A contração muscular esquelética é regulada pelo complexo troponina/tropomiosina de maneira dependente de Ca2+. O complexo troponina consiste de três subunidades: a troponina C (TnC), a troponina I (TnI) e a troponina T (TnT). A troponina C é a subunidade que liga Ca2+, a TnI é a subunidade inibitória e a TnT liga-se fortemente à tropomiosina. A TnI e a TnT são altamente insolúveis a baixas forças iônicas, a não ser que estejam complexadas com a TnC. O complexo troponina pode ser reconstituído \"in vitro\" a partir das subunidades isoladas simplesmente misturando-se as subunidades em razões equimolares em uréia, que depois é removida através de diálise. Na primeira parte deste trabalho um vetor para a co-expressão da TnC, TnI e TnT em E.coli foi construído. Utilizando este vetor nós produzimos um complexo troponina funcional montado no citoplasma de E.coli. A presença da TnT é requerida para regulação dependente de Ca2+ da contração muscular esquelética. O papel da TnT em conferir sensibilidade ao Ca2+ à atividade ATPásica da acto-miosina foi analisado. Mutantes de deleção da TnT foram construídos através de mutação sítio-dirigida e expressos em E.coli. Complexos troponina contendo os mutantes de TnT e/ou mutantes de TnI foram reconstituídos e analisados em ensaios de ligação ao filamento fino e ensaios de atividade ATPásica. Baseado nestes resultados a TnT foi subdividida em três domínios: o domínio ativatório (aminoácidos 157-216), o domínio inibitório (aminoácidos 157-216) e o domínio de ancoragem do dímero TnC/TnI (aminoácidos 216-263). Nós demonstramos que o dímero TnC/TnI está ancorado ao filamento fino através da interação entre a região amino-terminal da TnI e da região carbóxi-terminal da TnT (aminoácidos 216-263). Um modelo para o papel da TnT na regulação da contração muscular dependente de Ca2+ é proposto. / The contraction of skeletal muscle is regulated by troponin and tropomyosin in a Ca2+ dependent manner. The troponin complex consists of three subunits: troponin C (TnC), troponin I (TnI) and troponin T (TnT). Troponin C is the Ca2+ binding subunit, TnI is the inhibitory subunit and TnT binds tightly to tropomyosin. TnI and TnT are highly insoluble proteins at low ionic strengths, unless they are complexed with TnC. The troponin complex can be reconstituted \"in vitro\" from the isolated subunits simply by mixing the subunits at equimolar ratios in urea, which is then removed by dialysis. In the first part of this work a vector for the co-expression of TnC, TnI and TnT in E.coli was constructed. Using this vector we were able to produce a functional troponin complex assembled \"in vivo\" in the E.coli cytoplasm The presence of TnT is required for the Ca2+ dependente regulation of the skeletal muscle contraction. The role of TnT in conferring full Ca2+ sensitivity to the ATPase activity of acto-myosin was analyzed. Deletion mutants of TnT were constructed by site-directed mutagenesis and expressed in E.coli. Troponin complexes containing the TnT deletion mutants and/or TnI deletion mutants, were reconstituted and analyzed in thin filament binding assays and in ATPase activity assays. Based on these studies, TnT was subdivided into three domains: the activation domain (comprised of aminoacids 1-157), the inhibitory domain (comprised of amino acids 157-216) and the TnC/TnI dimer anchoring domain (aminoacids 216-263). We demonstrated that the TnC/TnI is anchored to the thin filament through interaction between the amino-terminal domain of TnI and the region comprised of aminoacids 216-263 of TnT. A model for the role of TnT in the Ca2+ dependent regulation of muscle contraction is proposed.

