Metallothioneins (MT) are small metal-binding proteins. Metallothionein isoform MT-1 alters localization from cytoplasm to nucleus as cells enter S phase. The perinuclear localization of MT-1 mRNA is essential for this nuclear localization. The localization of the MT-1 mRNA requires a signal in the 3'untranslated region (3'UTR). This thesis describes studies of the localization signal in the MT-1 3'UTR and its binding to transacting cellular proteins.

Milk is a highly nutritious natural product and research over the last 10 years has proven that these milk proteins not only provide a rich source of amino acids to the consumer but also contains many bioactive proteins and peptides known to exert biological activity benefitting human health. In this research, proteomic methods were first used to characterize the low abundance proteome within the skim milk fraction produced by Holstein and Jersey dairy cows maintained under the same diet, management and environmental conditions. Milk samples were collected over a seven day period from six Holstein and six Jersey dairy cows. Samples were depleted of casein (CN) by acidification and ultracentrifugation followed by ProteoMiner treatment. Extracts were subjected to sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) separation followed by liquid chromatography mass spectrometry (LC-MS). Over 930 low abundance proteins were identified and label-free proteomic analysis allowed for semi-quantification of proteins. Gene ontology (GO) classified proteins into various cellular localization and function categories. Forty-three low abundance proteins were differentially expressed between the two dairy breeds. Some bioactive proteins with immunomodulatory activities were present at significantly different abundance between breeds such as lactotransferrin (P <0.01) and Complement C2 (P <0.01), whereas others like osteopontin (P = 0.17) and lactoperoxidase (P = 0.29) were present at similar levels. This work has identified the highest number of low abundance proteins within the whey fraction in bovine skim milk, providing a foundation for future research exploring the bovine milk proteome. Nutrition is a significant animal factor that has potential to alter milk protein composition. Therefore in the second phase of this work, nutritional perturbances were used to alter the bovine milk proteome by feeding Holstein dairy cows different proportions of rumen degradable (RDP) and rumen undegradable protein (RUP) to alter whole-body nitrogen (N) metabolism. Six multiparous Holstein cows in mid-lactation were randomly assigned to one of two treatment groups. The experiment was conducted as a double-crossover design consisting of three 21-day periods. Within each period, treatment groups received diets with either 1) a high RDP:RUP ratio (control: 62.4:37.6 % of CP) or 2) a low RDP:RUP ratio (RUP: 51.3:48.7 % of CP). Both diets were isonitrogenous (CP = 18.5%) and isoenergetic (NEL = 0.8 Mcal lbs-1). Feeding a diet high in RUP decreased β-casein (P = 0.06), κ-casein (P =0.04) and total milk casein concentrations in milk (P <0.001). Milk urea nitrogen (MUN) and plasma urea nitrogen (PUN) were significantly higher in the RDP group (P = 0.04; P < 0.01, respectively). Over 590 low abundance proteins were identified and only three proteins were found to be differentially expressed between the two dietary groups. The high dietary crude protein (CP) inclusion may explain the lack of treatment effect since protein synthesis within the mammary gland (MG) may not be responsive to dietary changes when total CP levels is offered in excess. Additional feeding trials are needed to alter N utilization patterns within a dairy cow while maintaining isonitrogenous and isoenergetic diets and offering normal CP levels. Nutritional perturbances offer opportunities to selectively alter the bovine proteome, providing a tool to enhance the healthfulness of milk.

Made available in DSpace on 2014-12-17T14:03:40Z (GMT). No. of bitstreams: 1 AlexandreCS_DISSERT.pdf: 2097840 bytes, checksum: 2cb282516c6ef3d0a5391ba33939b8a4 (MD5) Previous issue date: 2012-12-10 / Obesity is increasing, reaching epidemic levels in many regions of the world. Studies have shown that consumption of peanuts influences on weight control and this influence may be due to the action of trypsin inhibitors sacietog?nica that condition increased plasma colescistocinina (CCK). Moreover, the peanut has other health benefits, and these assignments are guaranteed to increase their production and consumption of several of its products, including the pa?oca peanut. The aim of this study was to identify the presence of a trypsin inhibitor in pa?oca peanut and evaluate its effect on food intake, weight gain and histomorphological changes in swiss mice (n = 8) and Wistar rats (n = 6). Experimental diets were prepared based on the AIN-93G and supplemented with tack or peanut trypsin inhibitor partially purified pa?oca peanut (AHTI). After each treatment, the animals were anesthetized and euthanized, their bloods were collected by cardiac puncture for the determination of CCK and other biochemical parameters (glucose, triglycerides, total cholesterol, high density lipoprotein, low density lipoprotein, glutamic-pyruvic transaminase, glutamic oxaloacetic transaminase and albumin) and their pancreas removed for histologic and morphometric analysis. The supplementation with pa?oca peanut and the AHTI showed a decrease of body weight gain and food intake in both mice and rats, due to the satiety, since the animals showed no evidence of impairment of nutritional status conditioned by consumption the AHTI. There were also observed biochemical or morphological important when compared with controls. However, AHTI led to increased secretion of CCK, a peptide sacietog?nico. Thus, these results indicate that AHTI present in pa?oca peanut, is able to enhance the secretion of plasma CCK and thereby reduce the weight gain associated with lower food intake of experimenta animals / A obesidade ? crescente, atingindo n?veis epid?micos, em muitas regi?es do mundo. Estudos t?m mostrado