Der erste Teil der Dissertation behandelt die Substanz Phenylacetaldehyd, welche im Honig ausgehend von der Aminosäure Phenylalanin als natürlicher Stoff, aber auch als Rückstand nach Einsatz als Bienenvertreibungsmittel vorliegen kann. Die in dieser Arbeit durchgeführten Untersuchungen zeigen, dass der Gehalt an Phenylalanin sowie äußere Bedingungen, denen Honige ausgesetzt sind, für die Konzentration an Phenylacetaldehyd maßgebend sind. Diese Parameter müssen mindestens bekannt sein, um entscheiden zu können, ob Phenylacetaldehyd als Rückstand im Honig vorliegt. Der zweite Teil befasst sich mit der Filtration von Honig, welche in manchen Ländern durchgeführt wird, um eine Kristallisation zu herauszuzögern. Es wurde eine Methode entwickelt, um illegale Beimischungen gefilterter Honige zu ungefilterten Honigen nachzuweisen. Dazu wird das Enzym Saccharase gelchromatographisch isoliert und diese Fraktion elektrophoretisch untersucht. Die Veränderung des Proteinspektrums lässt sich mit Hilfe einer densitometrischen Auswertung quantifizieren und zeigt gefilterten Honig auch in Mischungen bis zu einem Anteil von mindestens 15 % an.

京都大学 / 0048 / 新制・課程博士 / 博士(医学) / 甲第20227号 / 医博第4186号 / 新制||医||1019(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 増永 慎一郎, 教授 宮本 享, 教授 伊佐 正 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

Exogenously supplied organoselenium compounds, capable of propagating a selenium redox cycle, were shown to supplement natural cellular defenses against oxidants generated during biological activity. Phenylaminoalkyl selenides were developed in our laboratory as novel substrate analogs for the enzyme dopamine beta-monooxygenase. Recently, phenylaminoalkyl selenides were found to protect plasmid DNA and Molecular beacons from oxoperoxynitrate – mediated damage by scavenging this oxidant and forming the corresponding selenoxides as the sole selenium – containing products. Rate constants were determined for the reactions of the phenylaminoalkyl selenoxides with GSH at physiological pH and 25 degrees C. The kinetic data obtained in current and previous research was subsequently used in a MatLab simulation, which showed the feasibility of selenium redox cycling by GSH in the presence of a cellular oxidant, oxoperoxynitrate. Loblolly pine (LP, Pinus taeda) is the primary commercial species in southern forests covering 11.7 million hectares. Somatic embryogenesis (SE) is an effective technique to implement production of high value genotypes of LP. SE is a multi-step process, which includes initiation of somatic embryo (SME) growth from tree tissue, maintenance and multiplication of early stage SMEs and the maturation / germination phase. In this work, we isolated a substance from stage 2 or 3 LP female gametophyte (FG) tissue that stimulates early stage SME growth, and characterized this substance as citric acid on the basis of 1H NMR and mass spectrometry. We then demonstrated that topical application of citric acid to SMEs stimulates embryo colony growth at p = 0.05 for 3 of the 5 genotypes tested. Phenylketonuria (PKU) is an autosomal recessive disorder caused by an impaired conversion of L-phenylalanine (L-Phe) to L-tyrosine (L-Tyr). A novel assay based on enzymatic - colorimetric methodology (ECA) was developed in order to detect elevated concentrations of L-Phe in undeproteinized plasma of PKU patients via continuous spectrophotometric detection. We report here that L-Phe concentrations in undeproteinized plasma measured using our ECA were comparable to those determined on an amino acid analyzer based on Pearson correlation coefficients and a Bland and Altman comparison.

