An earlier approach to restore homeostatic levels of ECM degrading matrix metalloproteases (MMPs) by the Sefton Lab utilized hydroxamate-based MMP inhibitory (MI) beads. While the MI beads delayed ECM degradation in the context of skin wound healing, they caused elevated cell infiltration in a subcutaneous implant model. The primary goal of this project was to further investigate this finding using an air pouch implant model in mice and a different control group – methacrylic acid-based (MAA) beads. Exudate analysis indicated that the MI beads, implanted subcutaneously with gelatin discs, elicited a similar biological response as the MAA beads. Exudates corresponding to both biomaterials had similar cell counts and chemokine levels, which were greater than those corresponding to the control used earlier, poly-methyl methacrylate-based (PMMA) beads. Further, both MI and MAA beads activated infiltrating macrophages in the classical manner, and influenced the activity of an MMP8 catalytic domain in a similar manner.

An earlier approach to restore homeostatic levels of ECM degrading matrix metalloproteases (MMPs) by the Sefton Lab utilized hydroxamate-based MMP inhibitory (MI) beads. While the MI beads delayed ECM degradation in the context of skin wound healing, they caused elevated cell infiltration in a subcutaneous implant model. The primary goal of this project was to further investigate this finding using an air pouch implant model in mice and a different control group – methacrylic acid-based (MAA) beads. Exudate analysis indicated that the MI beads, implanted subcutaneously with gelatin discs, elicited a similar biological response as the MAA beads. Exudates corresponding to both biomaterials had similar cell counts and chemokine levels, which were greater than those corresponding to the control used earlier, poly-methyl methacrylate-based (PMMA) beads. Further, both MI and MAA beads activated infiltrating macrophages in the classical manner, and influenced the activity of an MMP8 catalytic domain in a similar manner.

No description available.

This thesis covers a range of methodologies to provide an account of the current (2010-2014) state of the art and to develop new methods for solubility prediction. We focus on predictions of intrinsic aqueous solubility, as this is a measure commonly used in many important industries including the pharmaceutical and agrochemical industries. These industries require fast and accurate methods, two objectives which are rarely complementary. We apply machine learning in chapters 4 and 5 suggesting methodologies to meet these objectives. In chapter 4 we look to combine machine learning, cheminformatics and chemical theory. Whilst in chapter 5 we look to predict related properties to solubility and apply them to a previously derived empirical equation. We also look at ab initio (from first principles) methods of solubility prediction. This is shown in chapter 3. In this chapter we present a proof of concept work that shows intrinsic aqueous solubility predictions, of sufficient accuracy to be used in industry, are now possible from theoretical chemistry using a small but diverse dataset. Chapter 6 provides a summary of our most recent research. We have begun to investigate predictions of sublimation thermodynamics. We apply quantum chemical, lattice minimisation and machine learning techniques in this chapter. In summary, this body of work concludes that currently, QSPR/QSAR methods remain the current state of the art for solubility prediction, although it is becoming possible for purely theoretical methods to achieve useful predictions of solubility. Theoretical chemistry can offer little useful additional input to informatics models for solubility predictions. However, theoretical chemistry will be crucial for enriching our understanding of the solvation process, and can have a beneficial impact when applied to informatics predictions of properties related to solubility.

Biologically active peptides are important for many physiological functions in the human body and therefore serve as interesting starting points in drug discovery processes. In this work the neuropeptide substance P 1–7 (SP1–7, H-Arg-Pro-Lys-Pro-Gln-Gln-Phe-OH), which has been demonstrated to reduce neuropathic pain and attenuate opioid withdrawal symptoms in animal models, has been addressed in a medicinal chemistry program with the overall aim of transforming this bioactive peptide into more drug-like compounds. Specific binding sites for this neuropeptide have been detected in the brain and the spinal cord. Interestingly, the smaller neuropeptide endomorphin-2 (EM-2, H-Tyr-Pro-Phe-Phe-NH2) also interacts with these binding sites, although 10-fold less efficient. In this work the structure–activity relationship of SP1–7 and EM-2, regarding their affinity to the SP1–7 binding site was elucidated using alanine scans, truncation, and terminal modifications. The C-terminal part of both peptides, and especially the C-terminal phenylalanine, was crucial for binding affinity. Moreover, the C-terminal functional group should preferably be a primary amide. The truncation studies finally resulted in the remarkable discovery of H-Phe-Phe-NH2 as an equally good binder as the heptapeptide SP1–7. This dipeptide amide served as a lead compound for further studies. In order to improve the drug-like properties and to find a plausible bioactive conformation, a set of rigidified and methylated dipeptides of different stereochemistry, and analogs with reduced peptide character, were synthesized and evaluated regarding binding, metabolic stability and absorption. Small SP1–7 analogs with retained affinity and substantially improved permeability and metabolic stability were identified. Beside peptide chemistry the synthetic work included the development of a fast and convenient microwave-assisted protocol for direct arylation of imidazoles. Furthermore, microwave-assisted aminocarbonylation using Mo(CO)6 as a solid carbon monoxide source was investigated in the synthesis of MAP amides and for coupling of imidazoles with amino acids. In a future perspective the present findings, together with the fact that some of the SP1–7 analogs discovered herein have been shown to reproduce the biological effects of SP1-7 in animal studies related to neuropathic pain and opioid dependence, can ultimately have an impact on drug discovery in these two areas.

Understanding molecular interactions at the surfaces of cellular membranes, including adsorption and transport, is of fundamental importance in both biological and pharmaceutical studies. At present, particularly with respect to small and medium size (drug-like) molecules, it is desirable to gain an understanding of the mechanisms that govern membrane adsorption and transport. To characterize drug-membrane interactions and mechanisms governing the process of molecular uptake at cellular membranes in living organisms, we need to develop effective experimental techniques to reach quantitative and time-resolved analysis of molecules at the membrane surfaces. Also, we preferably want to develop label-free optical techniques suited for single-cell and live cell analysis. Here, I discuss the nonlinear optical technique, second-harmonic light scattering (SHS), for studying molecule-membrane interactions and transport of molecules at the membrane of living cells with real-time resolution and membrane surface-specificity. Time-resolved SHS can quantify adsorption and transport of molecules, with specific nonlinear optical properties, at living organisms without imposing any mechanical stress onto the membrane. This label-free and surface-sensitive technique can even differentiate molecular transport at individual membranes within a multi-membrane cell (e.g., bacteria). In this dissertation, I present our current research and accomplishments in extending the capabilities of the SHS technique to study molecular uptake kinetics at the membranes of living cells, to monitor bacteria membrane integrity, to characterize the antibacterial mechanism-of-action of antibiotic compounds, to update the molecular mechanism of the Gram-stain protocol, to pixel-wise mapping of the membrane viscosity of the living cells, and to probe drug-induced activation of bacterial mechanosensitive channels in vitro. / Chemistry

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%.