que o consumo de amendoins influencia no controle de peso e essa influ?ncia pode ser devido ? a??o sacietog?nica de inibidores de tripsina que condicionam o aumento plasm?tico de colecistocinina (CCK). Al?m disso, o amendoim apresenta outros benef?cios ? sa?de e essas atribui??es t?m garantido o aumento da sua produ??o e o consumo de v?rios de seus produtos, entre eles, a pa?oca de amendoim. O objetivo deste estudo foi identificar a presen?a de um inibidor de tripsina na pa?oca de amendoim e avaliar o seu efeito sobre o consumo alimentar, o ganho de peso e altera??es histomorfol?gicas em camundongos swiss (n=8) e ratos wistar (n=6). Dietas experimentais foram preparadas com base na AIN-93G e suplementadas com a pa?oca de amendoim ou com o inibidor de tripsina parcialmente purificado da pa?oca de amendoim (AHTI). Ao final de cada tratamento, os animais foram anestesiados, eutanasiados e tiveram seus sangues colhidos, por pun??o card?aca, para a dosagem de CCK e de outros par?metros bioqu?micos (glicose, triglicer?deos, colesterol total, lipoprote?nas de altadensidade, lipoprote?na de baixa-densidade, transaminase glut?mica pir?vica, transaminase glut?mica oxalac?tica e albumina) e seus p?ncreas extra?dos para an?lise histol?gica e morfom?trica. As suplementa??es com a pa?oca de amendoim e com o AHTI mostraram uma diminui??o do ganho de peso corporal e do consumo alimentar tanto em camundongos quanto em ratos, devido ? saciedade, uma vez que os animais n?o apresentaram ind?cios de comprometimento do estado nutricional condicionada pelo consumo do AHTI. N?o foram, tamb?m, observadas altera??es bioqu?micas, nem histomorfol?gicas importantes quando comparadas com os controles. No entanto, o AHTI levou ao aumento da secre??o de CCK, um pept?dio sacietog?nico. Assim, estes resultados sugerem que o AHTI, presente na pa?oca de amendoim, seria capaz de aumentar a secre??o plasm?tica de CCK e reduzir o ganho de peso associado com menor consumo alimentar de animais experimentais

CoordenaÃÃo de AperfeiÃoamento de Pessoal de NÃvel Superior / Amburana cearensis (Allemao) A. C. Smith, usually known in portuguese language as âImburana-de-Cheiroâ or âCumaruâ, is a leguminous tree, subfamily Papilionoideae with common occurrence in âCaatingaâ Dominium. Despite the numerous ethnobotanical uses, few studies report biological activities of medical interest and / or agribusiness for this species or yet its utilization as food for humans and / or animals. This study aimed to evaluate the proteins of A. cearensis on its nutritional value associated with its biochemical characterization and as to the presence of bioactivity against bacteria, yeasts and filamentous fungi, all pathogens of humans, animals or plants of economic importance, and also against the vectors of disease, Aedes aegypti and Ae. albopictus. For this, seeds were collected in areas of caatinga trees in the municipality of Quixadà - CE and, subsequently, dried and finely ground. The seeds of A. cearensis have high nutritional potential, evidenced by the high content of proteins (22.69 &#61617; 0.81 g 100 g-1), lipid (24.45 2.02 g 100 g-1) and dietary fiber (34.75 1.78 g 100 g-1), keeping smaller quantities of starch (11.43 0.18 g 100 g-1), of total sugars (5.60 0.09 g 100 g-1) and minerals (4.51 0.21 g 100 g-1). Its amino acid composition is comparable to that of soybeans and beans. Moreover, the seeds have moderate levels of antinutritional factors, being detected only trypsin inhibitory activity (27.41  0.03 gTI Kg-1), urease activity (434  34 U kg-1) and some secondary metabolites such as tannins, phenols, flavones, flavonols, and xantone steroids. Chemical components, probably of low molecular mass present in seeds flour incorporated into diets, seem to interfere with their acceptance and use by animals since when the protein fraction (F0/90), obtained from its soluble protein, was incorporated into the balanced diet, the rats accepted well the diets and their performance indicated that F0/90 a good source of protein, comparable to major sources of vegetable protein such as soy and beans. Proteins of A. cearensis seeds are mainly composed of globulins (74.43 g 100 g-1) and albumins (14.23 g 100 g-1), with smaller quantities of glutelin basic proteins (10.07 g 100g-1), prolamins (1.20 g 100 g-1) and glutelin acidic proteins (0.07 g 100 g-1). The seeds crude extract (GE) offers a wide variety of proteins as shown by electrophoretic profiles with a predominance of proteins with apparent molecular mass over 45.0 kDa. The seeds of A. cearensis show also high bioactive potential, especially the activities of their majority proteins (albumins and globulins) against the growth of human pathogenic bacteria and yeast and phytopathogenic filamentous fungi, and against larvae of Aedes aegypti and Ae. albopictus. The inhibitory activity of the growth of phytopathogenic fungi concentrated in the albumins F70/90 fraction, being rich in proteins of low molecular mass (<30 kDa). Thus we can conclude that F0/90 is a good source of protein food when compared to other plant sources already used by the population. In addition, the globulins and albumins of A. cearensis are promising sources of bioactive proteins to be studied further and in greater purity. / Amburana cearensis (Allemao) A. C. Smith, popularmente conhecida como Imburana-de-Cheiro ou Cumaru, à uma leguminosa arbÃrea da subfamÃlia Papilionoideae de ocorrÃncia freqÃente na regiÃo do domÃnio Caatinga. Apesar dos inÃmeros usos etnobotÃnicos, poucos trabalhos relatam atividades biolÃgicas de interesse mÃdico e/ou agroindustrial para esta espÃcie ou, mesmo, sua utilizaÃÃo como fonte de alimento para humanos e/ou animais. Assim, o presente trabalho objetivou avaliar as proteÃnas de A. cearensis quanto a seu valor nutricional aliado à sua caracterizaÃÃo bioquÃmica e quanto à presenÃa de bioatividade contra bactÃrias, leveduras e fungos filamentosos, todos patÃgenos do homem, de animais ou de plantas de importÃncia econÃmica, e, ainda, contra os vetores de doenÃas, Aedes aegypti e Ae. albopictus. Para tanto, sementes foram coletadas em Ãrea de