, an overall ROC AUC (area under the curve) score well over 0.70 was obtained. The contribution maps obtained with the best HQSAR model (model 3.4) are in agreement with the predicted binding mode and with the biological potencies of the studied compounds. We also screened these compounds using the ROCS method, a Gaussian-shape volume filter able to identify quickly the shapes that match a query molecule. The AUC obtained with the ROC curves (ROC AUC) was 0.72, indicating that the method was very efficient in distinguishing between active and inactive cruzain inhibitors. These set of information guided us to propose novel cruzain inhibitors to be synthesized. Then, the best HQSAR model obtained was used to predict the pIC50 values of these new compounds. Some compounds identified using this method has shown calculated potencies higher than those which have originated them. In chapter 2, the effects on potency of cruzain inhibition of replacing a nitrile group with alternative warheads were explored; with the syntheses of 20 dipeptidyl compounds, we explored the structure activity relationships (SAR) based on exchanging of the warhead portion (P1\'). The oxime was 0.7 units more potent than the corresponding nitrile. Dipeptide aldehydes and azadipeptide nitriles were found to be two orders of magnitude more potent than the corresponding dipeptide nitriles. The vinyl esters and amides were less potent than the corresponding nitrile by between one and two orders of magnitude. In chapter 3, we synthesized 23 new imidazopyridine analogues arising from medicinal chemistry optimization at different sites on the molecule. Seven and twelve compounds exhibited an in vitro EC50 <= 1µM against Trypanosoma cruzi (T. cruzi) and Trypanosoma brucei (T. brucei) parasites, respectively. Based on promising results of in vitro activity (EC50 &lt; 100 nM), cytotoxicity, metabolic stability, protein binding and pharmacokinetics (PK) properties, compound 41 was selected as a candidate for in vivo efficacy studies. This compound was screened in an acute mouse model against T.cruzi (Tulahuen strain). After established infection, mice were dosed twice a day for 5 days, and then monitored for 6 weeks using an in vivo imaging system (IVIS). Compound 41 demonstrated parasite inhibition comparable to the benznidazole treatment group. Compound 41 represents a potential lead for the development of drugs to treat trypanosomiasis.

No capítulo 1, a modelagem HQSAR, a docagem e os estudos de ROCS foram construídos utilizando uma série de 57 inibidores de cruzaína. O melhor modelo HQSAR (q2 = 0,70, r2 = 0,95, r2test = 0,62, q2rand. = 0,09 and r2rand. = 0,26) foi utilizado para predizer a potência de 121 compostos extraídos da literatura (conjunto de dados V1), resultando em um valor de r2 satisfatório de 0,65 para essa validação externa. Uma validação externa adicional foi empregada utilizando uma série de 1223 compostos extraído dos bancos de dados ChEMBL e CDD (conjunto de dados V3); nessa validação externa o valor de AUC (área sob a curva) para a curva ROC foi de 0,70. Os mapas de contribuição, obtidos para o melhor modelo HQSAR 3.4, estão de acordo com as predições do modo de interação e com as bioatividades dos compostos estudados. Nos estudos de ROCS, a forma molecular utilizada como filtro, foi útil na rápida identificação de modificações moleculares promissoras para inibidores de cruzaína. O valor de AUC obtido com a curva ROC foi de 0,72, isso indica que o método foi muito eficiente na distinção entre inibidores ativos e inativos da enzima cruzaína. Em seguida, o melhor modelo HQSAR foi utilizado para predizer os valores de pIC50 para novos compostos. Alguns dos compostos identificados, utilizando esse método, demonstraram valores de potência calculada maior do que a série de treinamento em estudo. No capítulo 2, os efeitos sobre a potência na inibição da enzima cruzaína pela substituição de um grupo nitrila como warhead por outros grupos foi avaliada. Com a síntese de 20 compostos do tipo dipeptidil, avaliou-se a relação estrutura-atividade (SAR), baseado na troca do grupo warhead na porção P1\'. O grupo oxima foi mais potente que o grupo correspondente nitrila em 0,7 unidades logarítmicas. Os compostos do tipo dipeptidil aldeídos e azanitrila obtiveram potências mais elevadas do que o correspondente dipeptidil nitrila em duas de magnitude. Os compostos dipeptidil alfa-beta insaturados foram menos potentes do que o correspondente dipeptidil nitrila. No capítulo 3, estratégias de química medicinal foram empregadas nas sínteses de 23 novos análogos, contendo o esqueleto básico de imidazopiridina. Sete e doze compostos sintetizados exibiram EC50 <= 1µM in vitro contra os parasitos Tripanosoma cruzi (T. cruzi) e brucei (T. brucei), respectivamente. Com os resultados promissores de atividade biológica in vitro, citotoxicidade, estabilidade metabólica, ligação proteica e propriedades farmacocinéticas, o composto 41 foi selecionado como candidato para os estudos de eficácia in vivo. Esse composto foi submetido em um modelo agudo da infecção com T. cruzi em ratos (cepa Tulahuen). Depois de estabelecida a infecção, os ratos foram dosados duas vezes ao dia, durante 5 dias; e monitorados por 6 semanas usando um sistema de imagem in vivo IVIS (do inglês, \"In Vivo Imaging System\"). O composto 