Wong, Siu Lun. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (leaves 129-141). / Abstracts in English and Chinese. / Abstract --- p.i / Abstract (Chinese version) --- p.iii / Acknowledgements --- p.iv / List of Abbreviations --- p.v / List of Tables --- p.vii / List of Figures --- p.viii / Chapter 1. --- INTRODUCTION / Chapter 1.1 --- Neurodegenerative disorders - a brief overview --- p.1 / Chapter 1.2 --- Polyglutamine diseases --- p.2 / Chapter 1.3 --- Microscopically visible polyglutamine protein aggregates and its relation to toxicity --- p.7 / Chapter 1.4 --- Polyglutamine protein conformers and their relation to toxicity --- p.10 / Chapter 1.5 --- Modeling polyglutamine diseases in Drosophila / Chapter 1.5.1 --- GAL4/UAS spatial transgene expression system in Drosophila --- p.14 / Chapter 1.5.2 --- Temporal control of GAL4/UAS transgene expression system in Drosophila --- p.16 / Chapter 1.5.3 --- Drosophila as a model to study human pathologies --- p.19 / Chapter 1.5.4 --- Drosophila as a model to study polyglutamine diseases --- p.21 / Chapter 1.6 --- Aims of study --- p.26 / Chapter 2. --- MATERIALS AND METHODS / Chapter 2.1 --- Drosophila culture and manipulation / Chapter 2.1.1 --- Drosophila culture --- p.27 / Chapter 2.1.2 --- Phenotypic examination of adult external eye degeneration --- p.27 / Chapter 2.1.3 --- Pseudopupil assay of adult retinal degeneration and observation of green fluorescent protein in adult eyes --- p.28 / Chapter 2.2 --- Semi-quantitative Reverse Transcription-Polymerase Chain Reaction / Chapter 2.2.1 --- RNA extraction from adult Drosophila heads --- p.30 / Chapter 2.2.2 --- DNase treatment of extracted RNA --- p.31 / Chapter 2.2.3 --- Reverse transcription-Polymerase Chain Reaction (RT-PCR) --- p.31 / Chapter 2.2.4 --- Agarose gel electrophoresis --- p.33 / Chapter 2.3 --- Sodium Dodecyl Sulfate-Polyacrylamide Gel Electrophoresis (SDS-PAGE) / Chapter 2.3.1 --- Protein extraction from adult Drosophila heads --- p.33 / Chapter 2.3.2 --- Preparation of SDS-polyacrylamide gel and electrophoresis --- p.34 / Chapter 2.3.3 --- Western blotting --- p.35 / Chapter 2.3.4 --- Immunodetection --- p.36 / Chapter 2.4 --- Immunoprecipitation --- p.38 / Chapter 2.5 --- Filter retardation assay --- p.39 / Chapter 2.6 --- Isolation and solubilization of SDS-insoluble protein --- p.40 / Chapter 2.7 --- Sucrose gradient sedimentation --- p.41 / Chapter 2.8 --- Preparation of Drosophila tissues for immunofluorescence analysis / Chapter 2.8.1 --- Dissection and immunostaining of Drosophila larval imaginal eye discs --- p.42 / Chapter 2.8.2 --- Cryosectioning and immunostaining of adult Drosophila heads --- p.44 / Chapter 2.9 --- Atomic force microscopy --- p.47 / Chapter 2.10 --- Reagents and buffers / Chapter 2.10.1 --- Reagents for Drosophila culture --- p.48 / Chapter 2.10.2 --- Reagents for RT-PCR --- p.52 / Chapter 2.10.3 --- Reagents for SDS-PAGE --- p.54 / Chapter 2.10.4 --- Reagents for immunoprecipitation --- p.57 / Chapter 2.10.5 --- Reagents for filter retardation assay --- p.57 / Chapter 2.10.6 --- Reagents for isolation and solubilization of SDS-insoluble protein --- p.58 / Chapter 2.10.7 --- Reagents for sucrose gradient sedimentation --- p.58 / Chapter 2.10.8 --- Reagents for immunofluorescence --- p.59 / Chapter 3. --- RESULTS / Chapter 3.1 --- Establishment of an inducible transgenic Drosophila model of polyglutamine diseases / Chapter 3.1.1 --- Introduction --- p.60 / Chapter 3.1.2 --- Results / Chapter 3.1.2.1 --- GAL80ts-mediated inducible expression of expanded polyglutamine protein in Drosophila / Chapter 3.1.2.1.1 --- GAL80ts controls GAL4/UAS-mediated polyQ protein expression --- p.61 / Chapter 3.1.2.1.2 --- Inducible