Avec la hausse mondiale de la fréquence des floraisons de cyanobactéries (CB), dont certaines produisent des cyanotoxines (CT), le développement d’une méthode de détection/quantification rapide d’un maximum de CT s’impose. Cette méthode permettrait de faire un suivi quotidien de la toxicité de plans d’eau contaminés par des CB et ainsi d’émettre rapidement des avis d’alerte appropriés afin de protéger la santé publique. Une nouvelle technologie utilisant la désorption thermique induite par diode laser (LDTD) couplée à l’ionisation chimique sous pression atmosphérique (APCI) et reliée à la spectrométrie de masse en tandem (MS/MS) a déjà fait ses preuves avec des temps d'analyse de l’ordre de quelques secondes. Les analytes sont désorbés par la LDTD, ionisés en phase gazeuse par APCI et détectés par la MS/MS. Il n’y a donc pas de séparation chromatographique, et la préparation de l’échantillon avant l’analyse est minimale selon la complexité de la matrice contenant les analytes. Parmi les quatre CT testées (microcystine-LR, cylindrospermopsine, saxitoxine et anatoxine-a (ANA-a)), seule l’ANA-a a généré une désorption significative nécessaire au développement d’une méthode analytique avec l’interface LDTD-APCI. La forte polarité ou le poids moléculaire élevé des autres CT empêche probablement leur désorption. L’optimisation des paramètres instrumentaux, tout en tenant compte de l’interférence isobarique de l’acide aminé phénylalanine (PHE) lors de la détection de l’ANA-a par MS/MS, a généré une limite de détection d’ANA-a de l’ordre de 1 ug/L. Celle-ci a été évaluée à partir d’une matrice apparentée à une matrice réelle, démontrant qu’il serait possible d’utiliser la LDTD pour effectuer le suivi de l’ANA-a dans les eaux naturelles selon les normes environnementales applicables (1 à 12 ug/L). Il a été possible d’éviter l’interférence isobarique de la PHE en raison de sa très faible désorption avec l’interface LDTD-APCI. En effet, il a été démontré qu’une concentration aussi élevée que 500 ug/L de PHE ne causait aucune interférence sur le signal de l’ANA-a. / Within the context of the worldwide increasing frequency of cyanobacterial (CB) blooms, some containing cyanotoxins (CT), the development of a detection/quantification method for the fast analysis a maximum of CT is necessary. This method would allow daily tracking of the toxicity of CB-contaminated water such that, as warranted, appropriate measures can be taken quickly to protect public health. A new technology using laser diode thermal desorption (LDTD) coupled to atmospheric pressure chemical ionization (APCI)-tandem mass spectrometry (MS/MS) has shown great potential to reduce analysis time to seconds. Analytes are desorbed by the LDTD, ionized in gas-phase by APCI and detected by MS/MS. Therefore, there is no chromatographic separation and sample treatment prior to analysis is minimal, depending on the complexity of the sample matrix. Among the four CT tested (microcystin-LR, cylindrospermopsin, saxitoxin and anatoxin-a (ANA-a)), only ANA-a exhibited sufficient desorption which is necessary to develop an analytical method with the LDTD-APCI interface. The strong polarity or high molecular weight of the other CT probably inhibited their efficient desorption. Optimization of instrumental parameters, while accounting for the isobaric interference caused by the acid amino phenylalanine (PHE) in the detection of ANA-a by MS/MS, generated a detection limit of the order of 1 ug/L ANA-a. This value was obtained in a simulated natural matrix, demonstrating that it would be possible to use LDTD to monitor ANA-a in natural waters within the range of current applicable environmental guidelines (1 to 12 ug/L). Because PHE desorption is limited with the LDTD-APCI interface, this method avoids its interference on ANA-a analysis, even at PHE concentrations as high as 500 ug/L.

The development of drugs and therapeutic agents for combating infections and human malignancies continues to be a forefront area in both academic and industrial research. This is driven by the rapid emergence of multi-drug resistant bacterial strains and accumulating mutations in cancer targets that is quickly rendering our current arsenal of drugs ineffective for these therapies. Unless new drugs with novel mechanisms of action are identified and developed at a faster pace, we face a losing battle in managing these diseases. The first part of this work concerns with the natural product Simocyclinone D8 (SD8). Simocyclinone D8 is an angucyclinone antibiotic that inhibits DNA gyrase with a novel mechanism of action that has been termed competitive inhibition. Simocyclinone D8 was found to inhibit the growth of both Gram-(+ve) and Gram-(–ve) organisms and also inhibit a fluoroquinolone resistant mutant of DNA gyrase. Inspired by the structure and novel mechanism of action that SD8 displays, we synthesized analogues based on the co-crystal structure of SD8 with DNA gyrase. These compounds were found to inhibit DNA gyrase, albeit by a different mechanism of action than that of SD8. We also conducted studies towards the total chemical synthesis of SD8 and made three out of the four fragments in SD8 in decent yields. The second part of this work is focused on the development of a substrate-competitive covalent inhibitor for protein kinase B (AKT). AKT is a valid target for cancer research with two compounds currently in late stage clinical trials. Developing substrate- competitive inhibitors for kinases is a novel approach in targeting them, with very few examples in the literature. This mechanism has been postulated to overcome common resistance mutations that cancer targets harbor. A major drawback in this approach is the low binding affinity for peptide substrates by kinases. We circumvented this problem of affinity by utilizing a covalent mode of binding and synthesized a potent non-peptide active-site directed irreversible compound that inhibits AKT. Further studies on this compound are underway and are expected to yield a compound that can be used as a therapeutic agent or as a probe for AKT.

