A novel approach for the identification of protein–protein interaction with integral membrane proteins

Protein–protein interaction plays a major role in all biological processes. The currently available genetic methods such as the two-hybrid system and the protein recruitment system are relatively limited in their ability to identify interactions with integral membrane proteins. Here we describe the development of a reverse Ras recruitment system (reverse RRS), in which the bait used encodes a membrane protein. The bait is expressed in its natural environment, the membrane, whereas the protein partner (the prey) is fused to a cytoplasmic Ras mutant. Protein–protein interaction between the proteins encoded by the prey and the bait results in Ras membrane translocation and activation of a viability pathway in yeast. We devised the expression of the bait and prey proteins under the control of dual distinct inducible promoters, thus enabling a rapid selection of transformants in which growth is attributed solely to specific protein–protein interaction. The reverse RRS approach greatly extends the usefulness of the protein recruitment systems and the use of integral membrane proteins as baits. The system serves as an attractive approach to explore novel protein–protein interactions with high specificity and selectivity, where other methods fail.

Interaction of the human androgen receptor transactivation function with the general transcription factor TFIIF

The human androgen receptor (AR) is a ligand-activated transcription factor that regulates genes important for male sexual differentiation and development. To better understand the role of the receptor as a transcription factor we have studied the mechanism of action of the N-terminal transactivation function. In a protein–protein interaction assay the AR N terminus (amino acids 142–485) selectively bound to the basal transcription factors TFIIF and the TATA-box-binding protein (TBP). Reconstitution of the transactivation activity in vitro revealed that AR142–485 fused to the LexA protein DNA-binding domain was competent to activate a reporter gene in the presence of a competing DNA template lacking LexA binding sites. Furthermore, consistent with direct interaction with basal transcription factors, addition of recombinant TFIIF relieved squelching of basal transcription by AR142–485. Taken together these results suggest that one mechanism of transcriptional activation by the AR involves binding to TFIIF and recruitment of the transcriptional machinery.

Interaction of the copper chaperone HAH1 with the Wilson disease protein is essential for copper homeostasis

The delivery of copper to specific sites within the cell is mediated by distinct intracellular carrier proteins termed copper chaperones. Previous studies in Saccharomyces cerevisiae suggested that the human copper chaperone HAH1 may play a role in copper trafficking to the secretory pathway of the cell. In this current study, HAH1 was detected in lysates from multiple human cell lines and tissues as a single-chain protein distributed throughout the cytoplasm and nucleus. Studies with a glutathione S-transferase-HAH1 fusion protein demonstrated direct protein–protein interaction between HAH1 and the Wilson disease protein, which required the cysteine copper ligands in the amino terminus of HAH1. Consistent with these in vitro observations, coimmunoprecipitation experiments revealed that HAH1 interacts with both the Wilson and Menkes proteins in vivo and that this interaction depends on available copper. When these studies were repeated utilizing three disease-associated mutations in the amino terminus of the Wilson protein, a marked diminution in HAH1 interaction was observed, suggesting that impaired copper delivery by HAH1 constitutes the molecular basis of Wilson disease in patients harboring these mutations. Taken together, these data provide a mechanism for the function of HAH1 as a copper chaperone in mammalian cells and demonstrate that this protein is essential for copper homeostasis.

The Interaction and Colocalization of Sam68 with the Splicing-associated Factor YT521-B in Nuclear Dots Is Regulated by the Src Family Kinase p59fyn