expression of SDS-soluble expanded polyglutamine protein --- p.64 / Chapter 3.1.2.1.3 --- Inducible expression of expanded polyglutamine protein accumulates gradually in form of SDS-insoluble protein --- p.66 / Chapter 3.1.2.1.4 --- Inducible expression of expanded polyglutamine protein results in progressive accumulation of microscopically visible aggregates --- p.68 / Chapter 3.1.2.2 --- Inducible expression of expanded polyglutamine protein causes late-onset progressive neuronal degeneration in Drosophila / Chapter 3.1.2.2.1 --- Inducible expression of expanded polyglutamine protein leads to late-onset progressive deterioration of photoreceptor neurons --- p.68 / Chapter 3.1.2.2.2 --- Inducible expression of expanded polyglutamine protein neither causes external eye degenerative phenotype nor disrupts gross retinal morphology despite deterioration of photoreceptor neurons --- p.72 / Chapter 3.1.2.3 --- Co-expression of caspase inhibitor P35 suppresses polyglutamine-induced neuronal degeneration --- p.72 / Chapter 3.1.2.4 --- Co-expression of molecular chaperone Hsp70 suppresses polyglutamine-induced neuronal degeneration --- p.74 / Chapter 3.1.2.5 --- Inducible expression of expanded polyglutamine protein results in biphasic expression of molecular chaperone Hsp70 in Drosophila --- p.76 / Chapter 3.1.3 --- Discussion --- p.76 / Chapter 3.2 --- Involvement of microscopically visible polyglutamine aggregates in neurodegeneration / Chapter 3.2.1 --- Introduction --- p.83 / Chapter 3.2.2 --- Results / Chapter 3.2.2.1 --- Effect of Hsc70-K71S on microscopically visible polyglutamine aggregates and neuronal degeneration / Chapter 3.2.2.1.1 --- Co-expression of Hsc70-K71S reduces the level of microscopically visible polyglutamine aggregates --- p.83 / Chapter 3.2.2.1.2 --- Co-expression of Hsc70-K71S does not alter polyglutamine transgene expression --- p.84 / Chapter 3.2.2.1.3 --- Co-expression of Hsc70-K71S does not modify polyglutamine-induced neuronal degeneration --- p.87 / Chapter 3.2.2.2 --- Microscopically visible polyglutamine aggregates do not correlate with neuronal degeneration --- p.90 / Chapter 3.2.3 --- Discussion --- p.93 / Chapter 3.3 --- Detection of small SDS-insoluble expanded polyglutamine protein species and its association with neurodegeneration / Chapter 3.3.1 --- Introduction --- p.97 / Chapter 3.3.2 --- Results / Chapter 3.3.2.1 --- Accumulation of SDS-soluble expanded polyglutamine protein does not correlate with neuronal degeneration --- p.98 / Chapter 3.3.2.2 --- Identification of small SDS-insoluble expanded polyglutamine protein species / Chapter 3.3.2.2.1 --- Accumulation of total SDS-insoluble expanded polyglutamine protein positively correlates with progressive neuronal degeneration --- p.99 / Chapter 3.3.2.2.2 --- Accumulation of large SDS-insoluble expanded polyglutamine protein does not correlate with neuronal degeneration --- p.99 / Chapter 3.3.2.2.3 --- Accumulation of small SDS-insoluble expanded polyglutamine protein correlates with neuronal degeneration --- p.104 / Chapter 3.3.3 --- Discussion --- p.107 / Chapter 3.4 --- Biophysical characterization of small SDS-insoluble expanded polyglutamine protein species / Chapter 3.4.1 --- Introduction --- p.109 / Chapter 3.4.2 --- Results / Chapter 3.4.2.1 --- Separation of expanded polyglutamine protein species by sucrose gradient sedimentation --- p.110 / Chapter 3.4.2.2 --- Morphological studies of small SDS-insoluble expanded polyglutamine protein species by atomic force microscopy --- p.112 / Chapter 3.4.3 --- Discussion --- p.118 / Chapter 4. --- GENERAL DISCUSSION --- p.124 / Chapter 5. --- CONCLUSION --- p.127 / Chapter 6. --- REFERENCES --- p.129

No description available.

