The current project examined the ability of a novel series of guandine and amidine-containing nicotine analogs to interact with several native and recombinantlyexpressed mammalian neuronal nicotinic-acetylcholine receptor (nAChR) subtypes. Rational drug design methods and parallel organic synthesis was used to generate a library of guanidine-containing nicotine (NIC) analogs (AH compounds). A smaller series of amidine-containing nicotine analogs (JC compounds) were also synthesized. In total, >150 compounds were examined. Compounds were first assayed for affinity in a high-throughput [3H]epibatidine radioligand-binding screen. Lead compounds were evaluated in subtype-selective binding experiments to probe for affinity at the α4β2* and α7* neuronal nAChRs. Several compounds were identified which possess affinity and selectivity for the α4β2* subtype [AH-132 (Ki=27nm) and JC-3-9 (Ki=11nM)]. Schild analysis of binding suggests a complex one-site binding interaction at the desensitized high-affinity nAChR. Whole-cell functional fluorescence (FLIPR) assays revealed mixed subtype pharmacology. AH-compounds were identified which act as activators and inhibitors at nAChR subtypes, while lead JC-compounds were found which possess full agonist activity at α4β2* and α3β4* subtypes. Compounds were identified as partial agonists, full agonists and inhibitors of multiple nAChR subtypes. Several SAR-based, ligand-receptor pharmacophore models were developed to guide future ligand design. Second-generation lead compounds were identified.

Of the seven existing classes of serotonin receptors, the 5-HT7 receptors (5-HT7Rs) are the most recently discovered. Abundance of 5-HT7 in the central nervous system is suggestive of the receptor’s role in several physiological and pathophysiological functions. Existing research has afforded a number of compounds exhibiting specific affinity to the receptor. These selective ligands can provide structural information about the receptor and can serve as the foundation for pharmacological profiling . This thesis describes the synthesis of substituted pyrimidines and pyridines for affinity to the 5-HT7 receptor. Organometallic species are the cornerstone for sev-eral of the synthetic pathways.

Signal transducer and activator of transcription 3 (STAT3) is a cancer-driving proto-oncoprotein that represents a novel target for the development of chemotherapeutics. In this study, the functional requirements to furnish a potent STAT3 inhibitor was investigated. First, a series of peptidomimetic inhibitors were rationally designed from lead parent peptides. Prepared peptidomimetics overcame the limitations normally associated with peptide agents and displayed improved activity in biophysical evaluations. Notably, lead peptidomimetic agents possessed micromolar cellular activity which was unobserved in both parent peptides. Peptidomimetic design relied on computational methods that were also employed in the design of purine based STAT3 inhibitory molecules. Docking studies with lead STAT3-SH2 domain inhibitory molecules identified key structural and chemical information required for the construction of a pharmacophore model. 2,6,9-heterotrisubstituted purines adequately fulfilled the pharmacophore model and a library of novel purine-based STAT3 inhibitory molecules was prepared utilizing Mitsunobu chemistry. Several agents from this new library displayed high affinity for the STAT3 protein and effectively disrupted the STAT3:STAT3-DNA complex. Furthermore, these agents displayed cancer-cell specific toxicity through a STAT3 dependant mechanism. While purine agents elicited cellular effects, the dose required for cellular efficacy was much higher than those observed for in vitro STAT3 dimer disruption. The diminished cellular activity could be attributed to the apparent poor cell permeability of the first generation purine library; thus, a second library of purine molecules was constructed to improve cell penetration. Unfortunately, iii 2nd generation purine inhibitors failed to disrupt phosphorylated STAT3 activity and suffered from poor cell permeability. However, a lead sulfamate agent was discovered that showed potent activity against multiple myeloma cancer cells. Investigations revealed potential kinase inhibitory activity as the source of the sulfamate purine’s biological effect. Explorations into the development of a potent STAT3 SH2 domain binder, including the creation of salicylic purine and constrained pyrimidine molecules, are ongoing. Finally, progress towards the creation of a macrocyclic purine combinatorial library has been pursued and is reported herein.

