Yes / The Cdc42- and Rac-interactive binding motif (CRIB) of coronin binds to Rho GTPases with a preference for GDP-loaded Rac. Mutation of the Cdc42- and Rac-interactive binding motif abrogates Rac binding. This results in increased 1evels of activated Rac in coronin-deficient Dictyostelium cells (corA−), which impacts myosin II assembly. corA− cells show increased accumulation of myosin II in the cortex of growth-phase cells. Myosin II assembly is regulated by myosin heavy chain kinase–mediated phosphorylation of its tail. Kinase activity depends on the activation state of the p21-activated kinase a. The myosin II defect of corA− mutant is alleviated by dominant-negative p21-activated kinase a. It is rescued by wild-type coronin, whereas coronin carrying a mutated Cdc42- and Rac-interactive binding motif failed to rescue the myosin defect in corA− mutant cells. Ectopically expressed myosin heavy chain kinases affinity purified from corA− cells show reduced kinase activity. We propose that coronin through its affinity for GDP–Rac regulates the availability of GTP–Rac for activation of downstream effectors. / This work was supported by Deutsche Forschungsgemeinschaft (DFG), Sonderforschungsbereich 670 (SFB 670) and Köln Fortune (to A.A.N.). A.M.-T. acknowledges support by the SFB 914, and J.F. acknowledges support by Grant FA330/6-1 within the framework of the DFG priority programme “Principles and Evolution of Actin Nucleator Complexes” (SPP1464). Work in F.R. lab is supported by grants from the Hull York Medical School.

The world has proven unprepared for deadly viral outbreaks. Designing antiviral drugs and strategies requires a firm understanding of the interactions taken place between the proteins of the virus and human proteins. The current computational models for predicting these interactions consider only single viruses for which extensive prior knowledge is available. The two prediction frameworks in this dissertation, DeNovo and DeNovo-Human, make it possible for the first time to predict the interactions between any viral protein and human proteins. They further helped to answer critical questions about the Zika virus. DeNovo utilizes concepts from virology, bioinformatics, and machine learning to make predictions for novel viruses possible. It pools protein-protein interactions (PPIs) from different viruses sharing the same host. It further introduces taxonomic partitioning to make the reported performance reflect the situation of predicting for a novel virus. DeNovo avoids the expected low accuracy of such a prediction by introducing a negative sampling scheme that is based on sequence similarity. DeNovo achieved accuracy up to 81% and 86% when predicting for a new viral species and a new viral family, respectively. This result is comparable to the best achieved previously in single virus-host and intra-species PPI prediction cases. DeNovo predicts PPIs of a novel virus without requiring known PPIs for it, but with a limitation on the number of human proteins it can make predictions against. The second framework, DeNovo-Human, relaxes this limitation by forcing in-network prediction and random sampling while keeping the pooling technique of DeNovo. The accuracy and AUC are both promising ($>85%$, and $>91%$ respectively). DeNovo-Human facilitates predicting the virus-human PPI network. To demonstrate how the two frameworks can enrich our knowledge about virus behavior, I use them to answer interesting questions about the Zika virus. The research questions examine how the Zika virus enters human cells, fights the innate immune system, and causes microcephaly. The answers obtained are well supported by recently published Zika virus studies. / Ph. D. / When a virus attacks a human body, it disturbs the host cells by interacting with their proteins. Identifying these interactions is key to fighting the virus. In this dissertation, I developed two computational tools to identify the interactions for any virus infecting the human. I further used these tools to answer interesting questions about the Zika virus behavior. The results are in agreement with recently published experimental studies about the virus.