Indiana University-Purdue University Indianapolis (IUPUI) / Intrinsically disordered proteins (IDPs) are abundant in nature, being more prevalent in the proteomes of eukaryotes than those of bacteria or archaea. As introduced in Chapter I, these proteins, or portions of these proteins, lack stable equilibrium structures and instead have dynamic conformations that vary over time and population. Despite the lack of preformed structure, IDPs carry out many and varied molecular functions and participate in vital biological pathways. In particular, IDPs play important roles in cellular signaling that is, in part, enabled by the ability of IDPs to mediate molecular recognition. In Chapter II, the role of intrinsic disorder in molecular recognition is examined through two example IDPs: p53 and 14-3-3. The p53 protein uses intrinsically disordered regions at its N- and C-termini to interact with a large number of partners, often using the same residues. The 14-3-3 protein is a structured domain that uses the same binding site to recognize multiple intrinsically disordered partners. Examination of the structural details of these interactions highlights the importance of intrinsic disorder and induced fit in molecular recognition. More generally, many intrinsically disordered regions that mediate interactions share similar features that are identifiable from protein sequence. Chapter IV reviews several models of IDP mediated protein-protein interactions that use completely different parameterizations. Each model has its relative strengths in identifying novel interaction regions, and all suggest that IDP mediated interactions are common in nature. In addition to the biologic importance of IDPs, they are also practically important in the structural study of proteins. The presence of intrinsic disordered regions can inhibit crystallization and solution NMR studies of otherwise well-structured proteins. This problem is compounded in the context of high throughput structure determination. In Chapter III, the effect of IDPs on structure determination by X-ray crystallography is examined. It is found that protein crystals are intolerant of intrinsic disorder by examining existing crystal structures from the PDB. A retrospective analysis of Protein Structure Initiative data indicates that prediction of intrinsic disorder may be useful in the prioritization and improvement of targets for structure determination.