caatinga arbÃrea, no municÃpio de Quixadà â CE, sendo, posteriormente, desidratadas e finamente moÃdas. As sementes de A. cearensis possuem alto potencial nutricional, revelado pelo alto teor de proteÃnas (22,69 &#61617; 0,81 g. 100 g-1), lipÃdios (24,45 2,02 g. 100 g-1) e fibra alimentrar (34,75 1,78 g.100 g-1), retendo quantidades menores de amido (11,43 0,18 g.100g-1), aÃÃcares totais (5,60 0,09 g.100 g-1), e de minerais (4,51 0,21 g.100 g-1). Sua composiÃÃo aminoacÃdica à comparÃvel Ãquela da soja e feijÃo. AlÃm disso, as sementes apresentam moderados nÃveis de fatores antinutricionais, sendo detectados apenas atividade inibitÃria de tripsina (27,41  0,03 gTI.Kg-1), atividade ureÃsica (434,0  34,0 U.Kg-1) e alguns metabÃlitos secundÃrios, como taninos, fenÃis, flavonas, flavonÃis, xantonas e esterÃides. Componentes quÃmicos, provavelmente de baixa massa molecular, presentes nas sementes incorporadas a dietas interferem na sua aceitaÃÃo e aproveitamento por parte dos animais, uma vez que quando a fraÃÃo proteica (F0/90) obtida de suas proteÃnas solÃveis à incorporada à dieta balanceada, apresenta boa aceitaÃÃo pelos animais, mostrando-se uma boa fonte de proteÃnas, comparÃvel a importantes fontes de proteÃnas vegetais como a soja e os feijÃes. As proteÃnas das sementes de A. cearensis sÃo compostas principalmente por globulinas (74,43 g. 100g-1) e albuminas (14,23 g.100 g-1), com quantidades menores de proteÃnas do tipo glutelinas bÃsicas (10,07 g.100 g-1), prolaminas (1,20 g.100 g-1) e proteÃnas do tipo glutelinas Ãcidas (0,07 g.100 g-1). O extrato bruto (EB) das sementes apresenta uma grande diversidade de bandas proteicas com predominÃncia de bandas com massa molecular aparente > 45,0 kDa. As sementes de A. cearensis possuem tambÃm alto potencial bioativo, destacando-se as atividades de suas proteÃnas majoritÃrias (globulinas e albuminas) contra o crescimento de bactÃrias e leveduras patÃgenas do homem e de fungos filamentosos fitopatogÃnicos, e atividade contra larvas de Aedes aegypti e Ae. albopictus. A atividade inibitÃria do crescimento de fungos fitopatogÃnicos concentra-se na fraÃÃo F70/90 das albuminas, sendo rica em proteÃnas de baixa massa molecular (< 30 kDa). Assim, pode-se concluir que a F0/90 à uma boa fonte de proteÃna alimentar quando comparada a outras fontes vegetais jà utilizadas pela populaÃÃo. AlÃm disso, as globulinas e albuminas de A. cearensis sÃo fontes promissoras de proteÃnas bioativas que devem ser estudadas mais detalhadamente e em maior grau de pureza.

CoordenaÃÃo de AperfeiÃoamento de Pessoal de NÃvel Superior / A Caatinga possui uma vegetaÃÃo heterogÃnea cuja biodiversidade taxonÃmica conta com mais de 2.000 espÃcies de plantas. Dentre essas, cerca de 220 pertencem à famÃlia das leguminosas com 80 espÃcies endÃmicas, Ãnicas desse bioma. Muitas sÃo usadas para diversas finalidades de forma indiscriminada, reduzindo consideravelmente a diversidade e o nÃmero de espÃcies antes mesmo do conhecimento de suas potencialidades. Estudos que possam agregar valor econÃmico e viabilizar o uso racional, sustentÃvel e a conservaÃÃo das mesmas, aliada à constante busca por novas fontes de proteÃnas vegetais para atender à demanda crescente da populaÃÃo, bem como a grande necessidade de descoberta de compostos naturais que auxiliem no combate aos patÃgenos humanos e de plantas, sÃo de extrema relevÃncia. Assim, o presente estudo objetivou avaliar o potencial nutricional e bioativo de sementes de dez espÃcies vegetais da Caatinga destacando a espÃcie mais promissora. Para tanto, dez espÃcies de leguminosas selvagens da Caatinga foram analisadas quanto a sua composiÃÃo nutricional, apresentando elevado percentual de proteÃna bruta (10,9  0,4 a 50,0  3,4 %), fibras (0,8  0,0 a 52,3 Â1,0 %) e energia (1.000 a 1.804 kJ/100g), com perfil de aminoÃcidos comparÃveis aos da soja, com maiores teores de lisina (1088 a 456 mg/gN) e histidina (199 a 918 mg/gN) e bom perfil de minerais por apreentar boas quantidades de (mg/100g de farinha) de todos eles, em especial, de ferro (3,8 a 20,2), cÃlcio (31 a 268), magnÃsio (102 a 244) e potÃssio (366 a 1.581). As sementes apresentaram baixas quantidades de lectinas (80 a 2.560 e 160 a 2.560 UH/gF, quando nÃo tratadas e tratadas com enzimas, respectivamente), inibidores de tripsina (4,1  0,4 a 27,4  0,2 &#61549;gTI/mgF ), ureases (465  13 a 47.178  3.351 U/KgF) e atividade tÃxica, em apenas trÃs espÃcies, com DL50 variando de 0,72  0,03 a 1,12  0,04 g/Kg peso. Foi determinado um Ãndice de qualidade nutricional para todas as espÃcies, o qual apontou a espÃcie Piptadenia moniliformis Benth. (Catanduva) como detentora de melhor qualidade nutricional, sendo assim destacada e avaliada in vivo a qualidade das proteÃnas de suas sementes. Os processamentos tÃrmicos (fervura, cozimento em micro-ondas e autoclavagen) e o processo de extraÃÃo de &#61537;-galactosÃdios nas sementes dessas espÃcies nÃo proporcionaram bom desempenho dos animais, tendo em vista a perda de peso apresentada. Melhoria nos parÃmetros nutricionais, como NPU e VB foi verificada apÃs a retirada de &#61537;-galactosÃdios dessas sementes, sugerindo que a anÃlise de outros processamentos para o aproveitamento das proteÃnas de suas sementes, pode tornÃ-las uma fonte promissora. AlÃm do alto potencial nutricional, as dez espÃcies apresentam tambÃm potencial bioativo devido à presenÃa de metabÃlitos secundÃrios como alcalÃides, catequinas, calchonas, auronas, flavonÃis, fenÃis flavonas, xantonas, flavononÃis, saponinas e triterpenÃides. Possuem proteÃnas bioativas como proteases, quitinases (0,23  0,02 a 2,0  0,33 nKat/mgP), &#946;-1,3-glucanases (0,01  0,0 a 0,8  0,01 nKat/mgP), alÃm de proteÃnas ativas contra microorganismos que tambÃm sÃo consideradas antinutricionais (lectinas, inibidores de tripsina, ureases e toxinas). A avaliaÃÃo dos extratos brutos (EB) das espÃcies mostrou que todas sÃo ativas contra larvas de Aedes aegipty com percentual de mortalidade variando de 13,33  0,54 a 100,00  0,00 %, exceto o EB de Caesalpinea bracteosa que foi ativo contra a cepa Bacillus subtilis e contra o fungo Fusarium oxysporum, juntamente