Le paludisme, première endémie parasitaire mondiale ayant engendré près d’un demi-million de morts en 2017 (d’après l’OMS), est due à une infection par un parasite du genre Plasmodium. Cet apicomplexe infecte, au cours de son cycle de vie, un hôte définitif, un moustique femelle du genre Anopheles, et un hôte intermédiaire homéotherme (l’Homme pour au moins 6 espèces). Chez ce dernier, après une phase de développement hépatique, le parasite envahit puis lyse les érythrocytes. L’accroissement exponentiel de la parasitémie engendre les symptômes du paludisme et permet la production de formes sexuées (gamétocytes) qui seront transmises au vecteur arthropode, permettant ainsi la complétion du cycle de vie du parasite.Plasmodium a co-évolué avec ses hôtes et mis en place divers modes de régulation de l’expression de ses gènes. La phosphorylation est l’une des modifications post-traductionnelles majeures et rapides qu’il utilise pour répondre aux changements environnementaux auxquels il est confronté au cours de son cycle de vie. Nombre de ses kinases et phosphatases jouent un rôle essentiel dans l’invasion de cellules hôtes, la croissance et la division cellulaires, ainsi que la motilité de certains stades. En revanche, le rôle des cinq pseudokinases de Plasmodium dans son développement n’a jusqu’ici pas été exploré.Durant ma thèse, j’ai caractérisé l’unique pseudo-Tyrosine Kinase-like (pTKL) de Plasmodium et étudié son rôle au cours du cycle intra-érythrocytaire du parasite.L’annotation de la pTKL de P. falciparum (PfpTKL) m’a permis d’identifier différents domaines et motifs, et notamment un domaine SAM (Sterile Alpha Motif), deux motifs RVxF (connus pour leur capacité d’interaction avec la Protéine Phosphatase de type 1, PP1) et un pseudo-domaine kinase appartenant à la famille des Tyrosine Kinases-like (TKL). Nous avons montré que ce pseudo-domaine kinase est capable de lier l’ATP de manière cation-indépendante, mais est dépourvu d’activité enzymatique. Des études d’interaction in vitro couplées à l’utilisation de modèles hétérologues (Levure, ovocytes de Xénope) m’ont permis d’identifier deux protéines parasitaires partenaires de PfpTKL : le domaine SAM de PfpTKL interagit directement avec la pseudo-protéase PfSERA5 (SErine Repeat Antigen 5), alors que les deux régions de la protéine contenant les motifs RVxF de PfpTKL interagissent avec PfPP1c (phosphatase majeure de Plasmodium). De façon intéressante, le deuxième motif RVxF est directement impliqué dans l’interaction avec PP1c et serait capable de moduler l’activité de cette dernière de manière allostérique.La localisation de la pTKL de P. berghei (PbpTKL) a ensuite été étudiée par immunofluorescence et confirmée par des expériences de fractionnement cellulaire. Nous avons ainsi observé que PbpTKL est exportée dans l’érythrocyte infecté au stade trophozoïte, puis retenue dans le parasite et la vacuole parasitophore au stade schizonte. L’étude de l’interactome de PbpTKL par IP/MS au stade trophozoïte a montré que PbpTKL s’associe à diverses protéines impliquées dans l’organisation du cytosquelette de l’érythrocyte, ainsi que dans l’érythropoïèse et l’homéostasie cellulaire. Ces observations suggèrent que pTKL joue un rôle, direct ou via ses partenaires, à l’interface entre le parasite et sa cellule hôte.Enfin, afin d’approcher la fonction de pTKL chez le parasite, nous avons généré différentes lignées génétiquement modifiées. L’étude phénotypique des souches de P. berghei KO et iKD pour pTKL a montré qu’elle était dispensable pour la complétion du cycle intra-érythrocytaire, l’expression des gamétocytes ainsi que l’activation des gamétocytes mâles. Ces données suggèrent que pTKL est dispensable pour ces stades de développement ou que l’expression de gènes redondants compense son absence. Quoi qu’il en soit, il est important de poursuivre les recherches sur le rôle de cette protéine aux autres stades de développement du parasite, notamment du zygote aux stades hépatiques. / Malaria is the first endemic parasitic disease in the world with nearly half million deaths in 2017 according to the WHO. This disease is the result of an infection by an agent belonging to the Plasmodium genus. This apicomplexan parasite infects two hosts over its complex life cycle: a definitive one – a mosquito belonging to the Anopheles genus – and a homoeothermic intermediate host. At least six Plasmodium species can infect humans. In its intermediate host, Plasmodium first replicates in hepatocytes before releasing erythrocyte-infectious stages in the bloodstream. Once there, parasites invade and replicate within erythrocytes, before lysing them to release other infectious stages. This triggers an exponential rise in the parasitemia, as well as malaria symptoms. Sexual stages, called gametocytes, are