The first aim of this work was to develop copper modified carbon felt electrode for detection of amino acids, which are not electrochemically active on ordinary carbon electrodes. Phenylalanine solution at a concentration 1.0 mmol dm-3 was chosen as the testing solution. Electrode modified with electrochemical deposition of copper from mixture of copper(II) sulphate and sodium sulphate provided very low responses which were decreasing during first measurements, apparently because of insufficient amount of copper. Therefore, further experiments were performed using copper microparticles as a modifier. Copper microparticles activated in nitric acid at a concentration 80 mmol dm-3 were applied at carbon felt by several techniques and in different parts of the felt, i.e. by stirring the felt in microparticles suspension, by dripping of the suspension to the part of the felt in contact with capillary (proximal), between two parts of the carbon felt (sandwich) and at a part of the carbon felt in contact with electrolyte in a measuring cell (distal). Electrodes modified in the distal and in the sandwich arrangement were chosen as the best ones. In the last part, calibration dependences for phenylalanine in concentration range from 0.025 mmol dm-3 to 1.0 mmol dm-3 were measured on the last two electrodes....

<p></p><p>Phenylketonuria (PKU) is an inherited metabolic disorder affecting 1 in every 10,000 to 15,000 newborns in the United States every year. Caused by a genetic mutation, PKU results in an excessive build up of the amino acid Phenylalanine (Phe) in the body leading to symptoms including but not limited to intellectual disability, hyperactivity, psychiatric disorders and seizures. Most PKU patients must follow a strict diet limited in Phe. The aim of this research study is to formulate, implement and compare techniques for Phe estimation in commercial foods using the information on the food label (Nutritional Fact Label and ordered ingredient list). Ideally, the techniques should be both accurate and amenable to a user friendly implementation as a Phe calculator that would aid PKU patients monitor their dietary Phe intake.</p> <p> The first approach to solve the above problem is a mathematical one that comprises three steps. The three steps were separately proposed as methods by Jieun Kim in her dissertation. It was assumed that the third method, which is more computationally expensive, was the most accurate one. However, by performing the three methods subsequently in three different steps and combining the results, we actually obtained better results than by merely using the third method.</p> <p> The first step makes use of the protein content in the foods and Phe:protein multipliers. The second step enumerates all the ingredients in the food and uses the minimum and maximum Phe:protein multipliers of the ingredients along with the protein content. The third step lists the ingredients in decreasing order of their weights, which gives rise to inequality constraints. These constraints hold assuming that there is no loss in the preparation process. The inequality constraints are optimized numerically in two phases. The first involves nutrient content estimation by approximating the ingredient amounts. The second phase is a refinement of the above estimates using the Simplex algorithm. The final Phe range is obtained by performing an interval intersection of the results of the three steps. We implemented all three steps as web applications. Our proposed three-step method yields a high accuracy of Phe estimation (error <= +/- 13.04mg Phe per serving for 90% of foods).</p> <p> The above mathematical procedure is contrasted against a machine learning approach that uses the data in an existing database as training data to infer the Phe in any given food. Specifically, we use the K-Nearest Neighbors (K-NN) classification method using a feature vector containing the (rounded) nutrient data. In other words, the Phe content of the test food is a weighted average of the Phe values of the neighbors closest to it using the nutrient values as attributes. A four-fold cross validation is carried out to determine the hyper-parameters and the training is performed using the United States Department of Agriculture (USDA) food nutrient database. Our tests indicate that this approach is not very accurate for general foods (error <= +/- 50mg Phe per 100g in about 38% of the foods tested). However, for low-protein foods which are typically consumed by PKU patients, the accuracy increases significantly (error <= +/- 50mg Phe per 100g in over 77% foods).