41 demonstrou inibição parasitária comparável com o grupo de treinamento dosado com benzonidazol. O composto 41 representa um potencial líder para o desenvolvimento de novos fármacos para o tratamento de tripanossomíases. / In chapter 1, the HQSAR, molecular docking and ROCS were applied to a dataset of 57 cruzain inhibitors. The best HQSAR model (q2 = 0.70, r2 = 0.95, r2test = 0.62, q2rand. = 0.09 and r2rand. = 0.26) was then used to predict the potencies of 121 unknown compounds (the V1 database), giving rise to a satisfactory predictive r2 value of 0.65 (external validation). By employing an extra external dataset comprising 1223 compounds (the V3 database) either retrieved from the ChEMBL or CDD databases, an overall ROC AUC (area under the curve) score well over 0.70 was obtained. The contribution maps obtained with the best HQSAR model (model 3.4) are in agreement with the predicted binding mode and with the biological potencies of the studied compounds. We also screened these compounds using the ROCS method, a Gaussian-shape volume filter able to identify quickly the shapes that match a query molecule. The AUC obtained with the ROC curves (ROC AUC) was 0.72, indicating that the method was very efficient in distinguishing between active and inactive cruzain inhibitors. These set of information guided us to propose novel cruzain inhibitors to be synthesized. Then, the best HQSAR model obtained was used to predict the pIC50 values of these new compounds. Some compounds identified using this method has shown calculated potencies higher than those which have originated them. In chapter 2, the effects on potency of cruzain inhibition of replacing a nitrile group with alternative warheads were explored; with the syntheses of 20 dipeptidyl compounds, we explored the structure activity relationships (SAR) based on exchanging of the warhead portion (P1\'). The oxime was 0.7 units more potent than the corresponding nitrile. Dipeptide aldehydes and azadipeptide nitriles were found to be two orders of magnitude more potent than the corresponding dipeptide nitriles. The vinyl esters and amides were less potent than the corresponding nitrile by between one and two orders of magnitude. In chapter 3, we synthesized 23 new imidazopyridine analogues arising from medicinal chemistry optimization at different sites on the molecule. Seven and twelve compounds exhibited an in vitro EC50 <= 1µM against Trypanosoma cruzi (T. cruzi) and Trypanosoma brucei (T. brucei) parasites, respectively. Based on promising results of in vitro activity (EC50 &lt; 100 nM), cytotoxicity, metabolic stability, protein binding and pharmacokinetics (PK) properties, compound 41 was selected as a candidate for in vivo efficacy studies. This compound was screened in an acute mouse model against T.cruzi (Tulahuen strain). After established infection, mice were dosed twice a day for 5 days, and then monitored for 6 weeks using an in vivo imaging system (IVIS). Compound 41 demonstrated parasite inhibition comparable to the benznidazole treatment group. Compound 41 represents a potential lead for the development of drugs to treat trypanosomiasis.

Avec le besoin croissant en bande-passante, les technologies dites de radio-cognitive sont de plus en plus étudiées par la communauté scientifique. L’enjeu est d’utiliser au mieux le spectre disponible. L'une de ces technologies, Transform Domain Communication System (TDCS), dont les performances en termes d’efficacité énergétique et spectrale étaient jusqu'à présent méconnues, constitue le sujet d'étude de cette thèse. Après une présentation du contexte scientifique et industriel de la thèse, le système TDCS est introduit, ainsi que ses similarités et différences avec OFDM et MC-CDMA. Le système est ensuite décrit sous le formalisme algébrique des modulations linaires. Cela a permis d’établir une expression de l’efficacité spectrale du système. Plusieurs techniques sont alors proposées pour améliorer celle-ci tout en améliorant, dans certains cas, le taux d’erreur binaire. Étant composé d’un de plusieurs composantes sinusoïdales, le signal TDCS souffre d’un fort Peak-to-Average Power Ratio (PAPR). La théorie ensembliste est alors présentée puis mise à profit en troisième partie de cette thèse pour proposer les algorithmes Douglas-Rachford et ROCS de réduction du PAPR des signaux TDCS. Ces algorithmes convergent plus rapidement et vers des valeurs plus basses que l’algorithme POCS précédemment utilisé dans la littérature / For about ten years, spectrum scarcity and the growing need of bandwidth have pushed the studies on cognitive-radio technologies to counter this waste. Among them: the Transform Domain Communication System (TDCS), on which this thesis focuses. Until now, TDCS’ performance in terms of spectral and power efficiency was largely unknown. After introducing the thesis’ industrial and scientific context, the TDCS is introduced and compared with popular technologies such as OFDM and MC-CDMA. The system is then studied by means of the linear modulations’ algebraic framework. This has led to the TDCS’ spectral efficiency determination and to new design rules to jointly achieve a better spectral efficiency and a lower BER. Several methods are then proposed to further increase the spectral efficiency by means of a dense multidimensional modulation. Since a TDCS signal is made of several sines, it suffers from a strong Peak-to-Average Power Ratio (PAPR). Set theoretic estimation is then introduced in a third part and new PAPR-reduction algorithms such as Douglas-Rachford and Reflection Onto Convex Sets are brought to light and achieve better performance than the usual POCS algorithm regarding to the convergence rate, as well as the achieved PAPR

