This thesis describes an investigation of the mechanistic differences of hard and soft wheat varieties in the course of dough formation. These two classes of wheat exhibit dissimilar end-use, as hard wheat flour is known for its bread making attributes, whereas soft wheat flour is suitable for cake and cookie production. This difference is related to the grain hardness, protein content and property of gluten, in addition to chemical interactions that are occurring during dough making. Covalent and hydrophobic interactions, as well as hydrogen bond formation, are the main interactions that take place during dough mixing. However, the contribution of each interaction in dough formation of hard and soft wheat is not known. One variety of hard and one variety of soft wheat flour were mixed to their optimum hydration level (500 BU), as determined by farinograph. The extent of covalent interactions of gluten proteins during dough mixing was examined by monitoring changes in the solubility of flour proteins in a 2% Sodium Dodecyl Sulfate (SDS) media. Moreover, the contribution of thiol groups to covalent bond was examined by measuring the changes in the accessible thiols throughout the mixing. Lower extractability of proteins and accessible thiols of hard wheat dough, compared to soft wheat dough, indicated the predominant role of covalent interactions in hard wheat dough. The complementary results from Size Exclusion High Performance Liquid Chromatography (SE-HPLC) indicated that covalent interaction of hard wheat dough primarily occurs between Low Molecular Weight (LMW) and High Molecular Weight (HMW) gluten proteins, whereas this interaction mainly occurs among LMW proteins in soft wheat doughs. Fewer hydrophobic interactions in hard wheat dough in compare with soft wheat measured by Front-face fluorescence spectroscopy indicated that this interaction is more dominant in soft wheat dough. Study of the conformational change in secondary structure of protein (indirect approach to monitor hydrogen bond) by fourier transform infrared (FTIR) spectroscopy showed that β-sheets are formed in both varieties at their optimum dough strength. In hard wheat dough this structure resulted mainly from disulfide linkages, whereas in soft wheat dough this structure is more likely the result of hydrophobic interactions.

Nowadays, RNA is extensively acknowledged an important role in the functions of information transfer, structural components, gene regulation and etc. The secondary structure of RNA becomes a key to understand structure-function relationship. Computational prediction of RNA secondary structure does not only provide possible structures, but also elucidates the mechanism of RNA folding. Conventional prediction programs are either derived from evolutionary perspective, or aimed to achieve minimum free energy. In vivo, RNA folds during transcription, which indicates that native RNA structure is a result from both thermodynamics and kinetics. In this thesis, I first reviewed the current leading kinetic folding programs and demonstrate that these programs are not able to predict secondary structure accurately. Upon that, I proposed a new sequential folding program called GTkinetics. Given an RNA sequence, GTkinetics predicts a secondary structure and a series of RNA folding trajectories. It treats the RNA as a growing chain, and adds stable local structures sequentially. It is featured with a Z-score to evaluate stability of local structures, which is able to locate native local structures with high confidence. Since all stable local structures are captured in GTkinetics, it results in some false positives, which prevents the native structure to form as the chain grows. This suggests a refolding model to melt the false positive hairpins, probable intermediate structures, and to fold the RNA into a new structure with reliable long-range helices. By analyzing suboptimal ensemble along the folding pathway, I suggested a refolding mechanism, with which refolding can be evaluated whether or not to take place. Another way to favor local structures over long-distance structures, we introduced a distance penalty function into the free energy calculation. I used a sigmoidal function to compute the energy penalty according to the distance in the primary sequence between two nucleotides of a base pair. For both the training dataset and the test dataset, the distance function improves the prediction to some extent. In order to characterize the differences between local and long-range helices, I carried out analysis of standardized local nucleotide composition and base pair composition according to the two groups. The results show that adenine accumulates on the 5' side of local structure, but not on that of long-range helices. GU base pairs occur significantly more frequent in the local helices than that in the long-range helices. These indicate that the mechanisms to form local and long range helices are different, which is encoded in the sequence itself. Based on all the results, I will draw conclusions and suggest future directions to enhance the current sequential folding program.