</p> <p> The machine learning approach is more user-friendly than the mathematical approach. It is convenient, fast and easy to use as it takes into account just the nutrient information. In contrast, the mathematical method additionally takes as input a detailed ingredient list, which is cumbersome to be located in a food database and entered as input. However, the Mathematical method has the added advantage of providing error bounds for the Phe estimate. It is also more accurate than the ML method. This may be due to the fact that for the ML method, the nutrition facts alone are not sufficient to estimate Phe and that additional information like the ingredients list is required. </p><br><p></p>

O presente trabalho teve como objetivo estimar a concentração de Phe em 22 amostras de sopas desidratadas instantâneas, por serem úteis na diversificação do cardápio de fenilcetonúricos. Foi analisada a concentração de glutamato monossódico (GMS) por ser uma provável fonte de N não protéico (NNP) que pode resultar em concentrações protéicas superestimadas. A concentração de proteína real estimada foi realizada após precipitação da proteína com TCA 10%, seguida da análise do N pelo método de Kjeldahl, o qual foi convertido para proteína por um fator de conversão (Fc) adequado. A legislação Brasileira estabelece um Fc de 5,75 para proteínas vegetais, 6,25 para proteínas da carne e misturas de proteínas e 6,38 para proteínas lácteas. A concentração de GMS foi determinada por método enzimático com eletrodo sensível a amônia. A concentração de proteína bruta (N totalxFc) variou entre 6,05 e 21,51%, tendo sido estes valores, na maioria das vezes, similares aos declarados no rótulo, indicando que os fabricantes utilizam o N totalxFc para expressar o conteúdo protéico. A concentração protéica real estimada foi baixa, variando entre 1,28 e 16,31%. A concentração de NNP teve uma variação de 0,33 a 1,27g/100g de amostra, representando de 11,10 a 81,33% do NT presente. A concentração de GMS variou entre 1,01 e 7,86g/100g de amostra, sendo que o N proveniente deste realçador de sabor contribuiu com 2,53 a 47,71% na quantidade total de N. A diferença entre a concentração de proteína bruta e real estimada se deve à presença de NNP, na forma de GMS. Com base nos valores protéicos reais estimados, foram calculados os teores de Phe que variaram entre 51,16 e 652,24mg de Phe/100g de amostra. Assim, recomenda-se que todos os alimentos adicionados de realçadores de sabor sejam analisados quanto à concentração de proteína real para que a Phe seja corretamente estimada. / The aim of this work was to estimate the concentration of Phe in 22 samples of commercially available dehydrated soups, as they are useful to add variety to the diet for phenilketonurics. The monosodium glutamate (MSG) contents had been analyzed as it is a likely source of non protein N (NPN) that might result in overestimated protein contents. The true protein content was accomplished after protein precipitation with 10% TCA and followed by N analysis according to the Kjeldahl method, which was converted to protein by a suitable conversion factor (Fc). The Brazilian legislation establishes a Fc of 5,75 for vegetables proteins, 6,25 for meat and blended proteins and 6,38 for milk proteins. The MSG concentration was determined by an enzymatic method employing an ammonia gas-sensitive electrode. The crude protein content (total NxFc) varied from 6,05 to 21,51% and were similar, in most cases, to those stated on the label, showing that manufacturers use total NxFc to express the protein content. Nevertheless, the true protein content was low, varying from 1,28 to 16,31%. The NPN concentration varied from 0,33 to 1,27g/100g of sample, which represents from 11,10 to 81,33% of the existing total N. The MSG concentration varied from 1,01 to 7,86g/100g of sample; the N arose from this flavor enhancer gives about 2,53 to 47,71% of the total quantity of N. The difference between the crude protein and true protein contents is due to the presence of MSG-like NPN. The Phe concentrations were calculated in accordance with the true protein values and varied from 51,16 to 652,24 mg/100g of sample. Thus, we recommend the analysis of all flavor-enhancer-added foods, in order to get reliable results for Phe estimation from the protein contents.

