This thesis investigates the correlations between short protein peptide sequences and local tertiary structures. In particular, it introduces a novel algorithm for partitioning short protein segments into clusters of local sequence-structure motifs, and demonstrates that these motif clusters contain useful structural information via two applications to structural prediction. The first application utilizes motif clusters to predict local protein tertiary structures. A novel dynamic programming algorithm that performs comparably with some of the best existing algorithms is described. The second application exploits the capability of motif clusters in recognizing regular secondary structures to improve the performance of secondary structure prediction based on Support Vector Machines. Empirical results show significant improvement in overall prediction accuracy with no performance degradation in any specific aspect being measured. The encouraging results obtained illustrate the great potential of using local sequence-structure motifs to tackle protein structure predictions and possibly other important problems in computational biology.

Les ARN non codants (ARNnc) sont des transcrits d'ARN qui ne sont pas traduits en protéines et qui pourtant ont des fonctions clés et variées dans la cellule telles que la régulation des gènes, la transcription et la traduction. Parmi les nombreuses catégories d'ARNnc qui ont été découvertes, on trouve des ARN bien connus tels que les ARN ribosomiques (ARNr), les ARN de transfert (ARNt), les snoARN et les microARN (miARN). Les fonctions des ARNnc sont étroitement liées à leurs structures d’où l’importance de développer des outils de prédiction de structure et des méthodes de recherche de nouveaux ARNnc. Les progrès technologiques ont mis à la disposition des chercheurs des informations abondantes sur les séquences d'ARN. Ces informations sont accessibles dans des bases de données telles que Rfam, qui fournit des alignements et des informations structurelles sur de nombreuses familles d'ARNnc. Dans ce travail, nous avons récupéré toutes les séquences des structures secondaires annotées dans Rfam, telles que les boucles en épingle à cheveux, les boucles internes, les renflements « bulge », etc. dans toutes les familles d'ARNnc. Une base de données locale, RNAstem, a été créée pour faciliter la manipulation et la compilation des données sur les motifs de structure secondaire. Nous avons analysé toutes les boucles terminales et internes ainsi que les « bulges » et nous avons calculé un score d’abondance qui nous a permis d’étudier la fréquence de ces motifs. Tout en minimisant le biais de la surreprésentation de certaines classes d’ARN telles que l’ARN ribosomal, l’analyse des scores a permis de caractériser les motifs rares pour chacune des catégories d’ARN en plus de confirmer des motifs communs comme les boucles de type GNRA ou UNCG. Nous avons identifié des motifs abondants qui n’ont pas été étudiés auparavant tels que la « tetraloop » UUUU. En analysant le contenu de ces motifs en nucléotides, nous avons remarqué que ces régions simples brins contiennent beaucoup plus de nucléotides A et U. Enfin, nous avons exploré la possibilité d’utiliser ces scores pour la conception d’un filtre qui permettrait d’accélérer la recherche de nouveaux ARN non-codants. Nous avons développé un système de scores, RNAscore, qui permet d’évaluer un ARN en se basant sur son contenu en motifs et nous avons testé son applicabilité avec différents types de contrôles. / Noncoding RNAs (ncRNAs) are RNA transcripts that are not translated into proteins yet they play important functional roles in the cell including gene regulation, transcription and translation. Among the many categories of ncRNAs that were discovered, we find the well-known ribosomal RNA (rRNA), transfer RNA (tRNA), snoRNA and microRNAs (miRNA). The functions of ncRNAs are tightly linked to their structural features. Thus, understanding and predicting RNA structure as well as developing methods to search for new ncRNAs help to gain insight into these molecules. Technological advances have made available abundant sequence information accessible in databases such as Rfam, which provides alignments and structural information of many ncRNA families. In this research project, we retrieved the information from the Rfam database about the sequences of all secondary structures such as hairpin loops, internal loops, bulges, etc. in all RNA families. A local database, RNAstem, was created to facilitate the use and manipulation of information about secondary structure motifs. We analyzed hairpin loops, bulges and internal loops using the compiled data about the frequencies of occurrence of each loop or bulge and calculated a frequency score. The frequency score is aimed to be an indicator for the abundance of a specific secondary structure motif. While minimizing the bias caused by the high redundancy of some RNA classes as ribosomal RNAs, the frequency score allowed us to identify the rare motifs in each category as well as the common ones. Our findings about the abundant motifs confirm what is already known from previous studies (ex. abundant GNRA or UNCG tetraloops). We found very large gaps between the most abundant and rare RNA structural features. Moreover, we discovered that "A" and "U" dominate single stranded RNA regions, whether they are bulges or loops. We further explored the possibility of using this data to improve current prediction tools for ncRNAs by applying a filter to new candidates. We developed a score system, RNAscore, that evaluates RNAs depending on their motif contents and we tested the program with many different controls.