This thesis contains three main sections. In the first section, we examine methodologies to discriminate Type II protein kinase inhibitors from the Type I inhibitors. We have studied the structure of 55 Type II kinase inhibitors and have notice specific descriptive geometric features. Using this information we have developed a pharmacophore and a shape based screening approach. We have found that these methods did not effectively discriminate between the two inhibitor types used independently, but when combined in a consecutive way – pharmacophore search first, then shape based screening, we have found a method that successfully filtered out all Type I molecules. The effect of protonation states and using different conformer generators were studied as well. This method was then tested on a freely available database of decoy molecules and again shown to be discriminative. In the second section of the thesis, we implement and assess swarm-based docking methods. We implement a repulsive particle swarm optimization (RPSO) based conformational search approach into Autodock 3.05. The performance of this approach with different parameters was then tested on a set of 51 protein ligand complexes. The effect of using different factoring for the cognitive, social and repulsive terms and the importance of the inertia weight were explored. We found that the RPSO method gives similar performance to the particle swarm optimization method. Compared to the genetic algorithm approach used in Autodock 3.05, our RPSO method gives better results in terms of finding lower energy conformations. In the final, third section we have implemented a Monte Carlo (MC) based conformer searching approach into Gaussian03. This enables high level quantum mechanics/molecular mechanics (QM/MM) potentials to be used in docking molecules in a protein active site. This program was tested on two Zn2+ ion-containing complexes, carbonic anhydrase II and cytidine deaminase. The effects of different QM region definitions were explored in both systems. A consecutive and a parallel docking approach were used to study the volume of the active site explored by the MC search algorithm. In case of the carbonic anhydrase II complex, we have used 1,2-difluorobenzene as a ligand to explore the favourable interactions within the binding site. With the cytidine deaminase complex, we have evaluated the ability of the approach to discriminate the native pose from other higher energy conformations during the exploration of the active site of the protein. We find from our initial calculations, that our program is able to perform a conformational search in both cases, and the effect of QM region definition is noticeable, especially in the description of the hydrophobic interactions within the carbonic anhydrase II system. Our approach is also able to find poses of the cytidine deaminase ligand within 1 Å of the native pose.

Standard IEC 61850-9-2 definuje přenos vzorkovaných měřených hodnot (sampled measured values, SMV) prostřednictvím sítě Ethernet a využití SMV získaných ze slučovacích jednotek nebo přístrojových transformátorů. Implementace IEC 61850-9-2 závisí na vlastnostech datového souboru, jakými jsou časová synchronizace, počet vzorků a časový interval. Dizertační práce je zaměřena na algoritmy chránění a analýzu vlivu standardu IEC61850-9-2LE na fyzická zařízení ochran s analogově/digitálními vstupními daty o proudu a napětí. S ohledem na narůstající míru interakce mezi fyzickými zařízeními a komunikačními prvky byl navržen test pro analýzu komunikace pro rozvodnu využívající konvenční metody (analogové vstupy) a metody digitální založené na standardu IEC 61850-9-2. Práce dále popisuje funkci slučovací jednotky využívající standard IEC61850-9-2LE. Navržená metoda definuje zdroj SMV a analyzuje přenos dat. V rámci práce byl za využití softwaru Matlab naprogramován algoritmus ochrany. Vytvořený model je schopen vyhodnotit vliv harmonického zkreslení na funkci digitálních ochran a vliv přesycení proudového transformátoru na distanční ochranu. V práci jsou zhodnoceny i možnosti zrychlení testování systémů chránění s využitím neuronové sítě. Závěrečná kapitola se zabývá aplikacemi v reálném čase, využívajícími data z rozvodny v blízkosti Vysokého učení technického v Brně. K přenosu dat z rozvodny do univerzitní laboratoře je zde využíváno SMV přenášených optickým kabelem o délce 16 km. Aplikace je vytvořena v programu Matlab a je schopna číst data z ethernetového portu, dekódovat je, převést z formátu ASCII do desítkové soustavy a poté vykreslit průběhy proudu a napětí. Mezi vlastnosti aplikace se řadí jednoduchost použití, schopnost implementace funkcí distanční ochrany, výpočet RMS hodnot proudu a napětí a harmonického zkreslení, harmonická analýza prostřednictvím rychlé Fourierovy transformace a výpočet impedance poruchové smyčky. Všechny výpočty běží v reálném čase a provedena je i citlivostní analýza modelu.