Protein folding, metal ions and conformational states: the case of a di-cluster ferredoxin

Dissertation presented to obtain the PhD degree in Biochemistry at the Instituto de Tecnologia Química e Biológica, Universidade Nova de LisboaMetal ions are present in over thirty percent of known proteins. Apart from a well established function in catalysis and electron transfer, metals and metal centres are also important structural elements which may as well play a key role in modulating protein folding and stability. In this respect, cofactors can act not only as local structural stabilizing elements in the native state, contributing to the maintenance of a given specific structural fold, but may also function as potential nucleation points during the protein folding process...Fundação para a Ciência e Tecnologia is acknowledged for financial support, by awarding a PhD Grant SFRH/BD/18653/2004. This work has been funded by the projects POCTI/QUI/37521; POCTI/QUI/45758 and PTDC/QUI/70101 all to Cláudio M. Gomes

Computational Modeling of Protein Kinases: Molecular Basis for Inhibition and Catalysis

Protein kinases catalyze protein phosphorylation reactions, i.e. the transfer of the γ-phosphoryl group of ATP to tyrosine, serine and threonine residues of protein substrates. This phosphorylation plays an important role in regulating various cellular processes. Deregulation of many kinases is directly linked to cancer development and the protein kinase family is one of the most important targets in current cancer therapy regimens. This relevance to disease has stimulated intensive efforts in the biomedical research community to understand their catalytic mechanisms, discern their cellular functions, and discover inhibitors. With the advantage of being able to simultaneously define structural as well as dynamic properties for complex systems, computational studies at the atomic level has been recognized as a powerful complement to experimental studies. In this work, we employed a suite of computational and molecular simulation methods to (1) explore the catalytic mechanism of a particular protein kinase, namely, epidermal growth factor receptor (EGFR); (2) study the interaction between EGFR and one of its inhibitors, namely erlotinib (Tarceva); (3) discern the effects of molecular alterations (somatic mutations) of EGFR to differential downstream signaling response; and (4) model the interactions of a novel class of kinase inhibitors with a common ruthenium based organometallic scaffold with different protein kinases. Our simulations established some important molecular rules in operation in the contexts of inhibitor-binding, substrate-recognition, catalytic landscapes, and signaling in the EGFR tyrosine kinase. Our results also shed insights on the mechanisms of inhibition and phosphorylation commonly employed by many kinases

Intrinsically Disordered Proteins and Chronic Diseases

This book is an embodiment of a series of articles that were published as part of a Special Issue of Biomolecules. It is dedicated to exploring the role of intrinsically disordered proteins (IDPs) in various chronic diseases. The main goal of the articles is to describe recent progress in elucidating the mechanisms by which IDPs cause various human diseases, such as cancer, cardiovascular disease, amyloidosis, neurodegenerative diseases, diabetes, and genetic diseases, to name a few. Contributed by leading investigators in the field, this compendium serves as a valuable resource for researchers, clinicians as well as postdoctoral fellows and graduate student

Protein Structure and Interactions Studied by Electrospray Mass Spectrometry

Since the emergence of electrospray ionization (ESI) mass spectrometry (MS) as a tool for protein structural studies, this area has experienced tremendous growth. ESI-MS is highly sensitive, and it allows the analysis of biological systems ranging in size from a few atoms to large multi-protein complexes. This work aims to solve questions in protein structural biology by using ESI-MS in conjunction with other techniques. We initially apply ESI-MS for studying the monomeric protein cytochrome c (Chapter 2). The physical reasons underlying the irreversible thermal denaturation of this protein remain controversial. By utilizing deconvoluted charge state distributions, oxidative modifications were found to be the major reason underlying the observed behavior. The positions of individual oxidation sites were identified by LC-MS/MS-based tryptic peptide mapping. Chapter 3 and 4 focus on noncovalent protein complexes. ESI allows the transfer of multi-protein complexes into the gas phase, thereby providing a simple approach for monitoring the stoichiometry of these assemblies by MS. It remains somewhat unclear, however, in how far this approach is suitable for measuring binding affinities. We demonstrate that the settings used for rf-only quadrupoles in the ion path are a key factor for ensuring uniform transmission behavior, which is a prerequisite for meaningful Kd measurements. Overall, our data support the viability of the direct ESI-MS approach for determining binding affinities of protein–protein complexes in solution. Having established suitable conditions for the analysis of noncovalent protein complexes, ESI-MS is applied for monitoring the folding and assembly of hemoglobin (Hb). The native structure of this protein comprises four heme-bound subunits. Hb represents an important model system for exploring coupled folding/binding reactions, an area that remains difficult to tackle experimentally. We demonstrate that efficient Hb refolding depends on the heme ligation status. Only under properly optimized conditions is it possible to return denatured Hb to its tetrameric native state with high yield. ESI-MS allows the observation of on-pathway and off-pathway intermediates that become populated during this highly complex self-assembly process. In summary, this work demonstrates that ESI-MS is a highly versatile tool for addressing questions at the interface of chemistry and structural biology