O presente trabalho teve como objetivo estimar a concentração de Phe em 22 amostras de sopas desidratadas instantâneas, por serem úteis na diversificação do cardápio de fenilcetonúricos. Foi analisada a concentração de glutamato monossódico (GMS) por ser uma provável fonte de N não protéico (NNP) que pode resultar em concentrações protéicas superestimadas. A concentração de proteína real estimada foi realizada após precipitação da proteína com TCA 10%, seguida da análise do N pelo método de Kjeldahl, o qual foi convertido para proteína por um fator de conversão (Fc) adequado. A legislação Brasileira estabelece um Fc de 5,75 para proteínas vegetais, 6,25 para proteínas da carne e misturas de proteínas e 6,38 para proteínas lácteas. A concentração de GMS foi determinada por método enzimático com eletrodo sensível a amônia. A concentração de proteína bruta (N totalxFc) variou entre 6,05 e 21,51%, tendo sido estes valores, na maioria das vezes, similares aos declarados no rótulo, indicando que os fabricantes utilizam o N totalxFc para expressar o conteúdo protéico. A concentração protéica real estimada foi baixa, variando entre 1,28 e 16,31%. A concentração de NNP teve uma variação de 0,33 a 1,27g/100g de amostra, representando de 11,10 a 81,33% do NT presente. A concentração de GMS variou entre 1,01 e 7,86g/100g de amostra, sendo que o N proveniente deste realçador de sabor contribuiu com 2,53 a 47,71% na quantidade total de N. A diferença entre a concentração de proteína bruta e real estimada se deve à presença de NNP, na forma de GMS. Com base nos valores protéicos reais estimados, foram calculados os teores de Phe que variaram entre 51,16 e 652,24mg de Phe/100g de amostra. Assim, recomenda-se que todos os alimentos adicionados de realçadores de sabor sejam analisados quanto à concentração de proteína real para que a Phe seja corretamente estimada. / The aim of this work was to estimate the concentration of Phe in 22 samples of commercially available dehydrated soups, as they are useful to add variety to the diet for phenilketonurics. The monosodium glutamate (MSG) contents had been analyzed as it is a likely source of non protein N (NPN) that might result in overestimated protein contents. The true protein content was accomplished after protein precipitation with 10% TCA and followed by N analysis according to the Kjeldahl method, which was converted to protein by a suitable conversion factor (Fc). The Brazilian legislation establishes a Fc of 5,75 for vegetables proteins, 6,25 for meat and blended proteins and 6,38 for milk proteins. The MSG concentration was determined by an enzymatic method employing an ammonia gas-sensitive electrode. The crude protein content (total NxFc) varied from 6,05 to 21,51% and were similar, in most cases, to those stated on the label, showing that manufacturers use total NxFc to express the protein content. Nevertheless, the true protein content was low, varying from 1,28 to 16,31%. The NPN concentration varied from 0,33 to 1,27g/100g of sample, which represents from 11,10 to 81,33% of the existing total N. The MSG concentration varied from 1,01 to 7,86g/100g of sample; the N arose from this flavor enhancer gives about 2,53 to 47,71% of the total quantity of N. The difference between the crude protein and true protein contents is due to the presence of MSG-like NPN. The Phe concentrations were calculated in accordance with the true protein values and varied from 51,16 to 652,24 mg/100g of sample. Thus, we recommend the analysis of all flavor-enhancer-added foods, in order to get reliable results for Phe estimation from the protein contents.