Signal transducer and activator of transcription 3 (STAT3) is a cancer-driving proto-oncoprotein that represents a novel target for the development of chemotherapeutics. In this study, the functional requirements to furnish a potent STAT3 inhibitor was investigated. First, a series of peptidomimetic inhibitors were rationally designed from lead parent peptides. Prepared peptidomimetics overcame the limitations normally associated with peptide agents and displayed improved activity in biophysical evaluations. Notably, lead peptidomimetic agents possessed micromolar cellular activity which was unobserved in both parent peptides. Peptidomimetic design relied on computational methods that were also employed in the design of purine based STAT3 inhibitory molecules. Docking studies with lead STAT3-SH2 domain inhibitory molecules identified key structural and chemical information required for the construction of a pharmacophore model. 2,6,9-heterotrisubstituted purines adequately fulfilled the pharmacophore model and a library of novel purine-based STAT3 inhibitory molecules was prepared utilizing Mitsunobu chemistry. Several agents from this new library displayed high affinity for the STAT3 protein and effectively disrupted the STAT3:STAT3-DNA complex. Furthermore, these agents displayed cancer-cell specific toxicity through a STAT3 dependant mechanism. While purine agents elicited cellular effects, the dose required for cellular efficacy was much higher than those observed for in vitro STAT3 dimer disruption. The diminished cellular activity could be attributed to the apparent poor cell permeability of the first generation purine library; thus, a second library of purine molecules was constructed to improve cell penetration. Unfortunately, iii 2nd generation purine inhibitors failed to disrupt phosphorylated STAT3 activity and suffered from poor cell permeability. However, a lead sulfamate agent was discovered that showed potent activity against multiple myeloma cancer cells. Investigations revealed potential kinase inhibitory activity as the source of the sulfamate purine’s biological effect. Explorations into the development of a potent STAT3 SH2 domain binder, including the creation of salicylic purine and constrained pyrimidine molecules, are ongoing. Finally, progress towards the creation of a macrocyclic purine combinatorial library has been pursued and is reported herein.

Submitted by Ricardo Cedraz Duque Moliterno (ricardo.moliterno@uefs.br) on 2017-08-08T21:31:24Z No. of bitstreams: 1 TESE_Odailson Paz - com ficha.pdf: 4071411 bytes, checksum: 033f0c18eb721e7010e1ddd7ec27e10c (MD5) / Made available in DSpace on 2017-08-08T21:31:24Z (GMT). No. of bitstreams: 1 TESE_Odailson Paz - com ficha.pdf: 4071411 bytes, checksum: 033f0c18eb721e7010e1ddd7ec27e10c (MD5) Previous issue date: 2017-05-25 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior - CAPES / Adenosine receptors are considered as potential targets for the development of drugs against different pathologies because they are involved in several physiological pathways. Due to the role of adenosine receptors of subtype 2B (RA2B) in the process of sickling cell, antagonists capable of blocking RA2B may be lead compounds for the development of new therapeutic alternatives to treatment of patients with sickle cell anemia. Then, the objective of this work was to identify anti-sickle cell agents capable of blocking RA2B activity. To achieve this goal, was built a pharmacophore model (model 04) capable of differentiating true ligands false-positive (area under the ROC curve = 0.94) and to classify RA2B antagonists, not used in the calibration of the model, regarding their Biological activities pKi = 7.5-9.3 (high potency), 5.5-7.4 (intermediate potency) and 5.4-4.0 (low potency). This pharmacophore model allowed the selection of 33 lead-like compounds from the ZINC database, between them12 compounds presented anti-sickle cell activity. In vitro cell assay with an agonist (NECA) and a RA2B antagonist (MRS1754), suggest that the anti-sickle cell activity is related to modulation of RA2B. Compounds Z1139491704 (pEC50= 7,77?0,17), Z168278894 (pEC50= 7,64?0,09) e Z847449186 (pEC50= 7,66?0,21) have anti-sickling activity Higher than MRS1754 (pEC50= 7,63?0,12) and do not present cytotoxic activity at micromolar range. In sum, it can be concluded that the in silico strategy used succeeded in identifying compounds with probable action antagonists of RA2B that can be considered as prototypes for the development of drugs useful in the treatment of patients with sickle cell anemia. / Os receptores de adenosina s?o considerados como alvos potenciais para o desenvolvimento de f?rmacos contra diferentes patologias por estarem envolvidos em diversas vias fisiol?gicas. Devido ao papel dos receptores de adenosina do subtipo 2B (RA2B) no processo de falciza??o de hem?cias, antagonistas capazes de bloquear RA2B podem ser compostos prot?tipos para o desenvolvimento de novas alternativas terap?uticas para o tratamento de pacientes com anemia falciforme.Diante desse cen?rio, o objetivo desse trabalho foi identificar agentes antifalcizantes capazes de antagonizar a atividade do RA2B. Para alcan?ar esse objetivo foi constru?do um modelo farmacof?rico (modelo 04 - 3 caracter?sticas aceptor e 1 doador de liga??o de hidrog?nio e 3 centros hidrof?bicos) que ? capaz de diferenciar ligantes verdadeiros de falso-positivos (?rea sob a curva ROC= 0,94)e classificar antagonistas de RA2B,n?o utilizados na calibra??o do modelo, quanto as suas atividades biol?gicas(pKi= 7,5-9,3 (alta pot?ncia), 5,5-7,4 (pot?ncia intermedi?ria) e 5,4-4,0 (baixa pot?ncia)). Esse modelo farmacof?rico permitiu a sele??o de 33 compostos lead like do banco de dados ZINC database para avalia??o biol?gica, dos quais 12 apresentaram atividade antifalcizante.Testes in vitro com um agonista (NECA) e um antagonista de RA2B (MRS1754), sugerem que a atividade antifalcizante est? relacionada a modula??o de RA2B.Os compostosZ1139491704(pEC50= 7,77?0,17),Z168278894 (pEC50= 7,64?0,09) e Z847449186 (pEC50= 7,66?0,21)possuem atividade antifalcizante superior ao MRS1754 (pEC50=7,63?0,12)e n?o apresentam atividade citot?xica em concentra??es micromolares. Dessa forma, pode-se concluir que a estrat?gia in silico utilizada logrou sucesso em identificar compostos com prov?vel a??o antagonistas de RA2B que podem ser considerados como prot?tipos para o desenvolvimento de f?rmacos ?teis no tratamento de pacientes com anemia falciforme.