A New Method for Ligand-supported Homology Modelling of Protein Binding Sites: Development and Application to the neurokinin-1 receptor

In this thesis, a novel strategy (MOBILE (Modelling Binding Sites Including Ligand Information Explicitly)) was developed that models protein binding-sites simultaneously considering information about the binding mode of bioactive ligands during the homology modelling process. As a result, protein binding-site models of higher accuracy and relevance can be generated. Starting with the (crystal) structure of one or more template proteins, in the first step several preliminary homology models of the target protein are generated using the homology modelling program MODELLER. Ligands are then placed into these preliminary models using different strategies depending on the amount of experimental information about the binding mode of the ligands. (1.) If a ligand is known to bind to the target protein and the crystal structure of the protein-ligand complex with the related template protein is available, it can be assumed that the ligand binding modes are similar in the target and template protein. Accordingly, ligands are then transferred among these structures keeping their orientation as a restraint for the subsequent modelling process. (2.) If no complex crystal structure with the template is available, the ligand(s) can be placed into the template protein structure by docking, and the resulting orientation can then be used to restrain the following protein modelling process. Alternatively, (3.) in cases where knowledge about the binding mode cannot be inferred by the template protein, ligand docking is performed into an ensemble of homology models. The ligands are placed into a crude binding-site representation via docking into averaged property fields derived from knowledge-based potentials. Once the ligands are placed, a new set of homology models is generated. However, in this step, ligand information is considered as additional restraint in terms of the knowledge-based DrugScore protein-ligand atom pair potentials. Consulting a large ensemble of produced models exhibiting di erent side-chain rotamers for the binding-site residues, a composite picture is assembled considering the individually best scored rotamers with respect to the ligand. After a local force-field optimisation, the obtained binding-site models can be used for structure-based drug design

Self-Assembly of Synthetic and Biological Polymeric Systems of Technological Interest

In the present work, we investigated the micellization, gelation and the structure of aggregates of three poly(ethylene oxide)-poly(styrene oxide)-poly(ethylene oxide) block copolymers (EO12SO10, EO10SO10E10 and EO137SO18EO137, where E represents the oxyethylene unit, S the oxystyrene unit, and the subscripts correspond to the number of monomeric unit constituting the polymeric chain) in solution. We also investigated the adsorption process and the surface properties of these block copolymers at the air-water (a/w) and chloroform-water (c/w) interfaces. Since these copolymers possess a more hydrophobic middle block –the styrene oxide unit, they should gives rise to more efficient drug delivery systems, in which geometry might play a key role for drug solubilisation and cell uptake. For these reasons, a detailed characterization of the physicochemical properties of these copolymers is required

Elucidating the early events of protein aggregation using biophysical techniques

Proteins and peptides can convert from their native form into insoluble highly ordered fibrillar aggregates, known as amyloid fibrils. The process of fibrillogenesis is implicated in the pathogenic mechanisms of many diseases and, although mature fibrils are well characterised by a plethora of biophysical techniques, the initiation and early steps remain, to date, ambiguous. Mass spectrometry can provide invaluable insights into these early events as it can identify the low populated and transient oligomeric species present in the lag phase by their mass to charge ratio. Recent evidence has shown that oligomers formed early in the aggregation process are cytotoxic and may additionally be central to the progression of diseases associated with amyloid fibril presence. The hybrid technique of ion mobility mass spectrometry can be employed to provide conformational details of monomeric and multimeric species present and elucidate the presence of oligomers which possess coincident mass to charge ratios. Molecular modelling, in conjunction with experimental results, can suggest probable monomeric and oligomeric structural arrangements. In this thesis three aggregating systems are investigated: amyloidogenic transthyretin fragment (105-115), insulin and two Aβ peptides. Initially amyloidogenic endecapeptide transthyretin (105-115) is studied as it has been widely utilised as a model system for investigating amyloid formation due to its small size. Secondly insulin, a key hormone in metabolic processes, is investigated as extensive research has been carried out into its aggregation into amyloid fibrils. The formation of insulin amyloid fibrils rarely occurs in vivo; however localised amyloidosis at the site of injection and the aggregation of pharmaceutical insulin stocks present problems. Thirdly the aggregation of A β peptides Aβ (1-40) and Aβ (1-42) and their interactions with an aggregation inhibitor, RI-OR2, are characterised. A (1-42), although less commonly produced in vivo, is more cytotoxic and has a faster aggregation mechanism than Aβ (1-40). Both Aβ peptides are implicated in the aetiology of Alzheimer’s disease whilst RI-OR2 has been reported to prevent the production of high molecular weight oligomers, with particular suppression of Aβ (1-42) aggregation