Alternative pre-mRNA splicing patterns can change an extracellular stimulus, but the signaling pathways leading to these changes are still poorly characterized. Here, we describe a tyrosine-phosphorylated nuclear protein, YT521-B, and show that it interacts with the nuclear transcriptosomal component scaffold attachment factor B, and the 68-kDa Src substrate associated during mitosis, Sam68. Northern blot analysis demonstrated ubiquitous expression, but detailed RNA in situ analysis revealed cell type specificity in the brain. YT521-B protein is localized in the nucleoplasm and concentrated in 5–20 large nuclear dots. Deletion analysis demonstrated that the formation of these dots depends on the presence of the amino-terminal glutamic acid-rich domain and the carboxyl-terminal glutamic acid/arginine-rich region. We show that the latter comprises an important protein–protein interaction domain. The Src family kinase p59fyn-mediated tyrosine phosphorylation of Sam68 negatively regulates its association with YT521-B, and overexpression of p59fyn dissolves nuclear dots containing YT521-B. In vivo splicing assays demonstrated that YT521-B modulates alternative splice site selection in a concentration-dependent manner. Together, our data indicate that YT521-B and Sam68 may be part of a signal transduction pathway that influences splice site selection.

PartsList: a web-based system for dynamically ranking protein folds based on disparate attributes, including whole-genome expression and interaction information

As the number of protein folds is quite limited, a mode of analysis that will be increasingly common in the future, especially with the advent of structural genomics, is to survey and re-survey the finite parts list of folds from an expanding number of perspectives. We have developed a new resource, called PartsList, that lets one dynamically perform these comparative fold surveys. It is available on the web at http://bioinfo.mbb.yale.edu/partslist and http://www.partslist.org. The system is based on the existing fold classifications and functions as a form of companion annotation for them, providing ‘global views’ of many already completed fold surveys. The central idea in the system is that of comparison through ranking; PartsList will rank the approximately 420 folds based on more than 180 attributes. These include: (i) occurrence in a number of completely sequenced genomes (e.g. it will show the most common folds in the worm versus yeast); (ii) occurrence in the structure databank (e.g. most common folds in the PDB); (iii) both absolute and relative gene expression information (e.g. most changing folds in expression over the cell cycle); (iv) protein–protein interactions, based on experimental data in yeast and comprehensive PDB surveys (e.g. most interacting fold); (v) sensitivity to inserted transposons; (vi) the number of functions associated with the fold (e.g. most multi-functional folds); (vii) amino acid composition (e.g. most Cys-rich folds); (viii) protein motions (e.g. most mobile folds); and (ix) the level of similarity based on a comprehensive set of structural alignments (e.g. most structurally variable folds). The integration of whole-genome expression and protein–protein interaction data with structural information is a particularly novel feature of our system. We provide three ways of visualizing the rankings: a profiler emphasizing the progression of high and low ranks across many pre-selected attributes, a dynamic comparer for custom comparisons and a numerical rankings correlator. These allow one to directly compare very different attributes of a fold (e.g. expression level, genome occurrence and maximum motion) in the uniform numerical format of ranks. This uniform framework, in turn, highlights the way that the frequency of many of the attributes falls off with approximate power-law behavior (i.e. according to V–b, for attribute value V and constant exponent b), with a few folds having large values and most having small values.

Nitrogen regulation of protein–protein interactions and transcript levels of GlnK PII regulator and AmtB ammonium transporter homologs in Archaea

Gene homologs of GlnK PII regulators and AmtB-type ammonium transporters are often paired on prokaryotic genomes, suggesting these proteins share an ancient functional relationship. Here, we demonstrate for the first time in Archaea that GlnK associates with AmtB in membrane fractions after ammonium shock, thus, providing a further insight into GlnK-AmtB as an ancient nitrogen sensor pair. For this work, Haloferax mediterranei was advanced for study through the generation of a pyrE2-based counterselection system that was used for targeted gene deletion and expression of Flag-tagged proteins from their native promoters. AmtB1-Flag was detected in membrane fractions of cells grown on nitrate and was found to coimmunoprecipitate with GlnK after ammonium shock. Thus, in analogy to bacteria, the archaeal GlnK PII may block the AmtB1 ammonium transporter under nitrogen-rich conditions. In addition to this regulated protein–protein interaction, the archaeal amtB-glnK gene pairs were found to be highly regulated by nitrogen availability with transcript levels high under conditions of nitrogen limitation and low during nitrogen excess. While transcript levels of glnK-amtB are similarly regulated by nitrogen availability in bacteria, transcriptional regulators of the bacterial glnK promoter including activation by the two-component signal transduction proteins NtrC (GlnG, NRI) and NtrB (GlnL, NRII) and sigma factor σN (σ54) are not conserved in archaea suggesting a novel mechanism of transcriptional control.