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Proteínas desempenham uma grande variedade de funções biológicas. O conhecimento da estrutura tridimensional proteica pode ajudar no entendimento da função desempenhada. De acordo com a hipótese de Anfisen, a estrutura terciária nativa de uma proteína pode ser determinada a partir da informação contida na sequência primária, o que permitiria que métodos computacionais poderiam ser usados para predizer estruturas terciárias quando a primária estiver disponível. No entanto, ainda não existe uma ferramenta computacional capaz de predizer a estrutura tridimensional para uma grande variedade de proteínas. Desse modo, o problema de Predição de Estruturas de Proteínas (PEP) permanece como um desafio para a Biologia Molecular. A conformação nativa de uma proteína é frequentemente a configuração termodinamicamente mais estável, ou seja, que possui menor energia livre. Assim, PEP pode ser vista como um problema de otimização, onde a estrutura com menor energia livre deve ser encontrada dentre todas as possíveis. Entretanto, este é um problema NP-completo, no qual métodos tradicionais de otimização, em geral, não apresentam um bom desempenho. Algoritmos Genéticos (AGs), devido às suas características, são interessantes para essa classe de problemas. O principal objetivo desse trabalho é verificar se a adição de informação pode ser útil aos AGs aplicados em PEP, valendo-se dede modelos moleculares simplificados. Cada indivíduo do AG representa uma solução que, neste caso, é uma possível conformação que será avaliada por um campo de força. Dessa forma, o indivíduo é codificado por um conjunto de ângulos de torção de cada aminoácido. Para auxiliar no processo de busca, bases de dados compostas de ângulos determinados por cristalografia e RNM são utilizadas. Com o objetivo de guiar o processo de busca e manter a diversidade nos AGs, duas estratégias são aqui testadas: Imigrantes Aleatórios e Imigrantes por Similaridade. A última delas foi criada baseando-se na similaridade da sequência primária. Além disso, é investigado neste trabalho o uso de um campo de força coarse grained, que utiliza os átomos de carbono- para representar a cadeia proteica, para avaliar os indivíduos do AG. / Proteins exhibit an enormous variety of biology functions. The knowledge of tertiary structures can help the understanding of the proteins function. According to Anfisen, the native tertiary structure of a protein can be determined by its primary structure information, what could allow that computational methods could be used to predict the tertiary structure when the primary structure is available. However, there is still not a computational tool to solve the structure prediction problem for a large range of proteins. In this way, Protein Structure Prediction (PSP) has been a challenge to Molecular Biology. The conformation of native protein is usually the thermodynamically most stable configuration, i.e., the one having the lowest free energy. Hence, PSP can be viewed as a problem of optimization, where the structure with the lowest free energy should be found among all possible structures. However, this is an NP-problem, where traditional optimization methods, in general, do not have good performance. Genetic algorithms (GAs), due to their characteristics, are interesting for this class of problems. In recent years, there is a growing interest in using GAs for the protein structure prediction problem. The main objective of this work is to verify the addition of useful information to GAs employed in PSP. Each individual of the GA represents a solution for the optimization problem which is, in this case, a possible conformation that will be evaluated by a force field function. Thus, an individual is encoded by a set of torsion angles of each amino acid. In order to reduce the search space, a database composed of angles, determined by crystallography and NMR, is used. With the aim to guide the final search process and maintain diversity in GAs, two strategies were employed here: Random Immigrants and Similarity-based Immigrants. The last strategy was based on similarity of primary amino acid sequence. Furthermore, in this work, a coarse-grained force field, which uses -carbon to represent the protein backbone was employed to evaluate the individuals of GA.

Due to the inherent problems with their structural elucidation in the laboratory, the computational prediction of membrane protein structure is an essential step toward understanding the function of these leading targets for drug discovery. In this work, the development of a genetic algorithm technique is described that is able to generate predictive 3D structures of membrane proteins in an ab initio fashion that possess high stability and similarity to the native structure. This is accomplished through optimisation of the distances between TM regions and the end-on rotation of each TM helix. The starting point for the genetic algorithm is from the model of general TM region arrangement predicted using the TMRelate program. From these approximate starting coordinates, the TMBuilder program is used to generate the helical backbone 3D coordinates. The amino acid side chains are constructed using the MaxSprout algorithm. The genetic algorithm is designed to represent a TM protein structure by encoding each alpha carbon atom starting position, the starting atom of the initial residue of each helix, and operates by manipulating these starting positions. To evaluate each predicted structure, the SwissPDBViewer software (incorporating the GROMOS force field software) is employed to calculate the free potential energy. For the first time, a GA has been successfully applied to the problem of predicting membrane protein structure. Comparison between newly predicted structures (tests) and the native structure (control) indicate that the developed GA approach represents an efficient and fast method for refinement of predicted TM protein structures. Further enhancement of the performance of the GA allows the TMGA system to generate predictive structures with comparable energetic stability and reasonable structural similarity to the native structure.