como o EB de Dioclea megacarpa. A espÃcie Senna rugosa inibiu o crescimento das cepas Bacillus subtilis e Staphylococcus aureus. Os fungos fitopatogÃnicos Aspergilus niger e Colletotrichum truncatum foram inibidos pelos EBs de Piptadenia moniliformis e Enterolobium contortisiliquum, que alÃm destes, foi ativo frente a Neurospora sp. e Trichoderma viridae. A espÃcie P. moniliformis destacou-se por sua elevada atividade quitinÃsica (1,12  0,0 nKat/mgP) em adiÃÃo à atuaÃÃo contra modelos biolÃgicos susceptÃveis a essa enzima, tendo sido escolhida para sua purificaÃÃo. A fraÃÃo proteica purificada de P. moniliformis (PmFP) contÃm elevada atividade de quitinases e causou pequena reduÃÃo no crescimento das leveduras Saccharomyces cerevisiae e Candida tropicalis, bem como da bactÃria B. subtilis. Inibiu ainda, a eclosÃo de ovos de A. aegypti com CI50 de 204, 42  2,19 ÂgP/ml e alterou a estrutura dos ovos e morfologia das larvas de primeiro estÃdio. A investigaÃÃo do potencial nutricional e bioativo das espÃcies mostrou boa composiÃÃo de nutrientes, em especial de proteÃnas e confirmou a presenÃa de compostos bioativos de natureza proteica e de metabÃlitos secundÃrios, tornando-as promissoras fontes de nutrientes e compostos antimicrobianos e anti-inseticidas que podem ser utilizados biotecnologicamente para fins agrÃcolas e industriais / The Caatinga Biome shows an heterogeneous vegetation with a taxonomic biodiversity of over 2,000 species of plants. Among these, approximately 220 belong to the Leguminosae family with 80 endemic species, unique to that biome. Many are used for various purposes in an indiscriminate manner, greatly reducing the variety and number of species even before the knowledge of their potential uses. Studies that can add economic value and enable the rational, sustainable use of these species, coupled with the constant search for new sources of plant protein to meet the ever increasing demand of the population are extremely important. Similarly important is the search for natural compounds which may help to combat human and plant pathogens. Thus, this study aimed to assess the nutritional and bioactive value of the seeds of ten plant species from Caatinga, highlighting the most promising ones. For this, the seeds were analyzed for nutritional composition, showing a high percentage of crude protein (10.9  0.4 to 50.0  3.4%), dietary fiber (0.8  0 , 0 to 52.3  1.0%) and energy (1,000 kJ/100g a1.804), with amino acid profile similar to that of soybeans, with higher amounts of lysine (1088-456 mg/gN) and histidine (199-918 mg/gN) and good mineral profile, with good content (mg/100 g flour) for all of them, especially, iron (3.8 to 20.2), calcium (31 to 268), magnesium (102-244) and potassium ( 366-1581). The seeds showed low amounts of lectins (80-2560 and 160-2560 UH / gF, when untreated and treated with enzymes, respectively), trypsin inhibitor &#61549;(4.1  0.4 to 27.4  0.2 GTI / mgF), urease (465  13 to 47,178  3,351 U / KGF) and toxic activity in only three species, with LD50 ranging from 0.72  0.03 to 1.12  0.04 g / kg body weight . Was given an index of nutritional quality for all species, which pointed to Piptadenia moniliformis Benth. species (Catanduva) as the most promising one and because of that the seeds of this species was had the quality of its proteins evaluated in vivo. The thermal processing (boiling, microwave cooking and autoclaving) as well as the removal of &#945;-galactosides did not improve animals performance. The nutritional parameters NPU and BV were improved when the animals were fed the seeds diet after removal of the &#945;-galactosides. This may indicate that the search for apropriate processing methods may turn these seeds a promising source of proteins. Besides the high nutritional potential, the seeds of the ten studied species also have bioactive potential due to the presence of secondary metabolites such as alkaloids, catechins, calchonas, Auron, flavonols, flavones phenols, xanthones, flavononols, saponins and triterpenoids. These seeds also have bioactive proteins such as proteases, chitinases (0.23  0.02 to 2.0  0.33 nkat / mg P), &#946;-1,3-glucanase (0.01  0.0 to 0.8  0, 01 nkat / mg P), and proteins active against microorganisms that are also considered antinutritional factors (lectins, trypsin inhibitors, urease and toxins). The evaluation of the crude extracts (CE) of the seeds showed that all species are active against the larvae of Aedes aegipti with mortality rates ranging from 13.33  0.54 to 100.00  0.00%, except that of Caesalpinea bracteosa which similarly to the CE of Dioclea megacarpa, was active against the bacterium Bacillus subtilis and against the fungus Fusarium oxysporum. Seeds extract of Senna rugosa species was able to inhibit the growth of Bacillus subtilis and Staphylococcus aureus. The pathogenic fungi Aspergillus niger and Colletotrichum truncatum were inhibited by the CE of Piptadenia moniliformis and Enterolobium contortisiliquum. The latter was also active against Neurospora sp. and Trichoderma viridae. The species P. moniliformis was distinguished for its high chitinase activity (1.12  0.0 nkat / mg P) in addition to its activity against biological models susceptible to this enzyme. For these reasons attempts were made for its purification. The purified protein fraction of P. moniliformis (PmFP) contains high activity of chitinases and caused a small reduction in the growth of the yeasts Saccharomyces cerevisiae and Candida tropicalis, and of the the bacterium B. subtilis. This protein fraction also inhibits the hatching of A. aegypti eggs with IC50 of 204. 42  2.19 &#956;gP / ml. It causes changes in the eggs structure and in the morphology of first stage larvae. Thus, investigation of bioactive and nutritional potential of the species showed good composition of nutrients, especially of proteins, and confirmed the presence of bioactive compounds from protein nature and secondary metabolites, making them promising sources of nutrients, antimicrobial and insecticides that can biotechnologically be used for agricultural and industrial purposes.