produced over this intra-erythrocytic cycle to be transmitted to the arthropod vector, thus allowing the completion of the parasite life cycle.Plasmodium co-evolved with its hosts and set up diverse gene expression regulation pathways accordingly. Phosphorylation is one of the major and fastest post-translational modifications used by the parasite to respond to environmental changes. Many of its kinases and phosphatases play key roles in host cell invasion, cellular growth and division, as well as motility of specific developmental stages. However, the role of the five pseudo-kinases expressed by Plasmodium has not been explored yet.During my PhD project, I have performed the characterization of the unique Plasmodium pseudo-Tyrosine Kinase-like (pTKL) and explored its role over the parasite intra-erythrocytic cycle.P. falciparum pTKL (PfpTKL) in silico annotation allowed the delineation of the protein domains. Notably, a SAM (Sterile Alpha Motif) domain, two RVxF motifs (known for their binding potential with the major protein phosphatase type 1, PP1) and a pseudo-kinase domain belonging to Tyrosine Kinase-like (TKL) family were found. This pseudo-kinase domain was found to be able to bind ATP in a cation-independent way although devoid of kinase activity. Two parasite protein partners of PfpTKL have been identified using in vitro protein-protein interaction studies together with heterologous models (yeast, Xenopus ovocytes). First, PfSERA5 (SErine Repeat Antigen 5) specifically and strongly interacts with PfpTKL SAM domain and second, PfPP1c binds the two RVxF-containing regions of PfpTKL. Interestingly, the second RVxF motif, which is located within the pseudo-kinase domain, directly binds PfPP1c and seems to be involved in the allosteric regulation of the phosphatase activity. The subcellular localization of P. berghei pTKL (PbpTKL) was studied by IFA as well as sequential lysis of erythrocytes followed by immunoprecipitation assays. PbpTKL was shown to be exported to the host cell cytosol at the trophozoite stage, but retained in the parasitophorous vacuole and the parasite cytosol at the schizont stage. Furthermore, our interactome analysis conducted at the trophozoite stage by IP/MS showed that PbpTKL binds many host cell proteins involved in erythrocyte cytoskeleton organization, as well as erythropoiesis and cell homeostasis. These data suggest that pTKL plays a role at the parasite/host interface, either directly or via its protein partners.Finally, in an attempt to understand the role of pTKL for the parasite development, we generated genetically modified P. berghei strains. The phenotypic study of PbpTKL KO and iKD strains did not show any difference between the defective parasites and the parental wild type ones during the intra-erythrocytic cycle, gametocyte expression and male gametocyte activation. These data suggest the dispensability of pTKL or the expression of redundant gene(s) with similar functions in these parasite stages. Whatever the explanation, it is still important to follow up this investigation in other parasite stages, from zygotes to hepatic stages.

BACKGROUND:A hub protein is one that interacts with many functional partners. The annotation of hub proteins, or more generally the protein-protein interaction "degree" of each gene, requires quality genome-wide data. Data obtained using yeast two-hybrid methods contain many false positive interactions between proteins that rarely encounter each other in living cells, and such data have fallen out of favor.RESULTS:We find that protein "stickiness", measured as network degree in ostensibly low quality yeast two-hybrid data, is a more predictive genomic metric than the number of functional protein-protein interactions, as assessed by supposedly higher quality high throughput affinity capture mass spectrometry data. In the yeast Saccharomyces cerevisiae, a protein's high stickiness, but not its high number of functional interactions, predicts low stochastic noise in gene expression, low plasticity of gene expression across different environments, and high probability of forming a homo-oligomer. Our results are robust to a multiple regression analysis correcting for other known predictors including protein abundance, presence of a TATA box and whether a gene is essential. Once the higher stickiness of homo-oligomers is controlled for, we find that homo-oligomers have noisier and more plastic gene expression than other proteins, consistent with a role for homo-oligomerization in mediating robustness.CONCLUSIONS:Our work validates use of the number of yeast two-hybrid interactions as a metric for protein stickiness. Sticky proteins exhibit low stochastic noise in gene expression, and low plasticity in expression across different environments.