Com o objetivo de buscar e identificar novo(s) inibidor(es) da cruzaína uma cisteíno-protease do Trypanosoma cruzi, o agente etiológico da doença de Chagas foram propostos, validados e, a seguir, aplicados sobre a biblioteca de compostos ZINC (3.294.714 compostos), dois modelos de virtual screening (Modelos I e II). Os modelos de virtual screening propostos, contendo seqüências de filtros físicoquímicos, farmacofóricos, de docking e de seleção por inspeção visual, foram construídos a partir de informações de 13 complexos da cruzaína e de 20 complexos de outras cisteínoprotease, cujas estruturas estão disponíveis no PDB. Numa primeira etapa, o reconhecimento detalhado das características estruturais da cruzaína foi realizado por inspeção visual; pelos campos de interação molecular, gerados pelo programa GRID; pela identificação das propriedades de interação molecular na superfície da cavidade, geradas pelo programa CA VBASE e; por simulações de dinâmica molecular. O Modelo I de virtual screeníng - obtido a partir do reconhecimento das estruturas dos 13 complexos da cruzaína depositadas no PDB - foi aplicado sobre o ZINC, selecionando 10 compostos, dos quais 6 compostos foram adquiridos e submetidos ao teste de inibição enzimática da cruzaína, para a validação experimental do modelo. Observou-se que 3 destes compostos (ZINC02470662, ZINC02682879 e ZINC03192044, respectivamente) não mostraram inibição significativa da cruzaína, nas condições experimentais utilizadas, até a concentração de 7 mM, enquanto que os 3 restantes (ZINC02663001, ZINC01936854 e ZINC03326243, respectivamente) apresentaram inibição enzimática inespecífica, sugerindo que estes últimos agem pelo mecanismo promíscuo. O mecanismo promíscuo de inibição enzimática, foi verificado pela adição de 0,1% Triton X-100 no ensaio enzimático, observando-se a correspondente perda de inibição da cruzaína. Para estes compostos, a confirmação do mecanismo promíscuo foi feita observando-se a perda de inibição da enzima, após o aumento em dez vezes da concentração da cruzaína no ensaio enzimático. O Modelo II - obtido a partir do reconhecimento das estruturas dos 13 complexos da cruzaína e dos 20 complexos de outras cisteíno-proteases, identificadas na busca por cavidades similares à cruzaína - foi aplicado sobre o banco de dados ZINC,selecionando 55 compostos dos quais 19 foram adquiridos e submetidos ao teste de inibição enzimática da cruzaína, para validação experimental do modelo. Observou-se que o composto ZINC01794422 apresentou inibição específica da enzima com constante de inibição no valor de Ki = 21 µM, enquanto que os demais 18 compostos não mostraram inibição significativa, nas condições experimentais utilizadas, até a concentração de 592 µM. O mecanismo promíscuo de inibição enzimática não foi observado, uma vez que todos os testes foram realizados com 0,1% de Triton X-100. O Modelo II identificou, ainda, mais dois inibidores da cruzaína (ZINC04899534 e ZINC01547017) que, por serem estruturalmente semelhantes aos utilizados na construção do modelo e já terem sido descritos na literatura, não foram adquiridos ou testados nos ensaios enzimáticos. Considerando apenas o novo inibidor identificado, o Modelo II apresentou uma taxa de acerto de 5,3%. Este valor esta de acordo com as taxas de acerto encontradas na literatura que variam entre 1 a 50% . / In order to search and identify new cruzain inhibitor(s) - a cysteine-protease of Trypanosoma cruzi, the etiologic agent of Chagas disease - two virtual screening schemes(Models I and II) were proposed, validated- and applied to the ZINC database (3.294.714 compounds). The proposed virtual screening models, bearing a sequence of different physicalchemical, pharmacophore and docking filters, as well as a visual inspection filter, were built from information taken from 13 cruzain complexes and from 20 complexes of other cysteine proteases, having their structures available in PDB. In a first step, a detailed recognition of the cruzain structural features and characteristics was performed through visual inspection of the enzyme environment; followed by the analysis of GRID generated molecular interaction fields; through the identification of molecular interaction properties exposed at the enzyme cavity surface, generated by the CAVBASE program; and by molecular dynamics simulations. The virtual screening Model I, - generated