No description available.

Diese Arbeit beschäftigt sich mit dem Thema Evolutionäre Algorithmen und deren Verwendung für Optimierungsaufgaben. Im ersten Teil der Arbeit werden die theoretischen Grundlagen ausführlich dargelegt, die zum Verständnis der Problemstellung und der vorgeschlagenen Lösungsmöglichkeiten notwendig sind. Dazu gehören die Einführung des Konzeptes von Fitneßlandschaften, deren Eigenschaften sowie die kurze Darstellung bekannter stochastischer Optimierungsverfahren wie z.B. Simulated Annealing. Im Anschluß daran wird auf neue Verfahren - insbesondere gemischte Strategien - eingegangen und diese vergleichend gegenüber den herkömmlichen Verfahren abgegrenzt. Die neu entwickelten Verfahren werden an Modellproblemen getestet, welche im zweiten Teil der Arbeit vorgestellt werden. Verwendet wurden sowohl einfache theoretische Modelle wie Frustrierte Periodische Sequenzen als auch praktisch relevante Probleme wie das der RNA Sekundärstrukturen. Die verschiedenen Modellprobleme werden bezüglich ihrer Eigenschaften und Schwierigkeitsgrade untersucht und miteinander verglichen, um die Effizienz der verwendeten Optimierungsverfahren abschätzen zu können. Der dritte Teil der Arbeit präsentiert wichtige Ergebnisse der im Rahmen dieser Arbeit durchgeführten umfangreichen numerischen Simulationen. Es wird demonstriert, wie sensitiv die Optimierungsergebnisse von den verwendeten Parametern der Algorithmen (wie z.B. Ensemblegröße, Temperatur oder Mutationsrate) abhängen und das ein relativ scharf umrissenes evolutionäres Fenster der Parameter existiert, innerhalb dessen die Optimierungsresultate deutlich besser sind. Eine im Rahmen dieser Arbeit entwickelte adaptive Parametersteuerung wird an den im zweiten Teil vorgestellten Modellproblemen getestet und gezeigt, daß es möglich ist, den Optimierungsprozeß automatisch innerhalb des evolutionären Fensters zu halten. Der letzte Teil gibt Einblick in die im Rahmen dieser Arbeit verwendete Computer-Software und das vom Autor entwickelte Programmpaket. Es wird hervorgehoben, daß die in C++ objektorientiert und modular geschriebene Software leicht an andere Optimierungsaufgaben angepaßt werden kann und dank graphischer Benutzeroberfläche auch einfach zu bedienen ist. / This work explores Evolutionary Algorithms and their application to optimization tasks. The work's first part gives detailed theoretical background information necessary to understand the problem and proposed solutions. This theoretical part includes the introduction of fitness landscapes, the investigation of their properties, and it briefly reiterates well known stochastic optimization strategies like Simulated Annealing. Finally, new strategies, in particular mixed stategies, are introduced and compared to traditional optimization techniques. In the second part of this work, the newly developed strategies are benchmarked using model problems such as 'Frustrated Periodic Sequences', or the analysis of RNA secondary structures. To evaluate the efficiency of different optimization strategies, the introduced model problems are compared with respect to their difficulty level. The third part of this work presents results of extensive numerical simulations demonstrating how sensitive the investigated algorithms depend on their respective control parameters (ensemble size, temperature, mutation rate). It is shown that there is always a distinct parameter window, the so-called evolutionary window, that clearly leads to improved optimization results. Going back to the model problems introduced in part two, a newly developed adaptive parameter control is presented that automatically keeps the optimization algorithm's parameters within the evolutionary window. In the final part of this work not only the software used, but also the software newly developed by this work's author is illuminated. It is emphasized that the new software was designed highly flexible to allow for easy adaptation to different optimization problems. A graphical user interface is provided for convenience.