Fundação Araucária / A Predição da Estrutura das Proteínas, conhecida como PSP (Protein Structure Prediction) pode ser considerada um dos problemas mais desafiadores da Bioinformática atualmente. Quando uma proteína está em seu estado de conformação nativa, a energia livre tende para um valor mínimo. Em geral, a predição da conformação de uma proteína por métodos computacionais é feita pela estimativa de dois valores de energia livre que são provenientes das interações intra e intermoleculares entre os átomos. Alguns estudos recentes indicam que estas interações estão em conflito, justificando o uso de abordagens baseadas em otimização multiobjetivo para a solução do PSP. Neste caso, a otimização destas energias é realizada separadamente, diferente da formulação mono-objetivo que considera a soma das energias. A Evolução Diferencial (ED) é uma técnica baseada em Computação Evolucionária e representa uma alternativa interessante para abordar o PSP. Este trabalho busca desenvolver um otimizador baseado no algoritmo de ED para o problema da Predição da Estrutura de Proteínas multiobjetivo. Este trabalho investiga ainda estratégias baseadas em parâmetros adaptativos para a evolução diferencial. Nicialmente avalia-se uma abordagem simples baseada em ED proposta para a solução do PSP. Uma evolução deste método que incorpora conceitos do algoritmo MOEA/D e adaptação de parâmetros é testada em um conjunto de problemas benchmark de otimização multiobjetivo. Os resultados preliminares obtidos para o PSP (para seis proteínas reais) são promissores e aqueles obtidos para o conjunto benchmark colocam a abordagem proposta como candidata para otimização multiobjetivo. / Protein Structure Prediction (PSP) can be considered one of the most challenging problems in Bioinformatics nowadays. When a protein is in its conformation state, the free energy is minimized. Evaluation of protein conformation is generally performed based on two values of the estimated free energy, i.e., those provided by intra and intermolecular interactions among atoms. Some recent experimental studies show that these interactions are in conflit, justifying the use of multiobjective optimization approaches to solve PSP. In this case, the energy optimization is performed separately, different from the mono-objective optimization which considers the sum of free energy. Differential Evolution (DE) is a technique based on Evolutionary Computation and represents an interesting alternative to solve multiobjective PSP. In this work, an optimizer based on DE is proposed to solve the PSP problem. Due to the great number of parameters, typical for evolutionary algorithms, this work also investigates adaptive parameters strategies. In experiments, a simple approach based on ED is evaluated for PSP. An evolution for this method, which incorporates concepts of the MOEA/D algorithm and parameter adaptation techniques is tested for a set of benchmarks in the multiobjective optimization context. The preliminary results for PSP (for six real proteins) are promising and those obtained for the benchmark set stands the proposed approach as a candidate to the state-of-art for multiobjective optimization.

Fundação Araucária / A Predição da Estrutura das Proteínas, conhecida como PSP (Protein Structure Prediction) pode ser considerada um dos problemas mais desafiadores da Bioinformática atualmente. Quando uma proteína está em seu estado de conformação nativa, a energia livre tende para um valor mínimo. Em geral, a predição da conformação de uma proteína por métodos computacionais é feita pela estimativa de dois valores de energia livre que são provenientes das interações intra e intermoleculares entre os átomos. Alguns estudos recentes indicam que estas interações estão em conflito, justificando o uso de abordagens baseadas em otimização multiobjetivo para a solução do PSP. Neste caso, a otimização destas energias é realizada separadamente, diferente da formulação mono-objetivo que considera a soma das energias. A Evolução Diferencial (ED) é uma técnica baseada em Computação Evolucionária e representa uma alternativa interessante para abordar o PSP. Este trabalho busca desenvolver um otimizador baseado no algoritmo de ED para o problema da Predição da Estrutura de Proteínas multiobjetivo. Este trabalho investiga ainda estratégias baseadas em parâmetros adaptativos para a evolução diferencial. Nicialmente avalia-se uma abordagem simples baseada em ED proposta para a solução do PSP. Uma evolução deste método que incorpora conceitos do algoritmo MOEA/D e adaptação de parâmetros é testada em um conjunto de problemas benchmark de otimização multiobjetivo. Os resultados preliminares obtidos para o PSP (para seis proteínas reais) são promissores e aqueles obtidos para o conjunto benchmark colocam a abordagem proposta como candidata para otimização multiobjetivo. / Protein Structure Prediction (PSP) can be considered one of the most challenging problems in Bioinformatics nowadays. When a protein is in its conformation state, the free energy is minimized. Evaluation of protein conformation is generally performed based on two values of the estimated free energy, i.e., those provided by intra and intermolecular interactions among atoms. Some recent experimental studies show that these interactions are in conflit, justifying the use of multiobjective optimization approaches to solve PSP. In this case, the energy optimization is performed separately, different from the mono-objective optimization which considers the sum of free energy. Differential Evolution (DE) is a technique based on Evolutionary Computation and represents an interesting alternative to solve multiobjective PSP. In this work, an optimizer based on DE is proposed to solve the PSP problem. Due to the great number of parameters, typical for evolutionary algorithms, this work also investigates adaptive parameters strategies. In experiments, a simple approach based on ED is evaluated for PSP. An evolution for this method, which incorporates concepts of the MOEA/D algorithm and parameter adaptation techniques is tested for a set of benchmarks in the multiobjective optimization context. The preliminary results for PSP (for six real proteins) are promising and those obtained for the benchmark set stands the proposed approach as a candidate to the state-of-art for multiobjective optimization.