from the structural characteristics recognized from 13 PDB cruzain complexes - when applied to the ZINC database selected 10 compounds. For the experimental validation ofthe model, six ofthese compounds have been acquired and were tested as cruzain inhibitors. It was observed that three of the tested compounds (ZINC02470662, ZINC02682879 and ZINC03192044, respectively) did not show any significant cruzain inhibition, up to 7 mM. Meanwhile the other three tested compounds (ZINC02663001, ZINC01936854 and ZINC03326243, respectively) showed an unspecific cruzain inhibition, suggesting that an enzyme inhibition by promiscuous mechanism occurred. This mechanism was verified by the addition of 0.1% Triton X-100 on the enzymatic assay with a concomitant loss of cruzain inhibition activity. For these compounds, the confirmation of the promiscuous mechanism was also done, observing the loss of enzyme inhibition, after a ten times increase in the cruzain concentration on the enzymatic assay. The virtual screenmg Model II - generated from the structural characteristics recognized from 13 cruzain complexes and 20 complexes of other cysteine proteases, that have been identified on a search for cavities similar to cruzain - selected 55 compounds, when applied to the ZINC database. In order to experimentally validate the model, nineteen compounds have been acquired and were tested as cruzain inhibitors. It has been observed that one compound, ZINC01794422, showed a specific cruzain inhibition (Ki = 21 µM), while the other eighteen showed no significant inhibition, up to 592 µM concentration. The promiscuous mechanism of enzymatic inhibition was not observed, since 0.1% of Triton X-100 was added in ali assays. Additionally, Model II identified two other cruzain inhibitors (ZINC04899534 and ZINC01547017). However, these compounds have not been acquired or tested, since they are known cruzain inhibitors - already described in the literature and are structurally similar to the inhibitors used in the construction of the mode!. Referring to new inhibitors found, Model II showed a hit rate of 5,3%. This value is in agreement with those found in the literature, which ranges from 1 to 50%.

Com o objetivo de buscar e identificar novo(s) inibidor(es) da cruzaína uma cisteíno-protease do Trypanosoma cruzi, o agente etiológico da doença de Chagas foram propostos, validados e, a seguir, aplicados sobre a biblioteca de compostos ZINC (3.294.714 compostos), dois modelos de virtual screening (Modelos I e II). Os modelos de virtual screening propostos, contendo seqüências de filtros físicoquímicos, farmacofóricos, de docking e de seleção por inspeção visual, foram construídos a partir de informações de 13 complexos da cruzaína e de 20 complexos de outras cisteínoprotease, cujas estruturas estão disponíveis no PDB. Numa primeira etapa, o reconhecimento detalhado das características estruturais da cruzaína foi realizado por inspeção visual; pelos campos de interação molecular, gerados pelo programa GRID; pela identificação das propriedades de interação molecular na superfície da cavidade, geradas pelo programa CA VBASE e; por simulações de dinâmica molecular. O Modelo I de virtual screeníng - obtido a partir do reconhecimento das estruturas dos 13 complexos da cruzaína depositadas no PDB - foi aplicado sobre o ZINC, selecionando 10 compostos, dos quais 6 compostos foram adquiridos e submetidos ao teste de inibição enzimática da cruzaína, para a validação experimental do modelo. Observou-se que 3 destes compostos (ZINC02470662, ZINC02682879 e ZINC03192044, respectivamente) não mostraram inibição significativa da cruzaína, nas condições experimentais utilizadas, até a concentração de 7 mM, enquanto que os 3 restantes (ZINC02663001, ZINC01936854 e ZINC03326243, respectivamente) apresentaram inibição enzimática inespecífica, sugerindo que estes últimos agem pelo mecanismo promíscuo. O mecanismo promíscuo de inibição enzimática, foi verificado pela adição de 0,1% Triton X-100 no ensaio enzimático, observando-se a correspondente perda de inibição da cruzaína. Para estes compostos, a confirmação do mecanismo promíscuo foi feita observando-se a perda de inibição da enzima, após o aumento em dez vezes da concentração da cruzaína no ensaio enzimático. O Modelo II - obtido a partir do reconhecimento das estruturas dos 13 complexos da cruzaína e dos 20 complexos de outras