Uma nova lectina extraída da semente de Artocarpus integrifólia, denominada KM+ foi recentemente descrita. KM+ e haptotática para neutrófilos, promove a aglutinação de hemácias dos grupos A, B, 0, estimula a proliferação de linfócitos do baço de camundongos e liga-se em &#945 D-manose, &#945 metil manosidio e &#945 D-glicose. Esta lectina é composta por quatro monômeros, com peso molecular de 13.150 daltons cada, unidos por interações não covalentes. KM+ contem 1,8% de carboidratos e apresentou quatro isoformas com pontos isoelétricos entre 4,2 e 5,2. Este trabalho teve como objetivos estudar modificações estruturais de KM+ em função de parâmetros como temperatura, força iônica, pH, agentes desnaturantes, ligação com D-manose, monitoradas por dicroísmo circular (CD) e fluorescência. CD também foi utilizado para estimar o conteúdo de estrutura secundaria de KM+, utilizando-se dois programas descritos na literatura: SSE (Secondary Structure Estimation), que utiliza o método dos mínimos quadrados para a estimativa da estrutura secundaria e obtenção dos espectros básicos, baseados nos dados cristalográficos de proteínas de .estrutura resolvida; CCA (Convex Constraint Analisys) que utiliza o algoritmo simplex e a partir dos espectros de CD das proteínas de referencia calcula os espectros das componentes básicas. Para a estimativa das frações de estrutura secundária o segundo método utiliza o programa Lincomb. Os espectros de CD foram registrados no intervalo de 185 a 260 nm. O conteúdo em estrutura secundária, estimado pelo programa SSE foi: 0% de &#945-hélice, 41% de folha &#946, 27% de volta &#946 e 32,3 de estrutura desordenada; pelo programa CCA foi: 1% de &#945-hélice, 35% de folha &#946 anti-paralela, 21% de volta &#946 e/ou folha &#946 paralela, 15% de contribuições de aromáticos e/ou ligações dissulfeto, 28% de estrutura desordenada. Os desvios médios quadráticos para os programas SSE e CCA foram 12% e 1%, respectivamente. Portanto a lectina KM+ é principalmente constituída por estruturas tipo folha &#946 e tipo desordenada. A curva calculada pelo programa CCA foi mais bem estimada, pois tem o desvio médio quadrático 12 vezes menor que o do programa SSE. Este resultado, provavelmente ocorre devido aos seguintes fatores: (i) no programa CCA, o espectro da proteína a ser analisada e alinhado com os espectros das proteínas de referência, influenciando no calculo dos espectros básicos; (ii) maior número de proteínas com estrutura &#946 no grupo de referência do programa CCA. A estabilidade de KM+ em função da temperatura tem comportamento diferente em tampão sódio fosfato (PBS) daquele observado em água. Em PBS, quando a amostra esta a 70&#176C, a forma do espectro de CD mostrou-se consistente com um espectro de proteína desnaturada. Comumente, um espectro de proteína desnaturada caracteriza-se pela perda da estrutura secundaria predominante e aumento da estrutura desordenada. Em água, também a 70&#176C, na região da estrutura &#946 (216 nm) surge uma nova banda e na região da estrutura desordenada (195 nm) aparece uma banda com valores positivos mimetizando um espectro da estrutura &#945-hélice. Esta diferença de comportamento pode ser devida à força iônica. A desorganização promovida na molécula de KM+ por cloreto de guanidina foi típica de desnaturação. o máximo da emissão de fluorescência, da KM+ em PBS pH 7,2, foi a 328 nm, característico de resíduos de triptofano protegidos do solvente. Este máximo mudou para 340 nm em pH 10,5. Este resultado indica mudanças no ambiente químico do triptofano neste pH. O deslocamento para a região do vermelho indica, que em pH. os resíduos de triptofano estio em maior contato com o solvente. O número de sitios ligantes de D-manose J)a molécula de KM+, foi estimado pela supressão da fluorescência promovida pelo D-manose. Esta estimativa foi baseada na suposição de que todos os sítios ligantes de D-manose estivessem próximos aos resíduos de triptofano. A relação encontrada foi de 2 moles de D-manose/mol de KM+ / Recently a new lectin, KM+, isolated from Artocarpus integrifolia seeds was described. KM+ induces neutrophil migration, agglutination of human red blood cells, proliferation of mouse spleen cells and binding with monosacharides D-mannose, D-glicose and &#945-metil mannoside. This glycoprotein is composed of four monomers, assembled by non covalent bonds, has 500 aminoacids residues/mol, with a Molecular