Regulation of ammonium assimilation in Haloferax mediterranei: Interaction between glutamine synthetase and two GlnK proteins

GlnK proteins belong to the PII superfamily of signal transduction proteins and are involved in the regulation of nitrogen metabolism. These proteins are normally encoded in an operon together with the structural gene for the ammonium transporter AmtB. Haloferax mediterranei possesses two genes encoding for GlnK, specifically, glnK1 and glnK2. The present study marks the first investigation of PII proteins in haloarchaea, and provides evidence for the direct interaction between glutamine synthetase and both GlnK1 and GlnK2. Complex formation between glutamine synthetase and the two GlnK proteins is demonstrated with pure recombinant protein samples using in vitro activity assays, gel filtration chromatography and western blotting. This protein–protein interaction increases glutamine synthetase activity in the presence of 2-oxoglutarate. Separate experiments that were carried out with GlnK1 and GlnK2 produced equivalent results.

Multifractal characterisation and analysis of complex networks

Complex networks have been studied extensively due to their relevance to many real-world systems such as the world-wide web, the internet, biological and social systems. During the past two decades, studies of such networks in different fields have produced many significant results concerning their structures, topological properties, and dynamics. Three well-known properties of complex networks are scale-free degree distribution, small-world effect and self-similarity. The search for additional meaningful properties and the relationships among these properties is an active area of current research. This thesis investigates a newer aspect of complex networks, namely their multifractality, which is an extension of the concept of selfsimilarity. The first part of the thesis aims to confirm that the study of properties of complex networks can be expanded to a wider field including more complex weighted networks. Those real networks that have been shown to possess the self-similarity property in the existing literature are all unweighted networks. We use the proteinprotein interaction (PPI) networks as a key example to show that their weighted networks inherit the self-similarity from the original unweighted networks. Firstly, we confirm that the random sequential box-covering algorithm is an effective tool to compute the fractal dimension of complex networks. This is demonstrated on the Homo sapiens and E. coli PPI networks as well as their skeletons. Our results verify that the fractal dimension of the skeleton is smaller than that of the original network due to the shortest distance between nodes is larger in the skeleton, hence for a fixed box-size more boxes will be needed to cover the skeleton. Then we adopt the iterative scoring method to generate weighted PPI networks of five species, namely Homo sapiens, E. coli, yeast, C. elegans and Arabidopsis Thaliana. By using the random sequential box-covering algorithm, we calculate the fractal dimensions for both the original unweighted PPI networks and the generated weighted networks. The results show that self-similarity is still present in generated weighted PPI networks. This implication will be useful for our treatment of the networks in the third part of the thesis. The second part of the thesis aims to explore the multifractal behavior of different complex networks. Fractals such as the Cantor set, the Koch curve and the Sierspinski gasket are homogeneous since these fractals consist of a geometrical figure which repeats on an ever-reduced scale. Fractal analysis is a useful method for their study. However, real-world fractals are not homogeneous; there is rarely an identical motif repeated on all scales. Their singularity may vary on different subsets; implying that these objects are multifractal. Multifractal analysis is a useful way to systematically characterize the spatial heterogeneity of both theoretical and experimental fractal patterns. However, the tools for multifractal analysis of objects in Euclidean space are not suitable for complex networks. In this thesis, we propose a new box covering algorithm for multifractal analysis of complex networks. This algorithm is demonstrated in the computation of the generalized fractal dimensions of some theoretical networks, namely scale-free networks, small-world networks, random networks, and a kind of real networks, namely PPI networks of different species. Our main finding is the existence of multifractality in scale-free networks and PPI networks, while the multifractal behaviour is not confirmed for small-world networks and random networks. As another application, we generate gene interactions networks for patients and healthy people using the correlation coefficients between microarrays of different genes. Our results confirm the existence of multifractality in gene interactions networks. This multifractal analysis then provides a potentially useful tool for gene clustering and identification. The third part of the thesis aims to investigate the topological properties of networks constructed from time series. Characterizing complicated dynamics from time series is a fundamental problem of continuing interest in a wide variety of fields. Recent works indicate that complex network theory can be a powerful tool to analyse time series. Many existing methods for transforming time series into complex networks share a common feature: they define the connectivity of a complex network by the mutual proximity of different parts (e.g., individual states, state vectors, or cycles) of a single trajectory. In this thesis, we propose a new method to construct networks of time series: we define nodes by vectors of a certain length in the time series, and weight of edges between any two nodes by the Euclidean distance between the corresponding two vectors. We apply this method to build networks for fractional Brownian motions, whose long-range dependence is characterised by their Hurst exponent. We verify the validity of this method by showing that time series with stronger correlation, hence larger Hurst exponent, tend to have smaller fractal dimension, hence smoother sample paths. We then construct networks via the technique of horizontal visibility graph (HVG), which has been widely used recently. We confirm a known linear relationship between the Hurst exponent of fractional Brownian motion and the fractal dimension of the corresponding HVG network. In the first application, we apply our newly developed box-covering algorithm to calculate the generalized fractal dimensions of the HVG networks of fractional Brownian motions as well as those for binomial cascades and five bacterial genomes. The results confirm the monoscaling of fractional Brownian motion and the multifractality of the rest. As an additional application, we discuss the resilience of networks constructed from time series via two different approaches: visibility graph and horizontal visibility graph. Our finding is that the degree distribution of VG networks of fractional Brownian motions is scale-free (i.e., having a power law) meaning that one needs to destroy a large percentage of nodes before the network collapses into isolated parts; while for HVG networks of fractional Brownian motions, the degree distribution has exponential tails, implying that HVG networks would not survive the same kind of attack.