Οι πρωτεϊνικές αλληλεπιδράσεις (PPI) αναφέρονται στην σύνδεση δύο ή περισσοτέρων πρωτεϊνών ώστε να εκτελεστεί μια βιολογική λειτουργία. Την τελευταία δεκαετία, νέες τεχνολογίες υψηλής απόδοσης για τον εντοπισμό αυτών των αλληλεπιδράσεων έχουν παράγει μεγάλης κλίμακας σύνολα δεδομένων τόσο του ανθρώπου όσο και των περισσοτέρων ειδών. Με την αναπαράσταση αυτών των δεδομένων σε δίκτυα, με τους κόμβους να αναπαριστούν τις πρωτεΐνες και τις ακμές τις αλληλεπιδράσεις, μπορούν να εξαχθούν χρήσιμες πληροφορίες σχετικά με τον προσδιορισμό της λειτουργίας των πρωτεϊνών/πρόβλεψη ή σχετικά με το πώς να σχεδιαστούν κατάλληλα φάρμακα που προσδιορίζουν τα νέα γονίδια-στόχους για τον καρκίνο ή τους μηχανισμούς που ελέγχουν (ή ρυθμίζουν) τις βιολογικές αλληλεπιδράσεις που είναι υπεύθυνες για την καλή ή την κακή λειτουργία ενός κυττάρου. Στα πλαίσια της παρούσας διπλωματικής, κληθήκαμε να κάνουμε λειτουργική πρόβλεψη των πρωτεϊνών στο δίκτυο πρωτεϊνικών αλληλεπιδράσεων του ανθρώπου εφαρμόζοντας μια μέθοδο δυναμικής επικάλυψης η οποία βασίζεται στον έλεγχο του πώς οι ταλαντωτές οργανώνονται σε ένα «αρθρωτό»(modular) δίκτυο σχηματίζοντας διεπαφές συγχρονισμού και κοινότητες επικάλυψης. Μελετήσαμε το δίκτυο πρωτεϊνικών αλληλεπιδράσεων του ανθρώπου και τις κλάσεις λειτουργιών θεωρώντας ένα σύνολο ταλαντωτών φάσης (phase oscillators) με μία τοπολογία συνδέσεων που ορίζεται από το δίκτυο πρωτεϊνικών αλληλεπιδράσεων του ανθρώπου. Συγκεκριμένα, αρχίσαμε με μία απλή ομαδοποίηση για κάθε πρωτεΐνη και έπειτα χρησιμοποιήσαμε την μέθοδο δυναμικής επικάλυψης για τον προσδιορισμό των λειτουργιών των πρωτεϊνών του PPI δικτύου. Στην συνέχεια, εντοπίσαμε εκείνες τις πρωτεΐνες οι οποίες δεν είχαν ομαδοποιηθεί σωστά καθώς και τις πρωτεϊνες που ήταν πιθανόν να «συμμετείχαν» σε περισσότερες από μία λειτουργικές κλάσεις (πολυλειτουργικές πρωτεΐνες). Με κατάλληλο έλεγχο των αλληλεπιδράσεων μεσαίας κλίμακας του δικτύου των δυναμικών συστημάτων που δημιουργήθηκε παρήχθησαν χρήσιμες πληροφορίες για τις μικρής και μεγάλης κλίμακας διαδικασίες μέσω των οποίων οι βιολογικές διεργασίες οργανώνονται σε ένα κύτταρο γεγονός που αποκαλύπτει ότι η μέθοδος είναι ικανή όχι μόνο να εντοπίσει τις μη σωστά ομαδοποιημένες πρωτεΐνες αλλά και να αποκαλύψει αυτές που έχουν διπλή λειτουργικότητα (2 λειτουργίες). / Protein-protein interactions (PPI) refer to the binding of two or more proteins to perform a biological function. In the last decade, novel high-throughput technologies for detecting those interactions have produced large-scale data sets across human and most model species. By embedding these data in networks, with nodes representing proteins and edges the detected PPIs, useful information can be extracted regarding protein functional annotation/prediction or on how to design proper drugs, identifying new targets on cancer, or mechanisms to control (or regulate) the biological interactions responsible for the functioning,or malfunctioning, of a cell. Under the framework of my master thesis, I had to apply a method of dynamical overlap based on the inspection of how oscillators organize in a modular network by forming synchronization interfaces and overlapping communities to the human PPI network. I studied the human protein interaction network (PIN) and its functional modules by considering an ensemble of phase oscillators with a topology of connections defined by the human PIN. In particular, I started with a single classification for each protein and I used the dynamical overlap method for identifying/predicting of the proteins function(s) in the PPI network. Then, I identified all those proteins that were misclassified and those proteins that were likely to be involved in more than one of the functional categories in our data(multifunctional proteins). A proper inspection on the meso-scale interactions of the generated network of dynamical systems provided useful information on the micro- and macro- scale processes through which biological processes are organized in a cell, that is, the method is not only able to identify the misclassified proteins but also to unveil those proteins that have double functionality.