Weight of 52,000 Daltons and 1.8% of carbohydrates [27]. In this work structural changes of KM+ was studied as a function of temperature, pH, chemical denaturing agents as well as the binding with D-mannose. These changes were monitored by circular dichroism (CD) and fluorimetry. Circular Dichroism (CD) spectroscopy was used for the analysis of the secondary structure of KM+ in solution due do its capacity to indicate the presence and to estimate the proportion of &#945-helix, &#946-sheet, &#946-turn and unordered conformations. This measurent can be regarded as a function of the relative orientation of the chromophores responsible for their chiroptical activity. CD spectroscopy is also one of the methods of choice for monitorization of conformational changes in proteins as a function of solvents, pH, temperature, ionic strength and specific or non specific binding. Two programs which are in use for estimation of secondary structure: SSE, using the linear least squares method and CCA, using the simplex method, were evaluated in the present work. SSE uses a set of proteins with known X-ray data as the basis for evaluation while CCA uses only pure proteins experimental CD spectra. Fluorescence spectroscopy is very useful to monitore of protein conformational changes in solution due to the presence of intrinsic fluorophores. Fluorescence Measurements were performed at 25&#176C. Samples were excited at 280 nm and the emission was monitored in the range 290-450 nm. The maximum emission as a function of pH was at pH 7.0. The wavelength for maximum emission changed from 328 nm at pH 7.0 to 340 nm at pH 10.5. CD spectra were recorded over the range of 185 up to 260 nm. The Secondary structure content estimated by SSE program was: 0% &#945-helix, 41% &#946-sheet, 26% &#946-turn and 32% random with RMS of 12% and CCA program was: 1% &#945-helix, 35% antiparallel &#946-sheet, 21% &#946-turn and/or parallel B-sheet, 28% random, 15% aromatics contributions and dissulfide linkages with RMS of 1%. The fractions of secondary structure obtained when using CCA program were more consistent than those of SSE program. The simulation by CCA program was better probably due to its desconvolution of the spectral contribution of the common secondary structures using experimental CD curves of proteins. The stability of KM+, in PBS, as a function of temperature changes above 55&#176C but only at 70&#176C the shape of the CD spectrum is consistent with the loss of the native ordered secondary structure that should accompany protein unfolding. CD spectra of KM+ in water showed conformational changes as a function of temperature was not consistent with denaturated proteins. The unfolding of KM+ by GdnCl and SDS resulted in CD spectroscopic changes: consistent with the increased random structure and disappearance of beta sheet. Using the two denaturing agents together GdnCl and temperature, the denaturation was observed at lower decreased both GdnCl concentration and at lower temperature. The estimation of the number of binding sites for D-mannose was obtained through the fluorescence intensity decrease due to a quenching effect of D-mannose and showed that the stoichiometry of binding was 2 moles of D-mannoseimol of lectin

Submitted by Rosangela Silva (rosangela.silva3@unioeste.br) on 2017-08-30T18:51:47Z No. of bitstreams: 2 Carla Lieko Della Torre.pdf: 1852525 bytes, checksum: db416b0a6fe4435a764893198350dbcc (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2017-08-30T18:51:47Z (GMT). No. of bitstreams: 2 Carla Lieko Della Torre.pdf: 1852525 bytes, checksum: db416b0a6fe4435a764893198350dbcc (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2017-02-07 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Enzymes of the xylanolytic complex, from microorganisms, have been an increasingly important biotechnological tool mainly in industrial processes that require high temperatures, such as in the baking industry, animal feed, textile, pulp and cellulose. Among the fungi producing thermostable enzymes, Thermomyces lanuginosus has been evidenced as a good producer of xylanases. In this context, xylanase from the recently isolated thermophilic fungus of the Paraná Atlantic Forest, T. lanuginosus, was purified, biochemically characterized, as well as a structureactivity correlation study of the enzyme was investigated through circular dichroism and fluorescence spectroscopy. Extracellular