Evolutionary algorithms (EAs) have been shown to be competent at solving complex, multimodal optimisation problems in applications where the search space is large and badly understood. EAs are therefore among the most promising classes of algorithms for solving the Protein Structure Prediction Problem (PSPP). The PSPP is how to derive the 3D-structure of a protein given only its sequence of amino acids. This dissertation defines, evaluates and shows limitations of simplified models for solving the PSPP. These simplified models are off-lattice extensions to the lattice HP model which has been proposed and is claimed to possess some of the properties of real protein folding such as the formation of a hydrophobic core. Lattice models usually model a protein at the amino acid level of detail, use simple energy calculations and are used mainly for search algorithm development. Off-lattice models usually model the protein at the atomic level of detail, use more complex energy calculations and may be used for comparison with real proteins. The idea is to combine the fast energy calculations of lattice models with the increased spatial possibilities of an off-lattice environment allowing for comparison with real protein structures. A hypothesis is presented which claims that a simplified off-lattice model which considers other amino acid properties apart from hydrophobicity will yield simulated structures with lower Root Mean Square Deviation (RMSD) to the native fold than a model only considering hydrophobicity. The hypothesis holds for four of five tested short proteins with a maximum of 46 residues. Best average RMSD for any model tested is above 6Å, i.e. too high for useful structure prediction and excludes significant resemblance between native and simulated structure. Hence, the tested models do not contain the necessary biological information to capture the complex interactions of real protein folding. It is also shown that the EA itself is competent and can produce near-native structures if given a suitable evaluation function. Hence, EAs are useful for eventually solving the PSPP.

A novel approach is proposed for modeling of structurally variable regions in proteins. In this approach, a prerequisite sequence-structure alignment is examined for regions where the target sequence is not covered by the structural template. These regions, extended with a number of residues from adjacent stem regions, are submitted to fold recognition. The alignments produced by fold recognition are integrated into the initial alignment to create a multiple alignment where gaps in the main structural template are covered by local structural templates. This multiple alignment is used to create a protein model by existing protein modeling techniques. Several alternative parameters are evaluated using a set of ten proteins. One set of parameters is selected and evaluated using another set of 31 proteins. The most promising result is for loop regions not located at the C- or N-terminal of a protein, where the method produces an average RMSD 12% lower than the loop modeling provided with the program MODELLER. This improvement is shown to be statistically significant.

An experimental study on randomly generated protein sequences can provide important insights into the origin and mechanism of secondary structure formation and protein folding. In this study we bring biophysical characterization of five protein sequences selected from the in silico generated library of random chains. The sequences were selected on the basis of bioinformatic analysis in order to find the candidates with the maximum potential to possess secondary structure. This study shows that the random polypeptide sequences form stable secondary structures and in some show the signs of tertiary structure, such as hydrophobic core formation and distinctive oligomerization pattern. While the work presented in this thesis is work in progress on a larger study, the data already demonstrate that unevolved protein sequence space provides a lot of potential for secondary and tertiary structure formation that awaits its characterization. Powered by TCPDF (www.tcpdf.org)