Computational identification of self-inhibitory peptides from envelope proteins

Fusion process is known to be the initial step of viral infection and hence targeting the entry process is a promising strategy to design antiviral therapy. The self-inhibitory peptides derived from the enveloped (E) proteins function to inhibit the proteinprotein interactions in the membrane fusion step mediated by the viral E protein. Thus, they have the potential to be developed into effective antiviral therapy. Herein, we have developed a Monte Carlo-based computational method with the aim to identify and optimize potential peptide hits from the E proteins. The stability of the peptides, which indicates their potential to bind in situ to the E proteins, was evaluated by two different scoring functions, dipolar distance-scaled, finite, ideal-gas reference state and residue-specific all-atom probability discriminatory function. The method was applied to a-helical Class I HIV-1 gp41, beta-sheet Class II Dengue virus (DENV) type 2 E proteins, as well as Class III Herpes Simplex virus-1 (HSV-1) glycoprotein, a E protein with a mixture of a-helix and beta-sheet structural fold. The peptide hits identified are in line with the druggable regions where the self-inhibitory peptide inhibitors for the three classes of viral fusion proteins were derived. Several novel peptides were identified from either the hydrophobic regions or the functionally important regions on Class II DENV-2 E protein and Class III HSV-1 gB. They have potential to disrupt the proteinprotein interaction in the fusion process and may serve as starting points for the development of novel inhibitors for viral E proteins. 

Network signatures based on gene pair expression ratios improve classification and the analysis of muscle-invasive urothelial cancer