<p>Eukaryotic Topoisomerase 2 is an essential enzyme that solves DNA topological problems such as DNA knotting, catenation, and supercoiling. It alters the DNA topology by introducing transient double strand break in one DNA duplex as a gate for the passage of another DNA duplex. Two different aspects of studies about eukaryotic Topoisomerase 2 will be covered in this thesis. In the first half of the thesis, we investigated conformational changes of human Topoisomerase 2&#61537; (hsTop2&#61537;) in the presence of cofactors and inhibitors. In the second half, we focused on an unknown regulatory function in the C-terminal domain (CTD) of Drosophila Topoisomerase 2 (Top2).</p><p>In the project of studying enzyme conformational changes, we adapted a previously developed methodology, Pulse-Alkylation Mass Spectrometry, with monobromobimane to study the protein dynamics of hsTop2&#61537;. Using this method, we captured the evidence of conformational changes in the presence of ATP and Mg2+ or the Top2 inhibitor, ICRF-193 which were not previously observed. Last, by using CTD truncated hsTop2&#61537;, the increasing reactivity of Cys427 suggested the CTD domain might be tethered adjacent to the core enzyme.</p><p>Following the study of enzyme conformational changes, we switched gear to examine an interaction between Drosophila Top2 and Mus101, homolog of human TopBP1. We first found that Mus101 interacts with CTD of Top2 in a phosphorylation-dependent manner. Next, in the co-immunoprecipitation and pull-down experiments using truncated or mutant Top2 with various Ser to Ala substitutions, we mapped the binding motif to the last amino acids of Top2 and identified that phosphorylation of Ser1428 and Ser1443 is important for Top2 to interact with the N-terminus of Mus101, which contains BRCT1/2 domains (BRCT, BRCA1 C-terminus). The binding affinity of the N-terminal Mus101 with a synthetic phosphorylated peptide covering the last 25 amino acids of Top2 (with pS1428 and pS1443) was determined by surface plasmon resonance with a Kd of 0.57 &#956;M. In an in vitro decatenation assay, Mus101 can specifically reduce the decatenation activity of Top2, and dephosphorylation of Top2 attenuates this response to Mus101. Next, we endeavored to establish a cellular system for testing the biological function of Top2-Mus101 interaction. Top2-silenced S2 cells rescued by Top2&#61508;20, truncation of 20 amino acids from the C-terminus of Top2, developed abnormally high chromosome numbers, which implies an infidelity in chromosome segregation during mitosis. Lastly, Top2-null flies rescued by Top2 with S1428A and S1443A were found to be viable but sterile. After investigating spermatogenesis, telophase of meiosis I was delayed, indicating Top2-Mus101 interaction is also important in segregating DNA in meiosis.</p> / Dissertation

Protein – Protein interactions (PPIs) are thought to be conserved between species, although this has not been systematically investigated. This problem was explored in Escherichia coli from experimental data in Treponema pallidum by predicting PPIs, focusing on protein domains of little or unknown function. The comparison of T. pallidum to a model organism such as E. coli can not only reveal additional data about T. pallidum but also reveals how E. coli is similar to this distantly related, obligate parasite. A set of novel T. pallidum interactions, enriched for proteins of unknown function, were the basis of over 23,000 predicted homologous E. coli protein-protein and domain-domain interactions. Utilizing computational methods of protein analysis to define identity cross-species comparisons, this work shows that T. pallidum is nearly 61% similar to E. coli by orthologous groups (OG), demonstrating that what we knew of T. pallidum can be applied to E. coli. Observed binary interactions of that same pool of OGs result in only 4.3% shared T. pallidum interactions. Assigning function to proteins of unknown function leads to a greater understanding of how individual proteins relate to the larger interactome, the whole of interactions within a cell.

No description available.