xylanase was purified after four steps of ion exchange chromatographic columns and molecular filtration. The purity and molecular mass (21.3 kDa) of the enzyme were determined by SDS-PAGE and MALDI-TOF/MS. The xylanase is highly specific to the beechwood xylan substrate and generated mainly xylobiose (X2) and xylotriose (X3), products characteristic of the action of endoxylanase. The enzyme was able to cleave the xylooligosaccharides xylotetraose and xylopentaose, except xylobiose and xylotriose. It exhibit higher activity at pH 6.5 and temperature of 75°C, with stability between pH 5.0-8.0 for 100 hours and thermostability between 40 and 75°C for 5 hours. The deconvolution of the circular dichroism spectrum (CD) enzyme revealed a secondary conformation rich in β-structures with transition midpoint temperature (Tm) of 73.0  0.2°C. In this structural study, xylanase reveals that to perform high enzymatic activity, it was necessary a conformational change. Its secondary structure is conserved even at pH extremes at temperatures up to 70°C and in the presence of MnCl2 (1 mM), DTT (5 mM) and high concentration of guanidine (6 M). Intrinsic fluorescence reveals that the tertiary structure is influenced by pH, guanidine (1 M) associated with temperature and in the presence of MnCl2 and DTT, whereas extrinsic fluorescence, using the ANS probe, shows changes in pH extremes and in the presence of MnCl2 and DTT. Fluorescence results suggest that both the increased enzymatic activity in the presence of cofactors and the loss of activity at extreme pH values are related to changes in the tertiary structure of the enzyme. Thus, T. lanuginosus xylanase has interesting biochemical characteristics for application in several industrial sectors that mainly use high temperature conditions. / As enzimas do complexo xilanolítico, provenientes de microrganismos, têm se tornado uma ferramenta biotecnológica cada vez mais importante, principalmente em processos industriais que requerem temperaturas elevadas, como na indústria de panificação, de rações animais, têxtil, polpa e celulose. Dentre os fungos produtores de enzimas termoestáveis, Thermomyces lanuginosus tem se destacado como bom produtor de xilanases. Nesse contexto, a xilanase do fungo termofílico recentemente isolado da Mata Atlântica do Paraná, T. lanuginosus, foi purificada, caracterizada bioquimicamente, bem como um estudo de correlação estruturaatividade da enzima foi investigado através das espectroscopias de dicroísmo circular e fluorescência. A xilanase extracelular foi purificada após quatro etapas cromatográficas envolvendo colunas de troca iônica e filtração molecular. A pureza e massa molecular (21,3 kDa) da enzima foram determinadas por SDS-PAGE e MALDI-TOF/MS. A xilanase é altamente específica para o substrato xilano de beechwood e gerou principalmente xilobiose (X2) e xilotriose (X3), produtos característicos da ação de endoxilanase. A enzima foi capaz de clivar os xilooligossacarídeos xitotetraose e xilopentaose, exceto a xilobiose e xilotriose. Exibe maior atividade em pH 6,5 e temperatura de 75°C, com estabilidade entre os pH 5,0-8,0 durante 100 horas e termoestabilidade entre 40 e 75°C durante 5 horas. A deconvolução do espectro de dicroísmo circular (CD) da enzima revela uma conformação secundária rica em estruturas-β, com temperatura do ponto médio da transição (Tm) de 73,0  0,2°C. Neste estudo estrutural, a xilanase revelou que, para desempenhar elevada atividade enzimática, foi necessário ocorrer mudança conformacional. Sua estrutura secundária é conservada mesmo em extremos de pH, em temperaturas até 70°C e na presença de MnCl2 (1 mM), DTT (5 mM) e elevada concentração de guanidina (6 M). A fluorescência intrínseca revela que a estrutura terciária sofre influência do pH, guanidina (1 M) associado à temperatura e na presença de MnCl2 e DTT, enquanto a fluorescência extrínseca, utilizando a sonda ANS, revela mudanças em extremos de pH e na presença de MnCl2 e DTT. Os resultados da fluorescência sugerem que tanto o aumento da atividade enzimática na presença dos cofatores quanto a perda da atividade em valores extremos de pH relacionam-se às alterações da estrutura terciária da enzima. Dessa forma, a xilanase de T. lanuginosus possui características bioquímicas interessantes para aplicação em diversos setores industriais que utilizam principalmente condições de temperatura elevada.