Peptides have assumed considerable importance in pharmaceutical industry and vaccine research. Understanding the structural features of these peptide molecules can be effective not only in mimicking natural proteins but also in the design of new biomaterials. Polypeptide sequences consisting of twenty genetically coded amino acids possess structural flexibility, which makes the predictions difficult. However, the introduction of non-protein amino acids into the peptide chain restricts the available range of backbone conformations and acts as stereochemical directors of polypeptide chain folding. Such conformationally rigid residues allow the formation of well defined structures like helices, strands etc, which further assemble into super secondary structural motifs by flexible linkages. Crystal structure determination of the oligopeptides by X-ray diffraction gives insight into the specific conformational states, modes of aggregation, hydrogen bond interactions, solvation of peptides and various weakly polar interactions involving the side chains of aromatic residues (Phe, Trp and Tyr). In β-, γ- and higher ω-amino acids, due to the insertion of one or more methylene groups between the N- and Cα-atoms into the peptide backbone the accessible conformational space is greater than the α-amino acids. The β-, γ-, δ-…. amino acid residues belong to the family of ω-amino acids. Extensive research in the field of β-peptides, which have been experimentally verified or theoretically postulated, has assigned several helices, turns and sheets. The use of ω-amino acid residues in conjunction with α-residues permits systematic exploration of the effects of introducing additional backbone atoms into well-characterized α-peptide structures. The observation of new families of hydrogen bonded motifs in the hybrid peptides containing α- and ω-amino acids are the recent interest in this regard. This thesis reports results of X-ray crystallographic studies of eighteen designed peptides and four protected ω-amino acids listed below. Within brackets are given the abbreviations used for the sequences (Symbol U represents Aib). The ω-amino acids reported in this thesis are: (S)-β3-HAla (β3-homoalanine), (R)-β3-HVal, (S)-β3-HVal (β3-homovaline), (S)-β3-HPhe (β3-homophenylalanine), (S)-β3-HPro (β3-homoproline), βGly (β-homoglycine), γAbu (gamma aminobutyric acid) and δAva (delta aminovaleric acid). 1. Boc-Leu-Trp-Val-OMe (LWV), C28H42N4O6 2. Ac-Leu-Trp-Val-OMe (Space group P21) (LWV1), C25H36N4O5 3. Ac-Leu-Trp-Val-OMe (Space group P212121) (LWV2), C25H36N4O5 4. Boc-Leu-Phe-Val-OMe (LFV), C26H41N3O6 5. Ac-Leu-Phe-Val-OMe (LFV1), C23H35N3O5 6. Boc-Ala-Aib-Leu-Trp-Val-OMe (AULWV), C35H54N6O8 7. Boc-Trp-Trp-OMe (WW), C28H32N4O5 8. Boc-Trp-Aib-Gly-Trp-OMe. (WUGW), C34H42N6O7 9. Boc-Leu-Trp-Val-Ala-Aib-Leu-Trp-Val-OMe (H8AU), C57H84N10O11 10. Boc-(S)-β3-HAla-NHMe (BANH), C10H20N2O3 11. Boc-(R)-β3-HVal-NHMe (BVNH), C12H24N2O3 12. Boc-(S)-β3-HPhe-NHMe (BFNH), C16H24N2O3 13. Boc-(R)-β3-HVal-(R)-β3-HVal-OMe (BVBV), C18H34N2O5 14. Boc-(R)-β3-HVal-(S)-β3-HVal-OMe (LVDV), C18H34N2O5 15. Boc-(S)-β3-HPro-OH (BPOH), C11H19N1O4 16. Boc-Leu-Phe-Val-Aib-(S)-β3-HPhe-Leu-Phe-Val-OMe (UBF8), C60H88N8O11 17. Piv-Pro-Gly-NHMe (PA1), C13H23N3O3 18. Piv-Pro-βGly-NHMe (PB1), C14H25N3O3 19. Piv-Pro-βGly-OMe (PBO), C14H24N2O4 20. Piv-Pro-δAva-OMe (PDAVA), C16H28N2O4 21. Boc-Pro-γAbu-OH (BGABU), C14H24N2O5 22. Boc-Aib-γAbu-OH (UG), C13H24N2O5 23. Boc-Aib-γAbu-Aib-OMe (UGU), C18H33N3O6 The thesis is divided into seven chapters. Chapter 1 gives a general introduction to the stereochemistry of polypeptide chains and the secondary structure classification: helices, β-sheets and β-turns followed by an overview of different types of weakly polar interactions involving the side chains of aromatic amino acid residues. This section also provides a brief overview of the conformational analysis of β-, γ- and higher ω-amino acid residues in oligomeric β-peptides and in α,ω-hybrid peptides. A brief discussion on X-ray diffraction and solution to the phase problem is also presented. Chapter 2 describes the crystal structures of the peptides, Boc-Leu-Trp-Val-OMe (LWV), the two polymorphs of Ac-Leu-Trp-Val-OMe (LWV1 and LWV2), Boc-Leu-Phe-Val-OMe (LFV), Ac-Leu-Phe-Val-OMe (LFV1) and Boc-Ala-Aib-Leu-Trp-Val-OMe (AULWV), in order to explore the nature of interactions between aromatic rings, specifically the indole side chain of Trp residues [1]. Peptide LWV adopts a type I β-turn conformation, stabilized by an intramolecular 4→1 hydrogen bond. Molecules of LWV pack into helical columns stabilized by two intermolecular hydrogen bonds, Leu(1)NH…O=CTrp(2) and Indole NH…O=CLeu(1). The superhelical columns further pack into the tetragonal space group P43 by means of a continuous