Protein homology detection has played a central role in the understanding of evolution of protein structures, functions and interactions. Many of the developments in protein bioinformatics can be traced back to an initial step of homology detection. It is not surprising then, that extension of remote homology detection has gained a lot of attention in the recent past. The explosive growth of genome sequences and the slow pace of experimental techniques have thrust computational analyses into the limelight. It is not surprising to see that many of the traditional experimental areas such as gene expression analysis, recognition of function and recognition of 3-D structure have been attempted effectively by computational approaches. The idea behind homology-based bioinformatics work is the fact that the hereditary mechanisms ensure that the parent generation gives rise to a very similar offspring generation. Since biological functions of proteins of an organism are product of expression of its genetic material, it follows that the genes of an organism should show conservation from one generation to another (with very few mutations if parent and offspring generation have to be nearly identical) Thus, if it can be established that two proteins have descended from a common ancestor, then it can be inferred that the biological functions of the two proteins could be very similar. Thus, homology-based information transfer from one protein to another has become a commonly used procedure in protein bioinformatics. The ability to recognize homologs of a protein solely from amino acid sequences has seen a steady increase in the last two decades. However, currently, still there are a large number of proteins of known amino acid sequence and yet unknown function . Thus, a major goal of current computational work is to extend the limits of remote homology detection to enable the functional characterization of proteins of unknown function. Since proteins do not work in isolation in a cell, it has become essential to understand the in vivo context of the function of a protein. For this purpose, it is essential to have an understanding of all the molecules that interact with a particular protein. Thus, another major area of bioinformatics has been to integrate biological information with protein-protein interactions to enable a better understanding of the molecular processes. Such attempts have been made successfully for the interaction network of proteins within an organism. The extension of the interaction network analysis to a host-pathogen scenario can lead to useful insights into pathophysiology of diseases. The work done as part of the thesis explores both the ideas mentioned above, namely, the extension of limits of remote homology detection and prediction of protein-protein interactions between a pathogen and its host. Since the work can logically be divided into two different areas though there is a connection, the thesis is organized as two parts. The first part of the thesis (comprising Chapters 2, 3, 4 and 5) describes the development and application of remote homology detection tools for function/structure annotation. The second part of the thesis (comprising of Chapters 6, 7, 8 and 9) describes the development and application of a homology-based procedure for detection of host-pathogen protein-protein interactions. Chapter 1 provides a background and literature survey in the areas of homology detection and prediction of protein-protein interactions. It is argued that homology-based information transfer is currently an important tool in the prediction and recognition of protein structures, functions and interactions. The development of remote homology detection methods and its effect on function recognition has been highlighted. Recent work in the area of prediction of protein-protein interactions using homology to known interaction templates is described and it is implied to be a successful approach for prediction of protein-protein interactions on a genome scale. The importance of further improvements in remote homology detection (as done in the first part of the thesis), is emphasized for annotation of proteins in newly sequenced genomes. The importance of application of homology detection methods in predicting protein-protein interactions across host-pathogen organisms is also explored. Chapter 2 analyzes the performance of the PSI-BLAST, one of the well-known and very effective approaches for recognition of related proteins, for remote homology detection. The chapter describes in detail the working of the PSI-BLAST algorithm and focuses on three parameters that determine the time required for searching in a large database, and also provide a ceiling for the sensitivity of the search procedure. The parameters that have been analyzed are the window size for two-hit method, the threshold for extension of an initial hit to dynamic programming and the extent of dependence on the query as encompassed in the profile generation step. The procedure followed for the analysis is to consider a large database of known evolutionary relationships (SCOP database was chosen for the analysis), and use the PSI-BLAST program at different values of three parameters to find out the effect on sensitivity (defined as the normalized number of correct SCOP superfamily relationships found in a search), and the time required for completion of the search. For the demonstration of the effect on the query dependence, a multiple sequence alignment (MSA) of a SCOP family (generated from all family sequences using ClustalW), was used with multiple queries to derive profiles in PSI-BLAST runs. The increase in sensitivity and the increase in time required for completion of each search were then monitored. The effect of changing the two PSI-BLAST internal parameters of score threshold for extension of word hits and the window size for the two-hit method do not result in a significant increase in sensitivity. Since PSI-BLAST uses the amino acid residues present in the query sequence to derive the Position Specific Scoring Matrix (PSSM) parameters, there is a strong query dependence on the sensitivity of each PSSM. Using multiple PSSMs derived from a single MSA can thus help overcome the query dependence and increase the sensitivity. In this Chapter such an approach, named as MulPSSM, has been demonstrated to have higher sensitivity than single profiles approach, (by up to two times more) in a benchmark dataset of 100 randomly chosen SCOP folds. Strategies to optimize sensitivity and the time required in searching MulPSSM have been explored and it is found that use of a non-redundant set of queries to generate MulPSSM can reduce the time required for each search while not affecting the sensitivity by a large degree. The application of the MulPSSM approach in function annotation of proteins in completely sequenced genomes was explored by searching genomic sequences in a MulPSSM database of Pfam families. The association of function to proteins has been assessed when both single profile per family database and MulPSSM database of families were used. It is found that in a comprehensive list of 291 genomes of Prokaryotes, 44 genomes of Eukaryotes and 40 genomes of Archea, that on an average MulPSSM is able to identify evolutionary relationships for 10% more proteins in a genome than single profiles-based approach. Such an enhancement in the recognition of evolutionary relationships, which has an implication in obtaining clues to functions, can help in more efficient exploration of newly sequenced genomes. Identification of evolutionary relationships involving some of the proteins of M. tuberculosis and M. leprae has been possible due to the use of multiple profiles search approach which is discussed in this chapter. The examples of annotations provided in the chapter include enzymes that are involved in glyco lipids synthesis which are vital for the survival of the