<p>Research in the last few decades has revealed the great capacity of the RNA molecule. RNA, which previously was assumed to play a main role only as an intermediate in the translation of genes to proteins, is today known to play many important roles in the cell in addition to that as a messenger RNA and transfer RNA, including the ability to catalyze reactions and gene regulations at various levels.</p><p>This thesis investigates several computational aspects of RNA. We will discuss identification of novel RNAs and RNAs that are known to exist in related species, RNA secondary structure prediction, as well as more general tools for analyzing, visualizing and classifying RNA sequences.</p><p>We present two benchmark studies concerning RNA identification, both de novo identification/characterization of single RNA sequences and homology search methods.</p><p>We develope a novel algorithm for analysis of the RNA folding landscape that is based on the nearest neighbor energy model adopted in many secondary structure prediction programs. We implement this algorithm, which computes structural neighbors of a given RNA secondary structure, in the program RNAbor, which is accessible on a web server.</p><p>Furthermore, we combine a mutual information based structure prediction algorithm with a sequence logo visualization to create a novel visualization tool for analyzing an RNA alignment and identifying covarying sites.</p><p>Finally, we present extensions to sequence logos for the purpose of tRNA identity analysis. We introduce function logos, which display features that distinguish functional subclasses within a large set of structurally related sequences, as well as the inverse logos, which display underrepresented features. For the purpose of comparing tRNA identity elements between different taxa we introduce two contrasting logos, the information difference and the Kullback-Leibler divergence difference logos.</p>

Research in the last few decades has revealed the great capacity of the RNA molecule. RNA, which previously was assumed to play a main role only as an intermediate in the translation of genes to proteins, is today known to play many important roles in the cell in addition to that as a messenger RNA and transfer RNA, including the ability to catalyze reactions and gene regulations at various levels. This thesis investigates several computational aspects of RNA. We will discuss identification of novel RNAs and RNAs that are known to exist in related species, RNA secondary structure prediction, as well as more general tools for analyzing, visualizing and classifying RNA sequences. We present two benchmark studies concerning RNA identification, both de novo identification/characterization of single RNA sequences and homology search methods. We develope a novel algorithm for analysis of the RNA folding landscape that is based on the nearest neighbor energy model adopted in many secondary structure prediction programs. We implement this algorithm, which computes structural neighbors of a given RNA secondary structure, in the program RNAbor, which is accessible on a web server. Furthermore, we combine a mutual information based structure prediction algorithm with a sequence logo visualization to create a novel visualization tool for analyzing an RNA alignment and identifying covarying sites. Finally, we present extensions to sequence logos for the purpose of tRNA identity analysis. We introduce function logos, which display features that distinguish functional subclasses within a large set of structurally related sequences, as well as the inverse logos, which display underrepresented features. For the purpose of comparing tRNA identity elements between different taxa we introduce two contrasting logos, the information difference and the Kullback-Leibler divergence difference logos.