network of indole - indole interactions. The peptide Ac-Leu-Trp-Val-OMe crystallized in two polymorphic forms: P21 (LWV1) and P212121 (LWV2). In both forms, the peptide backbone is extended and the crystal packing shows anti-parallel β-sheet arrangement. Similarly, extended strand conformation and anti-parallel β-sheet formation are also observed in the Phe containing analogs, LFV and LFV1. The pentapeptide AULWV adopts a short stretch of 310-helix. Analysis of aromatic - aromatic and aromatic - amide interactions in the structures of peptides LWV, LWV1 and LWV2 are reported along with the examples of 12 Trp containing peptides from the Cambridge Structural Database. The results suggest that there is no dramatic preference for the orientation of two proximal indole rings. In Trp containing peptides specific orientations of the indole ring, with respect to the preceding and succeeding peptide units, appear to be preferred in β-turns and extended structures. Crystal parameters LWV: C28H42N4O6; P43; a = 14.698(1) Å, b = 14.698(1) Å, c = 13.975(2) Å; Z = 4; R = 0.0737, wR2 = 0.1641. LWV1: C25H36N4O5; P21; a =10.966(3) Å, b = 9.509(2) Å; c = 14.130(3) Å, β = 104.94(1)°; Z = 2; R = 0.0650, wR2 = 0.1821. LWV2: C25H36N4O5; P212121; a = 9.533(6) Å, b = 14.148(9) Å, c = 19.53(1) Å, Z = 4; R = 0.0480, wR2 = 0.1365. LFV: C26H41N3O6; C2; a = 31.318(8) Å, b = 10.022(3) Å, c = 9.657(3) Å, β = 107.41(1)°; Z = 4; R = 0.0536, wR2 = 0.1328. LFV1: C23H35N3O5; P212121; a = 9.514(8) Å, b = 13.56(1) Å, c = 20.04(2) Å, Z = 4; R = 0.0897, wR2 = 0.1960. AULWV: C35H54N6O8.2H2O; P21; a = 9.743(3) Å, b = 22.807(7) Å, c = 10.106(3) Å, β = 105.73(2)°; Z = 2; R = 0.0850; wR2 = 0.2061. Chapter 3 describes the crystal structures of three peptides containing Trp residues at both N- and C-termini of the peptide backbone: Boc-Trp-Trp-OMe (WW), Boc-Trp-Aib-Gly-Trp-OMe (WUGW) and Boc-Leu-Trp-Val-Ala-Aib-Leu-Trp-Val-OMe (H8AU). Peptide WW adopts an extended conformation and the molecules pack into an arrangement of parallel β-sheet in crystals, stabilized by three intermolecular N-H…O hydrogen bonds. The potential hydrogen bonding group NE1H of Trp(1), which does not take part in hydrogen bonding interaction with an oxygen acceptor participate in an intermolecular N-H…π interaction. Peptide WUGW adopts a folded structure, stabilized by a consecutive type II-I’ β-turn conformation. The crystal of WUGW contains a stoichiometric amount of chloroform in two distinct sites each with an occupancy factor of 0.5 and the structure provides examples of N-H…π, C-H…π, π…π, N-H…Cl, C-H…Cl and C-H…O interactions [2]. The molecular conformation of H8AU reveals a 310-helix. The crystal structure of H8AU reveals an interesting packing motif in which helical columns are stabilized by side chain - backbone hydrogen bond involving the indole NH of Trp(2) as donor and C=O group of Leu(6) as acceptor of a neighboring molecule, which closely resembles the hydrogen bonding pattern obtained in the tripeptide LWV [1]. Helical columns also associate laterally and strong interactions are observed between the Trp(2) and Trp(7) residues on neighboring molecules [3]. The edge-to-face aromatic interactions between the indoles suggest a potential C-H…π interaction involving the CE3H of Trp (2) Crystal parameters WW: C28H32N4O5; P212121; a = 5.146(1) Å, b = 14.039(2) Å, c = 35.960(5) Å; Z = 4; R = 0.0503, wR2 = 0.1243. WUGW: C34H42N6O7.CHCl3; P21; a = 12.951(5) Å, b = 11.368(4) Å, c = 14.800(5) Å, β = 101.41(2)°; Z = 2; R = 0.1095, wR2 = 0.2706. H8AU: C57H84N10O11; P1; a = 10.494(7) Å, b = 11.989(7) Å, c = 13.834(9) Å, α = 70.10(1)°, β = 82.74(1)°, γ = 78.96(1)°; Z = 1; R = 0.0855, wR2 = 0.1965. Chapter 4 describes the crystal structures of four protected β-amino acid residues, Boc-(S)-β3-HAla-NHMe (BANH); Boc-(R)-β3-HVal-NHMe (BVNH); Boc-(S)-β3-HPhe-NHMe (BFNH); Boc-(S)-β3-HPro-OH (BPOH) and two β-dipeptides, Boc-(R)-β3-HVal-(R)-β3-HVal-OMe (BVBV); Boc-(R)-β3-HVal-(S)-β3-HVal-OMe (LVDV). Gauche conformations about the Cβ-Cα bonds (θ ~ ± 60°) are observed for the β3-HPhe residue in BFNH and all four β3-HVal residues in the dipeptides BVBV and LVDV. Trans conformations (θ ~ 180°) are observed for β3-HAla residues in both independent molecules in BANH and for the β3-HVal and β3-HPro residues in BVNH and BPOH, respectively. In all these cases