Urothelial cancer (UC) is highly recurrent and can progress from non-invasive (NMIUC) to a more aggressive muscle-invasive (MIUC) subtype that invades the muscle tissue layer of the bladder. We present a proof of principle study that network-based features of gene pairs can be used to improve classifier performance and the functional analysis of urothelial cancer gene expression data. In the first step of our procedure each individual sample of a UC gene expression dataset is inflated by gene pair expression ratios that are defined based on a given network structure. In the second step an elastic net feature selection procedure for network-based signatures is applied to discriminate between NMIUC and MIUC samples. We performed a repeated random subsampling cross validation in three independent datasets. The network signatures were characterized by a functional enrichment analysis and studied for the enrichment of known cancer genes. We observed that the network-based gene signatures from meta collections of proteinprotein interaction (PPI) databases such as CPDB and the PPI databases HPRD and BioGrid improved the classification performance compared to single gene based signatures. The network based signatures that were derived from PPI databases showed a prominent enrichment of cancer genes (e.g., TP53, TRIM27 and HNRNPA2Bl). We provide a novel integrative approach for large-scale gene expression analysis for the identification and development of novel diagnostical targets in bladder cancer. Further, our method allowed to link cancer gene associations to network-based expression signatures that are not observed in gene-based expression signatures.

A further investigation of the cytochrome b5–cytochrome c complex

J Biol Inorg Chem (2003) 8: 777–786

Pathogenèse moléculaire de la neuropathie sensitive et motrice héréditaire avec agénésie du corps calleux

La neuropathie sensitive et motrice héréditaire avec agénésie du corps calleux (NSMH/ACC) se traduit par une atteinte neurodégénérative sévère associée à des anomalies développementales dans le système nerveux central et du retard mental. Bien que rare dans le monde, ce désordre autosomique récessif est particulièrement fréquent dans la population Québécoise du Canada Français du fait d’un effet fondateur. L’unique étude réalisée sur la mutation québécoise du gène qui code pour le co-transporteur de potassiumchlore 3 (KCC3) a montré qu’il y a une perte de fonction de la protéine. Cependant, la maladie est également retrouvée hors du Québec et il reste encore à élucider les pathomécanismes mis en jeu. Nous avons donc séquencé les 26 exons du gène KCC3 chez des individus recrutés dans le monde entier et suspectés d’être atteints de la maladie. Nous avons ainsi identifié trois nouvelles mutations. L’étude fonctionnelle de ces mutations nous a confirmé la perte de fonction systématique des co-transporteurs mutés. Puisque l’inactivation de KCC3 se produit majoritairement via l’élimination de segments peptidiques en C-terminus, nous avons concentré notre attention sur l’identification des interactions qui s’y produisent. À l’aide d’approches double hybride, pull-down et immunomarquage, nous avons déterminé que KCC3 interagit avec la créatine kinase CK-B et que cette interaction est perturbée par les mutations tronquantes. De plus, l’utilisation d’un inhibiteur de créatine kinase inactive KCC3, ce qui démontre qu’il existe bien un lien fonctionnel et pathologique entre KCC3 et ses partenaires C-terminaux. Nous avons aussi identifié des anomalies majeures de localisation membranaire des KCC3 mutés. Que KCC3 soit tronqué ou pleine longueur, sa distribution subcellulaire est affectée dans des cellules en culture, dans les ovocytes de Xenopes et dans des échantillons de cerveau de patients. La perte d’interaction entre KCC3 et CK-B et/ou les défauts de transit intracellulaire de KCC3 sont donc les mécanismes pathologiques majeurs de la NSMH/ACC.

Synthesis and incorporation into cyclic peptides of tolan amino acids and their hydrogenated congeners: construction of an array of A–B-loop mimetics of the Cε3 domain of human IgE

The disruption of the human immunolobulin E–high affinity receptor I (IgE–FcεRI) protein–protein interaction (PPI) is a validated strategy for the development of anti asthma therapeutics. Here, we describe the synthesis of an array of conformationally constrained cyclic peptides based on an epitope of the A–B loop within the Cε3 domain of IgE. The peptides contain various tolan (i.e., 1,2-biarylethyne) amino acids and their fully and partially hydrogenated congeners as conformational constraints. Modest antagonist activity (IC50 660 μM) is displayed by the peptide containing a 2,2′-tolan, which is the one predicted by molecular modeling to best mimic the conformation of the native A–B loop epitope in IgE.

Recurrent genomic alterations in sequential progressive leukoplakia and oral cancer: drivers of oral tumorigenesis?