Cette thèse de doctorat s’inscrit dans le cadre de l’étude in silico des relations qui lient la séquence d’une protéine à sa structure, sa stabilité et sa fonction. Elle a pour objectif de permettre à terme la conception rationnelle de protéines modifiées qui restent actives dans des conditions physico chimiques non physiologiques. Nous nous sommes plus particulièrement penchés sur la stabilité thermique des protéines, qui est définie par leur température de fusion Tm au delà de laquelle leur structure n’est thermodynamiquement plus stable. Notre travail s’articule en trois grandes parties :la recherche de facteurs favorisant la thermostabilité des protéines parmi des familles de protéines homologues, la mise sur pied d’une base de données de protéines de structure et de Tm déterminées expérimentalement, de laquelle sont dérivés des potentiels statistiques dépendant de la température, et enfin la mise au point de deux outils bioinformatiques visant à prédire d’une part la Tm d’une protéine à partir de la Tm de protéines homologues et d’autre part les changements de thermostabilité d’une protéine (Tm) engendrés par l’introduction d’une mutation ponctuelle.<p><p>La première partie a pour objectif l’identification des facteurs de séquence et de structure (e.g. fréquence de ponts salins, d’interactions cation-{pi}) responsables des différentes stabilités thermiques de protéines homologues au sein de huit familles (chapitre 2). La spécificité de chaque famille ne nous a pas permis de généraliser l’impact de ces différents facteurs sur la stabilité thermique des protéines. Cependant, cette approche nous a permis de constater la multitude de stratégies différentes suivies par les protéines pour atteindre une plus grande thermostabilité.<p><p>La deuxième partie concerne le développement d’une approche originale pour évaluer l’influence de la température sur la contribution de différents types d’interactions à l’énergie libre de repliement des protéines (chapitres 3 et 4). Cette approche repose sur la dérivation de potentiels statistiques à partir d’ensembles de protéines de thermostabilité moyenne distincte. Nous avons d’une part collecté le plus grand nombre possible de protéines de structure et de Tm déterminées expérimentalement, et d’autre part développé des potentiels tenant compte de l’adaptation des protéines aux températures extrêmes au cours de leur évolution. Cette méthode originale a mis en évidence la dépendance en la température d’interactions protéiques tels les ponts salins, les interactions cation-{pi}, certains empilements hydrophobes .Elle nous a en outre permis de mettre le doigt sur l’importance de considérer la dépendance en la température non seulement des interactions attractives mais également des interactions répulsives, ainsi que sur l’importance de décrire la résistance thermique par la Tm plutôt que la Tenv, température de l’environnement de l’organisme dont elle provient (chapitre 5).<p><p>La dernière partie de cette thèse concerne l’utilisation des profils énergétiques dans un but prédictif. Tout d’abord, nous avons développé un logiciel bioinformatique pour prédire la thermostabilité d’une protéine sur la base de la thermostabilité de protéines homologues. Cet outil s’est avéré prometteur après l’avoir testé sur huit familles de protéines homologues. Nous avons également développé un deuxième outil bioinformatique pour prédire les changements de thermostabilité d’une protéine engendrés par l’introduction d’une mutation ponctuelle, en s’inspirant d’un logiciel de prédiction des