Integrating protein structural information

Dissertação apresentada para obtenção de Grau de Doutor em Bioquímica,Bioquímica Estrutural, pela Universidade Nova de Lisboa, Faculdade de Ciências e TecnologiaThe central theme of this work is the application of constraint programming and other artificial intelligence techniques to protein structure problems, with the goal of better combining experimental data with structure prediction methods. Part one of the dissertation introduces the main subjects of protein structure and constraint programming, summarises the state of the art in the modelling of protein structures and complexes, sets the context for the techniques described later on, and outlines the main points of the thesis: the integration of experimental data in modelling. The first chapter, Protein Structure, introduces the reader to the basic notions of amino acid structure, protein chains, and protein folding and interaction. These are important concepts to understand the work described in parts two and three. Chapter two, Protein Modelling, gives a brief overview of experimental and theoretical techniques to model protein structures. The information in this chapter provides the context of the investigations described in parts two and three, but is not essential to understanding the methods developed. Chapter three, Constraint Programming, outlines the main concepts of this programming technique. Understanding variable modelling, the notions of consistency and propagation, and search methods should greatly help the reader interested in the details of the algorithms, as described in part two of this book. The fourth chapter, Integrating Structural Information, is a summary of the thesis proposed here. This chapter is an overview of the objectives of this work, and gives an idea of how the algorithms developed here could help in modelling protein structures. The main goal is to provide a flexible and continuously evolving framework for the integration of structural information from a diversity of experimental techniques and theoretical predictions. Part two describes the algorithms developed, which make up the main original contribution of this work. This part is aimed especially at developers interested in the details of the algorithms, in replicating the results, in improving the method or in integrating them in other applications. Biochemical aspects are dealt with briefly and as necessary, and the emphasis is on the algorithms and the code

Proteomics studies of protein homeostasis and aggregation in ageing and neurodegeneration

Upon ageing, a progressive disruption of protein homeostasis often leads to extensive protein aggregation and neurodegeneration. It is therefore important to study at the proteome level the origins and consequences of such disruption, which so far have remained elusive. Addressing this problem has recently become possible by major advances in mass spectrometry-based (MS) proteomics, which allows the identifications and quantification of thousands of proteins in a variety of biological samples. In the first part of this thesis, I analyse proteome-wide MS data for the nematode worm C. elegans upon ageing, in wild type (WT), long-lived and short-lived mutant strains. By comparing the total abundance and the soluble abundance for nearly 4000 proteins, I provide extensive evidence that proteins are expressed in adult worms at levels close to their solubility limits. With the use of sequence-based prediction tools, I then identify specific physico-chemical properties associated with this age-related protein homeostasis impairment. The results that I obtained reveal that the total intracellular protein content remains constant, in spite of the fact that the proteome undergoes wide remodeling upon ageing, resulting into severe protein homeostasis disruption and widespread protein aggregation. These results suggest a protein-dependent decrease in solubility associated with the protein homeostasis failure. In the second part of the thesis, I determine and classify potential interactions of misfolded protein oligomers with other proteins. This phenomenon is widely believed to give rise to cytotoxicity, although the mechanisms by which this happens are not fully understood. To address this question, I process and analyse MS data from structurally different oligomers (toxic type A and nontoxic type B) of the protein HypF-N, incubated in vitro with proteins extracted from murine cell cultures. I find that more than 2500 proteins are pulled down with the misfolded oligomers. These results indicate that the two types of oligomers interact with the same pool of proteins and differ only in the degree of binding. Functional annotation analysis on the groups reveals a preference of the oligomers to bind proteins in specific biological pathways and categories, including in particular mitochondrial membrane proteins, RNA-binding proteins and molecular chaperones. Overall, in this study I complement the powerful and high-throughput experimental approach of MS proteomics with bioinformatics analyses and prediction algorithms to define the physical, chemical and biological features of protein homeostasis disruption upon ageing and the interactome of misfolded oligomers

Bioinformatic analysis of bacterial and eukaryotic amino- terminal signal peptides

Ph.DDOCTOR OF PHILOSOPH