pathogens inside the host and such annotations can help in expanding our knowledge of these processes. Chapter 3 describes the development and assessment of a sensitive remote homology detection method. The sensitivity of remote homology detection methods has been steadily increasing in the past decade and profile analysis has become a mainstay of such efforts. The profile is a probabilistic model of substitutions allowed at each position in a sequence family, and hence captures the essential features of a family. Alignment of two such profiles is thus considered to provide a more sensitive and accurate method than the alignment of two sequences. The performance of HMMs (Hidden Markov Models) has been shown to be higher than PSSMs (Position Specific Scoring Matrix). Thus, a profile-profile alignment using HMMs can in principle give the best possible sensitivity in remote homology detection. Many investigators have incorporated residue conservation and secondary structure information to align two HMMs, and such additional information has been demonstrated to provide better sensitivity in remote homology detection (for instance in the HHSearch program). The work presented in Chapter 3, extends the idea of incorporating additional information such as explicit hydrophobicity information, along with conservation and predicted secondary structure over a window of Multiple Sequence Alignment (MSA) columns in aligning HMMs. The new algorithm is named AlignHUSH (Alignment of HMMs Using Secondary structure and Hydrophobicity). The HMMs used in the work are derived from structural alignments using HMMER program and are taken from the publicly available superfamily database which provides HMMs for all the SCOP families. The HMMs are modified into two-state HMMs by collapsing the ‘insert’ and ‘delete’ states into a ‘non-match’ state in the AlignHUSH algorithm. The two state HMMs enables the use of dynamic programming methods and keeps intact the position-specific gap penalties. The two state HMMs can be more readily extended to alignment of PSSMs. The incorporation of secondary structure information is made using secondary structure predictions made using PSIPRED program. The hydrophobicity information is calculated using the Kyte Doolittle hydrophobicity values. The alignment is generated by scoring each position using the values present in a window of residues. The assessment of alignment accuracy is done by comparison to manually curated alignments present in the BaliBASE database. A detailed description of the optimization steps followed for obtaining the values for each score contribution (conservation, secondary structure and hydrophobicity) is provided. The assessment revealed that a high weightage to conservation score (18.0) and low weightage to the secondary structure score (1.5) and hydrophobicity (1.0) is optimal. The use of residue windows in alignment has been shown to dramatically increase the sensitivity (around 30% on a small dataset comprising 10% of total SCOP domains). The sensitivity of AlignHUSH algorithm in comparison to other HMM-HMM alignment methods HHSearch and PRC in an all-against-all comparison of SCOP 1.69 database demonstrates that AlignHUSH has better sensitivity than both HHSearch and PRC (approximately by 10% and 5% respectively). The alignment accuracy calculated as the ratio of correctly aligned residues and all alignment positions in BaliBASE alignments reveals that AlignHUSH algorithm provides an accuracy comparable or marginally higher than both HHSearch and PRC (25% for AlignHUSH and roughly 17% for both HHSearch and PRC). A few examples of structural relationships between SCOP families belonging to different folds and/or classes are presented in the chapter to illustrate the strength of AlignHUSH in detecting very remote relationships. Chapter 4 describes a database of evolutionary relationships identified between Pfam families. The grouping of Pfam families is important for obtaining better understanding on evolutionary relationships and in obtaining clues to functions of proteins in families of yet unknown function. Much effort has been taken by various investigators in bringing many proteins in the sequence databases within homology modeling distance with a protein of known structure. Structural genomics initiatives spend considerable effort in achieving this goal. The results from such experiments suggest that in many cases after the structure has been solved using X-ray crystallography or NMR methods, the protein is seen to have structural similarity to a protein of already known structure. Thus, an inability to detect such remote relationships severely impairs the efficiency of structural genomics initiatives. The development of the SUPFAM method was made earlier in the group to enable detection of distant relationships between Pfam families. In SUPFAM approach, relationships are detected by mapping the Pfam families to SCOP families. Further, using the implicit or explicit evolutionary relationship information present in the SCOP database relationships between Pfam families are detected. The work presented in this chapter is an improvement of previous development using the significantly more sensitive AlignHUSH method to uncover more relationships. The new database follows a procedure slightly different than the older SUPFAM database and hence is called SUPFAM+. The relative improvement brought by SUPFAM+ has been discussed in detail in the chapter. The methodology followed for the analysis is to first generate SUPFAM database by recognition of relationships between Pfam families and SCOP families using PSI BLAST / RPS BLAST. For the generation of SUPFAM+ database, recognition of relationships between Pfam families and SCOP families is done using AlignHUSH. The criteria are kept stringent at this stage to minimize the rate of false positives. In cases of a Pfam family mapping to two or more SCOP superfamilies, a semi-automated decision tree is used to assign the Pfam family to a single SCOP superfamily. Some of the Pfam families which remain without a mapping to a SCOP family are mapped indirectly to a SCOP family by identifying relationships between such Pfam families and other Pfam families which are already mapped to a SCOP family. In the final step, the Pfam families still without a SCOP family mapping are mapped onto one another to form ‘Potential New Superfamilies’ (PNSF), which are excellent targets for structural genomics since none of the proteins in such PNSFs have a recognizable homologue of known structure. The clustering of Pfam families into Superfamilies belonging to SCOP 1.69 version, were then queried to check if a structure has been solved for these Pfam families subsequent to the release of the SCOP 1.69 database. The latest SCOP database reveals that for close to 87 Pfam families a structure was solved which is at best related at a SCOP superfamily level with a family present in SCOP 1.69. An analysis of the mappings provided by SUPFAM+ database reveals that the mappings are correct in 85% of the cases at the SCOP superfamily level. An in-depth analysis revealed that among the rest of the cases, only one can be adjudged as an incorrect mapping. Many of the inconsistent mappings were found to be due to the absence of the SCOP fold in the SCOP 1.69 release, although interestingly the mapping provided by SUPFAM+ database shows structural similarity to the actual fold for the Pfam family found subsequently. A straightforward comparison with a similar database (Pfam Clans database) reveals that the SUPFAM+ database could suggest four times more pairwise relationships between Pfam families than the Pfam Clans database. Thus, since the structural mappings provided in the SUPFAM+ database are very accurate the relationships found in the database could help in function annotation of uncharacterized protein families (explored in Chapter 5). The accuracy of mapping would be similar for the