Due to increasing problems with bacterial resistance development, there is a growing need for identifying new types of antibiotics. Antimicrobial peptides constitute an interesting group of substances for this purpose, since they are believed to act mainly by disrupting the bacterial membrane, which is a fast and non-specific mechanism. In order to understand the details on this action simplified phospholipid model membranes based on liposomes, monolayers and bilayers, were employed in this thesis. By in situ ellipsometry studies on supported lipid bilayers in combination with leakage from liposomes it was found that peptide-induced membrane rupture to a great extent is related to peptide adsorption. The peptide activity and mechanism of action is highly dependent on peptide properties such as length, topology, charge, and hydrophobicity. Electrostatic interactions are crucial for peptide adsorption, whereas α-helix formation is of less importance, demonstrated by the dominating peptide conformation being random coil both in absence and presence of membranes, as investigated by circular dichroism. Comparable effects were observed in both mono- and bilayer systems, showing that formation of transmembrane structures is no prerequisite for membrane rupture by complement-derived peptides. Electrochemical studies on these peptides further demonstrated that hydrophobic interactions facilitate peptide penetration into the membrane, causing defects in close proximity to the peptides, while strong electrostatic interactions arrest the peptide in the headgroup region. Increasing the peptide hydrophobicity, by e.g., tryptophan end-tagging, also increases salt resistance. Good correlations were found between model membrane investigations and antibacterial activity towards both Gram-negative and Gram-positive bacteria, showing that membrane rupture is a key mechanism of action for the peptides investigated. In addition, for all peptides investigated cell toxicity is low.

Unravelling biological processes is dependent on the adequate modelling of regulatory mechanisms that determine the timing and spatial patterns of gene expression. In the last decade, a novel regulatory mechanism has been discovered and its biological importance has been increasingly recognised. This mechanism is mediated by RNA molecules named miRNAs that are the product of the maturation of non-coding gene transcripts and act post- transcriptionally usually to dampen or abolish the expression of protein-coding genes. Despite having eluded detection for such a long time, it is now clear that the elucidation of the expression pattern of many genes cannot be achieved without incorporating the effects of miRNA-mediated regulation. The technical difficulties that the experimental detection of these regulators entailed prompted the development of increasingly sophisticated computational approaches. Gene finding strategies originally developed for coding genes cannot be applied since these non- coding molecules are subject to very different sequence restraints and are too short to exhibit statistical properties that can be easily distinguished from the background. As a result, com- putational tools came to rely heavily on the identification of conserved sequences, distant homologs and machine learning techniques. Recent developments in sequencing technology have overcome some of the limitations of earlier experimental approaches, but pose new computational challenges. At present, the identification of new miRNA genes is therefore the result of the use of several approaches, both computational and experimental. In spite of the advancement that this research field has known in the last several years, we are still not able to formally and rigourously characterise miRNA genes in order to identify whichever sequence, structure or contextual requirements are needed to turn a DNA sequence into a functional miRNA. Efforts using computational algorithms towards the enumeration of the full set of miRNAs of an organism have been limited by strong reliance on arguments of precursor conservation and feature similarity. However, miRNA precursors may arise anew or be lost across the evolutionary history of a species and a newly-sequenced genome may be evolutionarily too distant from other genomes for an adequate comparative analysis. In addition, the learning of intricate classification rules based purely on features shared by miRNA precursors that are currently known may reflect a perpetuating identification bias rather than a sound means to tell true miRNAs from other genomic stem-loops. In this thesis, we present a strategy to sieve through the vast amount of stem-loops found in metazoan genomes in search of pre-miRNAs, significantly reducing the set of candidates while retaining most known miRNA precursors. Our approach relies on precursor properties derived from the current knowledge of miRNA biogenesis, analysis of the precursor structure and incorporation of information about the transcription potential of each candidate. i Our approach has been applied to the genomes of Drosophila melanogaster and Anophe- les gambiae, which has allowed us to show that there is a strong bias amongst annotated pre-miRNAs towards robust stem-loops in these genomes and to propose a scoring scheme for precursor candidates which combines four robustness measures. Additionally, we have identified several known pre-miRNA homologs in the newly-sequenced Anopheles darlingi and shown that most are found amongst the top-scoring precursor candidates for that or- ganism, with respect to the combined score. The structural analysis of our candidates and the identification of the region of the structural space where known precursors are usually found allowed us to eliminate several candidates, but also showed that there is a staggering number of genomic stem-loops which seem to fulfil the stability, robustness and structural requirements indicating that additional evidence is needed to identify functional precursors. To this effect, we have introduced different strategies to evaluate the transcription potential of the remaining candidates which vary according to the information which is available for the dataset under study.