Arf1 est une petite protéine G (pG), essentiellement impliquée dans le trafic vésiculaire. Arf1 oscille entre deux conformations, l'une active liée au GTP et l'autre inactive associée au GDP. Arno est un des facteurs d'échange (GEF) capable d'activer Arf1 en stimulant l'échange GDP/GTP. Suractivée dans les cellules invasives du cancer du sein, Arf1 joue un rôle important dans la migration et la prolifération des cellules cancéreuses.Le but de ma thèse s'inscrit dans l'étude et la modulation de l'interaction pG-GEF, et plus spécifiquement, le couple Arf1-Arno. Mon travail a été planifié autour de deux axes: (1) L'étude fine de l'interaction entre Arf1 et Arno, et sa modulation avec un inhibiteur connu la Bréféldine A (BFA). (2) La mise en place d'une stratégie de conception d'inhibiteurs de l'interaction protéine-protéine du couple Arf1-Arno.Dans un premier temps, nous avons mis en place une méthode basée sur la résonance plasmonique de surface (SPR) permettant la détermination des paramètres cinétiques de l'interaction entre Arf1 et Arno. Nous avons précisé aussi les conséquences des partenaires allostériques (GDP, GTP, et Mg2+) et de la BFA sur les paramètres cinétiques de l'interaction. Ceci a permis une analyse fine de la régulation allostérique et du mode d'action de la BFA. Appliquée à d'autres inhibiteurs, cette méthode permettra d'examiner leur mécanisme d'inhibition.Dans la deuxième partie j'expose, la stratégie que nous avons utilisé pour la conception rationnelle d'inhibiteur de l'interaction entre Arf1 et Arno. Elle est basée sur le criblage virtuel de fragments au niveau des résidus clé « hotspots » de l'interaction, la validation des molécules-touches par des techniques biophysiques, et l'élimination de molécules artefacts. Les structures des complexes fragments-Arno ont été résolues, ce qui confirme la validité de cette stratégie ouvrant la voie vers l'optimisation moléculaire pour obtenir des inhibiteurs plus efficaces. / Arf1 is a small GTPases, essentially involved in the vesicular traffic. Arf1 switch between two conformations, an active form bound to GTP and an inactive form bound to GDP. Arno is one of the exchange factors (GEF) that can activate Arf1, through its catalytic Sec7 domain, promoting the exchange of GDP by GTP. Activated in breast cancer cells, Arf1 plays an important role in the migration and proliferation of cancer cells.The aim of my thesis was the study and the modulation of the interaction between small G proteins and their GEFs, more precisely the Arf1-Arno interaction. My work has been planned around two axes: (1) the study of the interaction between Arf1 and Arno, and its modulation with a known inhibitor Brefeldin A (BFA). (2) The development of a rational strategy for designing inhibitors of protein-protein interaction for the Arf1-Arno complex.In the first part of my PhD work, we set up a Surface Plasmon Resonance (SPR) method allowing to determine the kinetic parameters of the interaction between Arf1 and Arno. We also studied the effects of allosteric partners such as GDP, GTP and Mg2+ as well as the known uncompetitive inhibitor (Brefeldin A). This SPR approach allowed a very informative analysis at qualitative and quantitative levels of the various complexes taking place during the exchange reaction that should help to solve the inhibitory mechanism for the known inhibitors reported in the literature. In the second part of my thesis, we propose a strategy for targeting the interaction between Arf1and Arno. This approach is based on virtual screening of fragments at hotspot regions. Using biophysical techniques such fluorescence techniques, SPR, NMR and X-Ray crystallography, we identified and validated Hits, showing by crystallographic structural data their modes of interaction with the target protein Arno. A fluorescence polarization test was also developed to identify false positive fragments to eliminate promiscuous aggregators. Taken together, our work proposes a method based on SPR allowing the study of known inhibitors of GEFs, understanding at molecular level their mode of action. We also propose a general strategy for finding Hit fragments that designing competitive inhibitor of the interaction small G protein with its GEFs, that can be the scaffold for designing more powerful inhibitors.

Mass spectrometry (MS) is a rapid, specific and very sensitive analytical method with a broad spectrum of proteomic applications such as protein identification and sequencing, 3D protein structure characterization or study of protein-protein interaction. The introduction of two ionization techniques in late 1980's that are able to ionize the large biomolecules such as proteins, oligosaccharides or nucleic acids with no or low fragmentation has started the rapidly expanding field of MS-based proteomics. The presented thesis was aimed at the application of mass spectrometric approaches to answer several proteomic questions. Firstly we have employed the chemical cross-linking in combination with MS analysis to solve the 3D structure and protein-protein interactions of three model systems: (1) homodimeric human regulatory protein 14-3-3, (2) model of 14-3-3 and regulatory domain of tyrosine hydroxylase, and (3) system of two membrane proteins, cytochrome P450 2B4 and cytochrome b5, involved in xenobiotics biotransformation. This approach works in aqueous solutions under physiological conditions and thus preserves native structure of the investigated proteins. The second part of the thesis was focused on MS identification of proteins/peptides in fungal spores of Aspergillus and Pseudallescheria...