Abstract Species are the fundamental units of biological diversity, but their identification and delimitation is often difficult. The difficulties are pronounced in diverse taxa such as insects. DNA barcodes, short standardized segments of the genome, have recently become a popular tool for identifying specimens to species, and are increasingly used as one of the sources of information for species delimitation. In this thesis, I studied the utility of DNA barcodes in species identification and delimitation in beetles (Coleoptera). Beetles are one of the most diverse animal groups, with nearly 400 000 known species. The Nordic beetle fauna is among the most thoroughly studied on the planet, providing excellent conditions for these studies. I also approached barcode sequences from a new angle, exploring amino acid variation and its connections to life history in a sample of the entire animal kingdom. I also studied variation and evolution at the amino acid level in large-scale samples of beetles and moths & butterflies (Lepidoptera). DNA barcodes proved to be a feasible tool for identifying species of Nordic beetles: depending on the criteria for successful identification, 95-98% of specimens could be identified to the species level based on DNA barcodes. Regardless of the delimitation method used, approximately 90% of the currently accepted species were perfectly recovered based on barcode data, and simple rules for forming consensus between delimitations improved the fit between species and barcode clusters even further. Several species that were split into two or more sequence clusters apparently include species new to science that have been previously overlooked. This conclusion is supported by preliminary morphological analysis. The study on amino acid variation revealed both a general pattern of structural conservation throughout the animal kingdom, and some interesting amino acid substitutions with potential to affect enzymatic function. Amino acid variation was more extensive in Coleoptera than in Lepidoptera, potentially due to differences in selection pressure and patterns of molecular evolution in the barcode region between the two orders. / Tiivistelmä Laji on luonnon monimuotoisuuden perusyksikkö, mutta lajien tunnistaminen ja rajaaminen on usein vaikeaa. Vaikeudet korostuvat erityisesti hyvin monimuotoisissa eliöryhmissä kuten hyönteisissä. DNA-viivakoodit ovat lyhyitä standardoituja DNA-sekvenssejä, joiden käyttö lajien tunnistamisessa sekä yhtenä tiedon lähteenä lajien rajaamisessa on viime aikoina yleistynyt nopeasti. Tutkin väitöskirjatyössäni DNA-viivakoodien soveltuvuutta lajinmääritykseen ja lajien rajaamiseen kovakuoriaisilla. Kovakuoriaiset ovat yksi maailman lajirikkaimmista eliöryhmistä: lajeja on kuvattu lähes 400000. Pohjois-Euroopan lajisto tunnetaan koko maailman mittakaavassa poikkeuksellisen hyvin, mikä tarjoaa erinomaiset edellytykset tutkia DNA-viivakoodeihin liittyviä kysymyksiä kuoriaisilla. Tutkin DNA-viivakoodeja myös kokonaan uudesta näkökulmasta, selvittäen aminohappotason muuntelua koko eläinkunnan kattavassa otoksessa, sekä laajalla perhos- ja kuoriaisaineistolla. DNA-viivakoodit osoittautuivat erinomaiseksi työkaluksi lajinmääritykseen: riippuen onnistuneen määrityksen kriteereistä 95–98 % kuoriaislajeista voitiin tunnistaa luotettavasti viivakoodien perusteella. Käytetystä menetelmästä riippumatta noin 90 % nykykäsityksen mukaisista lajeista voitiin rajata viivakoodien perusteella oikein, ja soveltamalla yksinkertaisia konsensus-sääntöjä yhteensopivuus lajien ja viivakoodiklustereiden välillä kasvoi entisestään. Useat kuoriaislajit, jotka jakautuivat kahteen tai useampaan viivakoodiklusteriin, sisältävät alustavien morfologisten tutkimusten perusteella aiemmin huomaamatta jääneitä uusia lajeja. Aminohappo- ja proteiinitason tutkimus osoitti, että viivakoodijakson koodaaman proteiinin rakenne on yleisesti ottaen konservoitunut kautta eläinkunnan. Havaitsin kuitenkin myös useita kiinnostavia aminohappo-muutoksia, jotka saattavat vaikuttaa entsyymitoimintaan. Aminohapposekvenssi muuntelee kuoriaisilla paljon enemmän kuin perhosilla, mahdollisesti johtuen taksonien välisistä eroista molekyylievoluutiossa ja viivakoodisekvenssiin kohdistuvassa valintapaineessa.

The work described in this thesis is an experimental study into the application of Electron Paramagnetic Resonance (EPR) Spectroscopy for the study of biological systems. Using a variety of methods of site-directed spin-labelling (SDSL), this thesis aims to explore long range structure in an assortment of recombinant and native proteins, and complexes thereof. The work described in this thesis covers all aspects of the work, from experimental design, molecular biology and cloning, protein expression and purification, as well as functional characterisation, and finally EPR distance measurements, data analysis and interpretation. Challenges and pitfalls will also be addressed. Chapters 1 and 2 introduce EPR spectroscopy, and its application in the study of long range structure in biological systems. The experimental techniques employed throughout this thesis are also introduced. Chapter 3 details an investigation into the complement C3b:factor H complex. This chapter addresses the challenges associated with the SDSL of cysteine rich proteins. Utilising hidden cysteine residues in native proteins for spin-labelling purposes will also be addressed. Chapter 4 looks at the interactions of the human myosin regulatory light chain (RLC) with cardiac myosin binding protein C (cMyBP-C). Optimisation of expression and purification protocols will be the focus, as well as addressing issues with protein solubility and spin labelling efficiencies. Chapter 5 explores the development of new methods of SDSL, for the specific labelling of cysteine rich proteins. The ability of Escherichia coli to read through the amber stop codon will be exploited for the incorporation of unnatural amino acids for labelling purposes, and novel spin labels, specific for labelling cysteine pairs tested in several model systems. Furthermore, native paramagnetic centres in recombinant proteins will be explored as potential labelling sites.