A significant proportion (up to 62) of oral squamous cell carcinomas (OSCCs) may arise from oral potential malignant lesions (OPMLs), such as leukoplakia. Patient outcomes may thus be improved through detection of lesions at a risk for malignant transformation, by identifying and categorizing genetic changes in sequential, progressive OPMLs. We conducted array comparative genomic hybridization analysis of 25 sequential, progressive OPMLs and same-site OSCCs from five patients. Recurrent DNA copy number gains were identified on 1p in 20/25 cases (80) with minimal, high-level amplification regions on 1p35 and 1p36. Other regions of gains were frequently observed: 11q13.4 (68), 9q34.13 (64), 21q22.3 (60), 6p21 and 6q25 (56) and 10q24, 19q13.2, 22q12, 5q31.2, 7p13, 10q24 and 14q22 (48). DNA losses were observed in 20 of samples and mainly detected on 5q31.2 (35), 16p13.2 (30), 9q33.1 and 9q33.29 (25) and 17q11.2, 3p26.2, 18q21.1, 4q34.1 and 8p23.2 (20). Such copy number alterations (CNAs) were mapped in all grades of dysplasia that progressed, and their corresponding OSCCs, in 70 of patients, indicating that these CNAs may be associated with disease progression. Amplified genes mapping within recurrent CNAs (KHDRBS1, PARP1, RAB1A, HBEGF, PAIP2, BTBD7) were selected for validation, by quantitative real-time PCR, in an independent set of 32 progressive leukoplakia, 32 OSSCs and 21 non-progressive leukoplakia samples. Amplification of BTBD7, KHDRBS1, PARP1 and RAB1A was exclusively detected in progressive leukoplakia and corresponding OSCC. BTBD7, KHDRBS1, PARP1 and RAB1A may be associated with OSCC progression. Proteinprotein interaction networks were created to identify possible pathways associated with OSCC progression.