PNSFs, and hence these clusters can be excellent targets for structural genomics initiatives. The classification of families based on sequence/structural similarities can also be useful for function annotation of families of uncharacterized proteins, and such an idea is explored in the next chapter. Chapter 5 describes the attempts made to obtain clues to the structure and/or function of the DUF (Domain of Unknown Function) families present in the Pfam database. Currently, the DUF families populate around 21% of the Pfam database (2260 out of 10340). Thus, although homologues for each of the proteins in these families can be recognized in sequence databases, the homology does not provide obvious insight into the function of these proteins. The annotation of such difficult targets is a major goal of computational biologists in the post-genomic era. The development of a sensitive profile-profile alignment method as part of this thesis, gives an excellent opportunity to increase the number of annotations for proteins, especially in the DUF families, since a profile for these families exists in the Pfam database. The method followed for the analysis is similar to the SUPFAM+ development, and involved generation of Pfam profiles compatible with the AlignHUSH method. For the analysis presented in the chapter, relationships found between DUF families and SCOP families were analyzed. In benchmarks using the AlignHUSH method, it was found that a Z score of 5.0 gives a 10% error rate, and a Z score of 7.5 gives an error rate of 1%, and hence a minimum Z score cutoff of 7.5 was used in the analysis. A very high Z score in AlignHUSH is usually seen in cases, when sequence identity is also high, so a maximum Z score cutoff of 12.0 was used to find DUF families which are difficult to annotate using other profile based methods (such as PSI-BLAST). For some of the DUF families, subsequent structure determination of one of the proteins had been reported in literature, and these cases were used to assess the accuracy of structural annotation using AlignHUSH. In other cases, fold recognition was done using the PHYRE method to ensure that the structure mappings are corroborated by fold recognition. In all cases studied, the alignment of the DUF family with the SCOP family was generated and queried for conservation of active site residues reported for each homologous SCOP family in the CSA (Catalytic Site Atlas) database. The assessment on 8 DUF families for which structure was solved subsequent to the SCOP release used in the analysis, reveals that in all cases, the correct structure was identified using the AlignHUSH procedure. In the eight cases of validated structure annotation, the conservation of active site residues was seen pointing to the effectiveness of AlignHUSH and its use in function annotation. The 27 cases in which a structure for any one of the proteins in the DUF family is not known, the fold recognition attempts suggest that in all cases, the results from fold recognition corroborate the suggestion made by AlignHUSH. The alignments of each of the DUF families with the suggested homologous SCOP family reveals that in many cases the active site residues are not conserved or are substituted by different residues. An in-depth analysis of some cases reveals that the non-conservation of residues occurs between two SCOP families in the same SCOP superfamily. Thus, although structure annotation can be reliably provided for all the DUF families studied, the exact biochemical function could be detected only for those cases in which active site conservation is seen even among distantly related families (such as two SCOP families in the same SCOP superfamily). The development and application of methods for remote homology detection has been made successfully and it has been demonstrated in the first part of the thesis that there is scope for extending the limits of remote homology detection. The use of sequence derived information in aligning profiles makes the procedure generally applicable and has been applied successfully for the case of structure/function recognition in the DUF families. In the next part of the thesis, a method for prediction of protein-protein interactions between a host and pathogen organism and its application to three groups of pathogens is presented. Chapter 6 describes the development of a procedure for prediction of protein-protein interactions (PPI) between a pathogen and its host organism. In the past, prediction of PPI has been attempted for proteins of a given organism. This was often approached by identifying proteins of the organism of interest that are homologous to two interacting proteins of another organism. A study of conservation of interactions as a function of sequence identity has been made in the past by various groups, which reveal that homologues sharing a sequence identity greater than about 30% interact in similar way. This fact can be used, along with a high quality database of protein-protein interactions to predict interactions between proteins of same organism. The work done in this thesis is one of the first attempts at extending the idea to the prediction of interactions between two different organisms. Homology of proteins from a pathogen and its host to proteins which are known to interact with each other would suggest that the proteins from pathogen and host can interact. The feasibility of such an interaction to occur under in vivo conditions need to be addressed for biologically meaningful predictions. These issues have been dealt with in this part of the thesis. One of the main steps in the procedure for the prediction of PPI is identification of homologues of pathogen and host proteins to interacting proteins listed in PPI databases. Two template PPI databases have been used in this work. One of the databases is the DIP database which provides a list of interactions based on genome-scale yeast-two-hybrid data or small scale experiments. The other database used is the iPfam database which provides interaction templates (Pfam families) based on protein complexes of known structure present in Protein Data Bank (PDB). Thus, the two databases are both comprehensive and are of high quality. The search for homologues in the DIP database was made using PSI-BLAST with stringent cutoffs for various parameters to minimize false positives. The search in iPfam database is done using RPS-BLAST and MulPSSM using stringent cutoffs. The cutoffs for the searches were fixed based on an assessment of conservation of putative interacting residues in the host and pathogen proteins as compared to the protein complexes of known structure. The predictions made are analyzed manually to assess the importance to the pathogenesis of the disease under consideration. In this chapter, in order to obtain an idea about robustness of this approach, PPI prediction was made for the phage-bacteria system and the herpes virus – human system which have been experimentally studied extensively and hence opportunities exist to compare the “predictions” with experimental results. The prediction of phage – bacteria interactions suggests that the gross biological features of the pathogenesis have been captured in the predictions. The GO (Gene Ontology) based annotations for the bacterial proteins predicted to interact suggests that the predictions involve proteins participating in DNA replication and protein synthesis. Many of the known interactions such as between the lambda phage repressor and RecA protein of bacteria were also ‘predicted’ in the analysis. A few novel interactions were predicted. For example interaction between a tail component protein and a protein of unknown function, YeeJ in E.coli has been predicted. The prediction of interactions between Herpes Virus 8 and human host and its comparison to a set of experimentally verified interactions reported in literature suggested that close to 50% of the known