changements de stabilité thermodynamique des protéines développé au sein de notre équipe de recherche. Ce deuxième algorithme de prédiction repose sur le développement d’une grande base de données de mutants caractérisés expérimentalement, d’une combinaison linéaire de potentiels pour évaluer la Tm, et d’un réseau de neurones pour identifier les coefficients de la combinaison. Les prédictions générées par notre logiciel ont été comparées à celles obtenues via la corrélation qui existe entre stabilités thermique et thermodynamique, et se sont avérées plus fiables.<p><p>Les travaux décrits dans notre thèse, et en particulier le développement de potentiels statistiques dépendant de la température, constituent une nouvelle approche très prometteuse pour comprendre et prédire la thermostabilité des protéines. En outre, nos travaux de recherche ont permis de développer une méthodologie qui pourra être adaptée à l’étude et à la prédiction d’autres propriétés physico chimiques des protéines comme leur solubilité, leur stabilité vis à vis de l’acidité, de la pression, de la salinité .lorsque suffisamment de données expérimentales seront disponibles.<p> / Doctorat en Sciences agronomiques et ingénierie biologique / info:eu-repo/semantics/nonPublished

Indiana University-Purdue University Indianapolis (IUPUI) / Disruptions of the endoplasmic reticulum (ER) cause perturbations in protein folding and result in a cellular condition known as ER stress. ER stress and the accumulation of unfolded protein activate the unfolded protein response (UPR) which is a cellular attempt to remedy the toxic accumulation of unfolded proteins. The UPR is implemented through three ER stress sensors PERK, ATF6, and IRE1. Phosphorylation of the α-subunit of eIF2 by PERK during ER stress represses protein synthesis and also induces preferential translation of ATF4, a transcriptional activator of stress response genes. Early UPR signaling involves translational and transcriptional changes in gene expression that is geared toward stress remedy. However, prolonged ER stress that is not alleviated can trigger apoptosis. This dual signaling nature of the UPR is proposed to mimic a 'binary switch' and the regulation of this switch is a key topic of this thesis. Adaptive gene expression aimed at balancing protein homeostasis encompasses the first phase of the UPR. In this study we show that the PERK/eIF2~P/ATF4 pathway facilitates both the synthesis of ATF6 and trafficking of ATF6 from the ER to the Golgi where ATF6 is activated. Liver-specific depletion of PERK significantly lowers expression of survival genes, leading to reduced expression of protein chaperones. As a consequence, loss of PERK in the liver sensitizes cells to stress which ultimately leads to apoptosis. Despite important roles in survival, PERK signaling is often extended to the vii activation of other downstream transcription factors such as CHOP, a direct target of ATF4-mediated transcription. Accumulation of CHOP is a hallmark of the second phase in the binary switch model where CHOP is shown to be required for full activation of apoptosis. Here the transcription factor ATF5 is found to be induced by CHOP and that loss of ATF5 improves the survival of cells following changes in protein homeostasis. Taken together this study highlights the importance of UPR signaling in determining the balance between cell survival and cell death. A topic that is important for understanding the more complex pathological conditions of diseases such as diabetes, cancer, and neurodegeneration.