cisteíno-proteases, identificadas na busca por cavidades similares à cruzaína - foi aplicado sobre o banco de dados ZINC,selecionando 55 compostos dos quais 19 foram adquiridos e submetidos ao teste de inibição enzimática da cruzaína, para validação experimental do modelo. Observou-se que o composto ZINC01794422 apresentou inibição específica da enzima com constante de inibição no valor de Ki = 21 µM, enquanto que os demais 18 compostos não mostraram inibição significativa, nas condições experimentais utilizadas, até a concentração de 592 µM. O mecanismo promíscuo de inibição enzimática não foi observado, uma vez que todos os testes foram realizados com 0,1% de Triton X-100. O Modelo II identificou, ainda, mais dois inibidores da cruzaína (ZINC04899534 e ZINC01547017) que, por serem estruturalmente semelhantes aos utilizados na construção do modelo e já terem sido descritos na literatura, não foram adquiridos ou testados nos ensaios enzimáticos. Considerando apenas o novo inibidor identificado, o Modelo II apresentou uma taxa de acerto de 5,3%. Este valor esta de acordo com as taxas de acerto encontradas na literatura que variam entre 1 a 50% . / In order to search and identify new cruzain inhibitor(s) - a cysteine-protease of Trypanosoma cruzi, the etiologic agent of Chagas disease - two virtual screening schemes(Models I and II) were proposed, validated- and applied to the ZINC database (3.294.714 compounds). The proposed virtual screening models, bearing a sequence of different physicalchemical, pharmacophore and docking filters, as well as a visual inspection filter, were built from information taken from 13 cruzain complexes and from 20 complexes of other cysteine proteases, having their structures available in PDB. In a first step, a detailed recognition of the cruzain structural features and characteristics was performed through visual inspection of the enzyme environment; followed by the analysis of GRID generated molecular interaction fields; through the identification of molecular interaction properties exposed at the enzyme cavity surface, generated by the CAVBASE program; and by molecular dynamics simulations. The virtual screening Model I, - generated from the structural characteristics recognized from 13 PDB cruzain complexes - when applied to the ZINC database selected 10 compounds. For the experimental validation ofthe model, six ofthese compounds have been acquired and were tested as cruzain inhibitors. It was observed that three of the tested compounds (ZINC02470662, ZINC02682879 and ZINC03192044, respectively) did not show any significant cruzain inhibition, up to 7 mM. Meanwhile the other three tested compounds (ZINC02663001, ZINC01936854 and ZINC03326243, respectively) showed an unspecific cruzain inhibition, suggesting that an enzyme inhibition by promiscuous mechanism occurred. This mechanism was verified by the addition of 0.1% Triton X-100 on the enzymatic assay with a concomitant loss of cruzain inhibition activity. For these compounds, the confirmation of the promiscuous mechanism was also done, observing the loss of enzyme inhibition, after a ten times increase in the cruzain concentration on the enzymatic assay. The virtual screenmg Model II - generated from the structural characteristics recognized from 13 cruzain complexes and 20 complexes of other cysteine proteases, that have been identified on a search for cavities similar to cruzain - selected 55 compounds, when applied to the ZINC database. In order to experimentally validate the model, nineteen compounds have been acquired and were tested as cruzain inhibitors. It has been observed that one compound, ZINC01794422, showed a specific cruzain inhibition (Ki = 21 µM), while the other eighteen showed no significant inhibition, up to 592 µM concentration. The promiscuous mechanism of enzymatic inhibition was not observed, since 0.1% of Triton X-100 was added in ali assays. Additionally, Model II identified two other cruzain inhibitors (ZINC04899534 and ZINC01547017). However, these compounds have not been acquired or tested, since they are known cruzain inhibitors - already described in the literature and are structurally similar to the inhibitors used in the construction of the mode!. Referring to new inhibitors found, Model II showed a hit rate of 5,3%. This value is in agreement with those found in the literature, which ranges from 1 to 50%.