interactions were ‘predicted’ by the procedure followed. A few novel cases of interaction between the viral proteins and the p53 protein have also been made which might help in understanding the tumorigenesis of the viral disease. A comparison between the procedure followed in this thesis and the results from another genome-scale method (proposed by Andrej Sali and coworkers) suggests that although the proteins involved in predicted interactions from two methods may differ, the functions of the proteins concerned suggested by GO annotations are highly correlated (greater than 98%). In the next few chapters, the prediction of interactions for different host-pathogen systems is described. In the Chapter 7, the prediction of PPI between a Eukaryotic malarial pathogen, P.falciparum and its human host is described. The malarial parasite was chosen because of the extensive work reported in the literature on this pathogen in the recent years. Also, the gene expression patterns in the pathogen are highly correlated to the human tissue types with each stage of the pathogen occurring in a distinct tissue type. Thus, the biological context of the PPI can be explicitly assessed, which makes this example a well suited case for the procedure described in the Chapter 6 of this thesis. The pathogen is important from a medical perspective since there has been a recent emergence of P.falciparum induced malaria which is unresponsive to conventional drugs. Thus, studies of this parasite have gained an importance in the post genomic era. The difficulty in identifying homologues of many of the P.falciparum proteins makes this a challenging case study. Prediction of PPI between the malarial parasite and the human proteins has been approached in the same way as described in Chapter 6, with the cutoffs in homology searches kept stringent. However, in this case effective use of available additional biological data has been possible. The tissue specific expression information for human proteins has been obtained from the Atlas of Human transcriptome, and the NCBI GEO database. The pathogen stage-specific expression data has been obtained from multiple genome-scale experiments reported in the literature. The subcellular localization of both human and pathogen proteins has been predicted and hence this information is given low weightage in subsequent analysis. The prediction of PPI between malarial parasite and human, resulted in a total of more than 30,000 interactions which were compatible in an in vivo condition according to the expression data. Further reduction in the set of predicted interactions was made by incorporating the subcellular localization predictions (reduced to around 2000 interactions). Manual analysis of each of these interactions taking aid from literature on malarial parasites reveals that many of the known PPI are also ‘predicted’ in the analysis such as the interaction between SSP2 protein of P.falciparum and human ICAMs. For many proteins known to be important for pathogenesis, such as the RESA antigen, novel interactions were predicted that could help in better understanding of the pathogen. For some of the novel predicted interactions, such as that between the parasite Plasmepsin and human Spectrin, there exists circumstantial experimental evidence of interaction. Among many other novel interactions, the procedure used could predict interactions for 441 ‘hypothetical proteins’ of unknown function coded in the genome of the pathogen. The comprehensive list of predictions made using the procedure and an exploration of its biological significance can lead to novel hypothesis regarding the parthenogenesis of malaria and hence the work presented in this chapter can be helpful for further experimental exploration of the pathogen. The success of the procedure in predicting known interactions as well as novel interactions in a Eukaryotic pathogen suggests that the procedure developed is generally applicable. However it must be pointed out that in many cases of host-pathogen systems, such extensive expression and localization data may not be available, which makes the analysis difficult due to the large number of interactions predicted. One of such difficult cases is the interactions between Mycobacterial species and human host which is described in the next chapter. Chapter 8 describes the prediction of PPI between human and M.tuberculosis as well as three pathogens closely related to M.tuberculosis. Each of the pathogens has seen to re-emerge due to drug resistance and other causes. M.tuberculosis is becoming a global problem due to the limited number of drugs available to treat TB, which is susceptible to resistance. M.leprae has also shown signs of emergence of drug resistance, whereas C.diptheriae another pathogen studied in this chapter is seen as an emerging pathogen in Eastern Europe and in Indian subcontinent. Nocardial infections have also seen a rise due to the prevalence of AIDS which leads to susceptibility to the Nocardia infections. Thus, there is a need to understand further the pathogens in this important family, in order to better direct drug development. An important area for such endeavors is the mapping of the PPI between the pathogens and the human host. The procedure developed as part of the thesis can be used to predict such interactions. The procedure for prediction of interactions is the same as followed in Chapter 6 and involves identifications of homologues for the pathogen and host proteins among the proteins listed in the two template datasets DIP and iPfam using PSI-BLAST and RPS-BLAST (MulPSSM). In addition to the homology to the proteins involved in PPI, information / prediction on subcellular localization is used to assess biological significance of the interaction. An experimentally derived dataset of exported proteins in the M.tuberculosis was used to supplement the predictions from PSORTb database that provides subcellular localization for bacterial proteins. In order to minimize the number of predictions explored manually and to maximize the biological relevance of predicted interactions,, the predictions were made only for proteins present on the membrane of the pathogen or which are exported into the host. Prediction of interactions between human proteins and the proteins of four pathogens studied revealed that, some of the interactions which were known from earlier experiments were “predicted” by the present procedure. For example, the M.leprae exported Serine protease is known to interact with Ras-like proteins in the human host, and this interaction was ‘predicted’. Among other predicted interactions, several novel interactions have been suggested for proteins important for pathogenesis such as the MPT70 protein of M.tuberculosis which has been predicted to interact with TGFβ associated proteins which could play an important role in the pathogenesis of the disease. Some of the human proteins are known to play important role in pathogenesis, especially the toll-like receptors. A C.diphtheriae protein Mycosin, has been predicted to interact with the toll-like receptors raising the possibility that the Mycosins may play an important role in pathogenesis. Several hypothetical proteins of unknown function in the pathogens have been predicted to interact with human proteins. A few of such cases from M.tuberculosis have been described in the thesis and these proteins are predicted to interact with proteins involved in post-transnational modification in the human host. The prediction of novel interactions along with known interactions in four bacterial species thus points to the fact that the procedure can be used for almost any host-pathogen pair. In the next chapter, the application of the method to three other bacterial species belonging to the Enterobacteriaciae family is presented. Chapter 9 describes the analysis performed on the predicted interactions between human and three pathogens in the Enterobact