Indiana University-Purdue University Indianapolis (IUPUI) / Intrinsically disordered proteins (IDPs) are flexible proteins without defined 3D structures. Studies show that IDPs are abundant in nature and actively involved in numerous biological processes. Two crucial subjects in the study of IDPs lie in analyzing IDPs’ functions and identifying them. We thus carried out three projects to better understand IDPs. In the 1st project, we propose a method that separates IDPs into different function groups. We used the approach of CH-CDF plot, which is based the combined use of two predictors and subclassifies proteins into 4 groups: structured, mixed, disordered, and rare. Studies show different structural biases for each group. The mixed class has more order-promoting residues and more ordered regions than the disordered class. In addition, the disordered class is highly active in mitosis-related processes among others. Meanwhile, the mixed class is highly associated with signaling pathways, where having both ordered and disordered regions could possibly be important. The 2nd project is about identifying if an unknown protein is entirely disordered. One of the earliest predictors for this purpose, the charge-hydropathy plot (C-H plot), exploited the charge and hydropathy features of the protein. Not only is this algorithm simple yet powerful, its input parameters, charge and hydropathy, are informative and readily interpretable. We found that using different hydropathy scales significantly affects the prediction accuracy. Therefore, we sought to identify a new hydropathy scale that optimizes the prediction. This new scale achieves an accuracy of 91%, a significant improvement over the original 79%. In our 3rd project, we developed a per-residue C-H IDP predictor, in which three hydropathy scales are optimized individually. This is to account for the amino acid composition differences in three regions of a protein sequence (N, C terminus and internal). We then combined them into a single per-residue predictor that achieves an accuracy of 74% for per-residue predictions for proteins containing long IDP regions.

Indiana University-Purdue University Indianapolis (IUPUI) / Proteasome assembly is a rapid and highly sequential process that occurs through a series of intermediates. While the quest to understand the exact process of assembly is ongoing, there remains an incomplete understanding of what happens early on during the process, prior to the involvement of the β subunits. A significant feature of proteasome assembly is the property of proteasomal subunits to self-assemble. While archaeal α and β subunits from Thermoplasma acidophilum can assemble into entire 20S units in vitro, certain α subunits from divergent species have a property to self-assemble into single and double heptameric rings. In this study, we have shown that recombinant α subunits from Methanococcus maripaludis also have a tendency to self-assemble into higher order structures when expressed in E. coli. Using a novel cross-linking strategy, we were able to establish that these higher order structures were double α rings that are structurally similar to a half-proteasome (i.e. an α-β ring pair). Our experiments on M. maripaludis α subunits represent the first biochemical evidence for the orientation of rings in an α ring dimer. We also investigated self-assembly of α subunits in S. cerevisiae and attempted to characterize a highly stable and unique high molecular weight complex (HMWC) that is formed upon co-expression of α5, α6, α7 and α1 in E. coli. Using our cross-linking strategy, we were able to show that this complex is a double α ring in which, at the least, one α1 subunit is positioned across itself. We were also able to detect α1-α1 crosslinks in high molecular weight complexes that are formed when α7 and α1 are co-expressed, and when α6, α7 and α1 are co-expressed in E. coli. The fact that we able to observe α1-α1 crosslinks in higher order structures that form whenever α7 and α1 were present suggests that α1-α1 crosslinks might be able to serve as potential trackers to detect HMWCs in vivo. This would be an important step in determining if these HMWCs represent bona fide assembly intermediates, or dead-end complexes whose formation must be prevented in order to ensure efficient proteasome assembly.

Indiana University-Purdue University Indianapolis (IUPUI) / Computational protein design aims at designing amino acid sequences that can fold into a target structure and perform a desired function. Many computational design methods have been developed and their applications have been successful during past two decades. However, the success rate of protein design remains too low to be of a useful tool by biochemists whom are not an expert of computational biology. In this dissertation, we first developed novel computational assessment techniques to assess several state-of-the-art computational techniques. We found that significant progresses were made in several important measures by two new scoring functions from RosettaDesign and from OSCAR-design, respectively. We also developed the first machine-learning technique called SPIN that predicts a sequence profile compatible to a given structure with a novel nonlocal energy-based feature. The accuracy of predicted sequences is comparable to RosettaDesign in term of sequence identity to wild type sequences. In the last two application chapters, we have designed self-inhibitory peptides of Escherichia coli methionine aminopeptidase (EcMetAP) and de novo designed barstar. Several peptides were confirmed inhibition of EcMetAP at the micromole-range 50% inhibitory concentration. Meanwhile, the assessment of designed barstar sequences indicates the improvement of OSCAR-design over RosettaDesign.