except for BPOH, molecules associate in the crystals via intermolecular backbone hydrogen bonds leading to the formation of sheets. The polar strands formed by β3-residues aggregate in both parallel (BANH, BFNH, LVDV) and anti-parallel (BVNH, BVBV) fashion. Sheet formation accommodates both the trans and gauche conformations about the Cβ - Cα bonds [4]. Crystal parameters BANH: C10H20N2O3; P1; a = 5.104(2) Å, b = 9.469(3) Å, c = 13.780(4) Å, α = 80.14(1)°, β = 86.04(1)°, γ = 89.93(1)°; Z =2; R = 0.0489, wR2 = 0.1347. BVNH: C12H24N2O3; P212121; a = 8.730(2) Å, b = 9.741(3) Å, c = 17.509(5) Å; Z = 4; R = 0.0479, wR2 = 0.1301. BFNH: C16H24N2O3; C2; a = 20.54(1) Å, b = 5.165(3) Å, c = 16.87(1) Å, β = 109.82(1)°; Z = 4; R = 0.0909, wR2 = 0.1912. BVBV: C18H34N2O5; P212121; a = 9.385(2) Å, b = 11.899(2) Å, c = 19.199(4) Å; Z = 4; R = 0.0583, wR2 = 0.1589. LVDV: C18H34N2O5; P212121; a = 5.170(4) Å, b = 10.860(8) Å, c = 37.30(3) Å; Z = 4; R = 0.0787, wR2 = 0.1588. BPOH: C11H19N1O4; P1; a = 5.989(2) Å, b = 6.651(2) Å, c = 8.661(3) Å, α = 70.75(1)°, β = 77.42(1)°, γ = 86.98(1)°; Z = 1; R = 0.0562, wR2 = 0.1605. Chapter 5 describes a new class of polypeptide helices in hybrid sequences containing α-, β- and γ-residues. The molecular conformation in crystals determined for the octapeptide Boc-Leu-Phe-Val-Aib-(S)-β3-HPhe-Leu-Phe-Val-OMe (UBF8) reveals an expanded helical turn in the hybrid sequence (ααβ)n. A repetitive helical structure composed of C14 hydrogen bonded units is observed. Using experimentally determined backbone torsion angles for the hydrogen bonded units formed by hybrid sequences, the energetically favorable hybrid helices have been generated. Conformational parameters are provided for C11, C12, C13, C14 and C15 helices in hybrid sequences [5]. Crystal parameters UBF8: C60H88N8O11; P212121; a = 12.365(1) Å, b = 18.940(2) Å, c = 27.123(3) Å; Z = 4; R = 0.0625, wR2 = 0.1274. Chapter 6 describes the crystal structures of five model peptides Piv-Pro-Gly-NHMe (PA1), Piv-Pro-βGly-NHMe (PB1), Piv-Pro-βGly-OMe (PBO), Piv-Pro-δAva-OMe (PDAVA) and Boc-Pro-γAbu-OH (BGABU). A comparison of the structures of peptides PA1 and PB1 illustrates the dramatic consequences upon backbone homologation in short sequences. The molecule PA1 adopts a type II β-turn conformation in the crystal state, while in PB1, the molecule adopts an open conformation with the β-residue being fully extended. The peptide PBO, which differs from PB1 by replacement of the C-terminal NH group by an O-atom, adopts an almost identical molecular conformation and packing arrangement in the crystal state. In peptide PDAVA, the observed conformation resembles that determined for PB1 and PBO, with the δAva residue being fully extended. In peptide BGABU, the molecule undergoes a chain reversal, revealing a β-turn mimetic structure stabilized by a C-H…O hydrogen bond [6]. Crystal parameters PA1: C13H23N3O3; P1; a = 5.843(1) Å, b = 7.966(2) Å, c = 9.173(2) Å, α = 114.83(1)°, β = 97.04(1)°, γ = 99.45(1)°; Z = 1; R = 0.0365, wR2 = 0.0979. PB1: C14H25N3O3.H2O; P212121; a = 6.297(3) Å, b = 11.589(5) Å, c = 22.503(9) Å; Z = 4; R = 0.0439, wR2 = 0.1211. PBO: C14H24N2O4.H2O; P212121; a = 6.157(2) Å, b = 11.547(4) Å, c = 23.408(8) Å; Z = 4; R = 0.050, wR2 = 0.1379. PDAVA: C16H28N2O4.H2O; P21212; a = 11.33(1) Å, b = 25.56(2) Å, c = 6.243(6) Å; Z = 4; R = 0.0919, wR2 = 0.2344. BGABU: C14H24N2O5; P61; a = 9.759(2) Å, b = 9.759(2) Å, c = 29.16(1) Å; Z = 6; R = 0.0773, wR2 = 0.1243. Chapter 7 describes the crystal structures of a dipeptide, Boc-Aib-γAbu-OH (UG) and a tripeptide, Boc-Aib-γAbu-Aib-OMe (UGU) containing a single γAbu residue in each sequence. The structure of UG forms a reverse turn stabilized by a 10-membered intramolecular C-H…O hydrogen bonded ring. The peptide UGU crystallized in the triclinic space group P⎯1 with two molecules in the asymmetric unit resulting in a parallel assembly of sheets in crystals. Notably, the insertion of a single Aib residue at the C-terminus drastically changes the overall conformation of the structures. Crystal parameters UG: C13H24N2O5; P21/c; a = 16.749(3) Å, b = 5.825(1) Å, c = 16.975(3) Å; β = 111.82(1); Z = 4; R = 0.0507; wR2 = 0.1294. UGU: C18H33N3O6; P⎯1; a = 9.576(6) Å, b = 13.98(1) Å, c = 17.83(1); α = 85.31 (1); β = 77.46 (1); γ = 71.39 (1); Z = 4; R = 0.0648; wR2 = 0.1837.