Ursachen der unterschiedlichen Oligomerisierung von Lichtsammelproteinen

Die verschiedenen Lichtsammelproteine (Lhc-Proteine) höherer Pflanzen unterscheiden sich im Oligomerisierungsverhalten. Im Photosystem II existieren 6 Lhc-Proteine, die entweder die monomeren Lichtsammelkomplexe (LHC) CP24 (Lhcb6), CP26 (Lhcb5) und CP29 (Lhcb4) oder den trimeren LHCII (Lhcb1, Lhcb2 und Lhcb3) bilden. Im Photosystem I sind laut Kristallstruktur vier Lhc-Proteine lokalisiert, die als Heterodimere organisiert vorliegen. Der schwerpunktmäßig untersuchte LHCI-730 setzt sich aus Lhca1 und Lhca4 zusammen, während der LHCI-680 aus Lhca2 und Lhca3 besteht. Das Ziel der Arbeit bestand in der Identifizierung der für das unterschiedliche Oligomerisierungsverhalten verantwortlichen Proteinbereiche und Aminosäuren. Die für diese Arbeit generierten Consensussequenzalignments verschiedener Lhca- und Lhcb-Proteine vieler Arten unterstützen die Folgerungen aus Strukturdaten und anderen Sequenzalignments, dass den LHCs eine gemeinsame Monomerstruktur zu Grunde liegt. Die Helices 1 und 3 weisen weitgehend sehr hohe Sequenzidentitäten auf, während die N- und C-Termini, die zwei Schleifenregionen und die Helix 2 nur schwach konserviert sind. Falls die Bereiche mit hoher Sequenzübereinstimmung für das Zustandekommen ähnlicher monomerer LHC-Strukturen verantwortlich sind, könnten in den schwach konservierten Domänen die Ursachen für das unterschiedliche Oligomerisierungsverhalten lokalisiert sein. Aufgrund dessen wurden die schwach konservierten Domänen des monomerisierenden Lhcb4, des mit dem Lhca1 dimerisierenden Lhca4 und des Trimere bildenden Lhcb1 gegen die entsprechenden Domänen der anderen Proteine ausgetauscht und bezüglich ihres Oligomerisierungsverhaltens untersucht. Im Lhca4 konnten mit der Helix 2 und der stromalen Schleife zwei für eine Heterodimerisierung essentielle Domänen gefunden werden. Im Lhcb1 waren neben dem N-Terminus auch die 2. Helix und die stromale Schleifendomäne unentbehrlich für eine Trimerisierung. Zusätzlich waren Dimerisierung und Trimerisierung bei Austausch der luminalen Schleife beeinträchtigt. Ein geringer Beitrag zur Lhcb1-Trimerisierung konnte auch für den C-Terminus belegt werden. Ein zusätzliches Ziel der Arbeit sollte der Transfer der Oligomerisierungseigenschaften durch umfangreichen Domänentausch von einem auf ein anderes Protein sein. Der Transfer der Fähigkeit zur Dimerbildung durch Substitution gegen essentielle Lhca4-Domänen (50% luminale Schleife, 100% Helix 2 und 100% stromale Schleife) gelang beim Lhcb4, nicht aber beim Lhcb1. Der Transfer der Trimerisierungsfähigkeit auf Lhca4 und Lhcb4 scheiterte. Eine Lhca1-Mutante mit allen für eine Dimerisierung essentiellen Lhca4-Domänen, die durch Interaktion einzelner Moleküle untereinander multimere LHCs bilden sollte, war bereits in ihrer Monomerbildung beeinträchtigt. Eine Übertragung der Oligomerisierungsfähigkeit auf andere Proteine durch massiven Domänentransfer gestaltete sich somit schwierig, da vermutlich im mutierten Protein immer noch ursprüngliche Tertiärstrukturanteile enthalten waren, die nicht mit den transferierten Proteinbestandteilen kompatibel sind. Bei zukünftigen Experimenten zur Klärung der Transferierbarkeit der Oligomerisierungseigenschaft sollten deswegen neben dem unberücksichtigten 1. Teil der luminalen Schleife auch wenig konservierte Aminosäuren in der 1. und 3. Helix Beachtung finden. Ein weiteres Ziel dieser Arbeit war es, die LHCI-730-Dimerisierung im Detail zu untersuchen. Mutationsanalysen bestätigten den von früheren Untersuchungen bekannten Einfluss des Isoleucins 103 und Histidins 99. Letzteres geht möglicherweise durch sein gebundenes Chlorophyll eine Interaktion mit dem Lhca1 ein. Das Phenylalanin 95 stellte sich ebenfalls als ein wichtiger Interaktionspartner heraus und könnte in Wechselwirkung mit einem zwischen Lhca1 und Lhca4 lokalisierten Phosphatidylglycerin treten. Das ebenfalls an der Dimerbildung beteiligte Serin 88 des Lhca4 könnte auf Grund der räumlichen Nähe bei Modellierungen direkt mit dem am C-Terminus des Lhca1 lokalisierten Glycin 190 interagieren. Darüber hinaus wurde ein in der luminalen Lhca4-Schleife lokalisiertes Phenylalanin 84 als Interaktionspartner des Tryptophans 185 im C-Terminus von Lhca1 identifiziert. Der simultane Austausch des Isoleucins 109 und Lysins 110 in der stromalen Schleife des Lhca4, konnte deren Einfluss auf die Dimerisierung belegen. Nachdem bislang an der Dimerbildung beteiligte Aminosäuren am N- und C-Terminus des Lhca1 und Lhca4 identifiziert werden konnten, wurden in dieser Arbeit viele an einer Dimerbildung beteiligten Proteinbereiche und Aminosäuren in der Helix 2 und den Schleifenregionen des Lhca4 identifiziert. Um alle an der Lhca1-Lhca4-Interaktion beteiligten Aminosäuren aufzuklären, müssten durch Mutationsanalysen die in der stromalen Lhca4-Schleife vermuteten Interaktionspartner des für die Dimerisierung wichtigen Tryptophans 4 am N-Terminus von Lhca1 identifiziert, und die in der Helix 3 des Lhca1 vermuteten Interaktionspartner der Helix 2 des Lhca4 ermittelt werden.