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Magister Scientiae - MSc / Viral genomes consist of either deoxyribonucleic acid (DNA) or ribonucleic acid (RNA). The viral RNA molecules are responsible for two functions, firstly, their sequences contain the genetic code, which encodes the viral proteins, and secondly, they may form structural elements important in the regulation of the viral life-cycle. Using a host of computational and bioinformatics techniques we investigated how predicted secondary structure may influence the evolutionary dynamics of a group of single-stranded RNA viruses from the Picornaviridae family. We detected significant and marginally significant correlations between regions predicted to be structured and synonymous substitution constraints in these regions, suggesting that selection may be acting on those sites to maintain the integrity of certain structures. Additionally, coevolution analysis showed that nucleotides predicted to be base paired, tended to co-evolve with one another in a complimentary fashion in four out of the eleven species examined. Our analyses were then focused on individual structural elements within the genome-wide predicted structures. We ranked the predicted secondary structural elements according to their degree of evolutionary conservation, their associated synonymous substitution rates and the degree to which nucleotides predicted to be base paired coevolved with one another. Top ranking structures coincided with well characterized secondary structures that have been previously described in the literature. We also assessed the impact that genomic secondary structures had on the recombinational dynamics of picornavirus genomes, observing a strong tendency for recombination breakpoints to occur in non-coding regions. However, convincing evidence for the association between the distribution of predicted RNA structural elements and breakpoint clustering was not detected.

The issue of comparing ribosomal RNA secondary structures is currently an open research problem. Goal of this work is to design and implement program comparing so called mutual conservancy of a group of rRNA secondary structures. This program is included as a new module of an existing system called rPredictor consisting of the structure database and an algorithm that predicts these structures. This thesis covers an introduction into the problem of secondary structures conservancy identification and summarizes known approaches towards the problem. The result of this work is a stand alone program for the secondary structure comparison and also a new analytic module of the rPredictor system, where the secondary structure comparison program can be used for comparison of the structures from the rPredictor database. Powered by TCPDF (www.tcpdf.org)

The diploma thesis is dealing with searching in secondary structures of nucleic acids. The NA2Dsearch application was developed that allows to search databases of secondary structures for a structural motif. The application offers user-friendly graphical user interface where a query motif can be constructed in comfortable visual way using drag&drop, database and result structures can be browsed and visualized. The application contains original interactive nucleic acid structure visualization algorithm and novel search algorithm. The search algorithm can perform a motif search on structural data (unlike existing programs that can perform a motif search on sequence data). The motif search means that a query is created that describes the structure of motif of our interest with variabilities (e.g. the length of hairpin loop) that can be tolerated. Search results are ordered by the score computed according to the resemblance of hit and the query. The NA2Dsearch also supports searching in sequence data which are folded by external folding program. Searching capabilities are demonstrated on several search experiments involving HCV IRES and tRNA. Three searches for HCV IRES were performed: a search for HCV IRES structure in database of more than thousand of HCV genomic sequences, a folding analysis of HCV IRES...

Protein structure is not fixed in time, and conformational transitions are the keyto many biological interactions such as enzymatic reactions or signal transduction.Protein dynamics and secondary structure propensities describe these conformationaltransitions, defining how protein structure is likely to evolve in time. Unfortunatelythis kind of information is extremely hard to obtain and the required experimentsare expensive and time consuming.A backbone dynamics and secondary structure propensity predictor that worksfrom sequence only, called DynaMine, has recently been developed. DynaMine addsa new dimension to protein sequences that can, for instance, be exploited to identifyprotein regions involved in specific biological tasks and in protein classification. Thisthesis shows how these predictions can be used to infer emergent properties of pro-teins and how they can highlight hidden evolutionary relationships between remotehomologs.The thesis is divided in 4 parts, corresponding to four different topics in which dy-namics and secondary structure propensities are reported to play a crucial role: thefirst part describes a new pairwise algorithm that uses secondary structure propen-sities and dynamics to align remote homologous proteins. The following three partsdeal with dynamics-related protein emergent behaviours: protein disorder, beta-aggregation and DNA-binding capability in archaea. The results show how backbonedynamics and secondary structure propensities can help improving the prediction ofall the aforementioned subjects. With regard to the identification of DNA-bindingproteins and the prediction of beta-aggregation, experimental validation is also pro-vided and discussed. / Doctorat en Sciences / info:eu-repo/semantics/nonPublished

Motivation: SARS-CoV-2 is the virus responsible for the COVID-19 pandemic that currently impacts our world. SARS-CoV-2 is an enveloped, positive sense single stranded RNA virus and like other RNA viruses is known to form RNA secondary structure in its genome. In related viruses the secondary structures are responsible for fulfilling roles including proper expression of viral gene products and possibly regulation of viral genome replication. I hypothesize that SARS-CoV-2 may be capable of forming additional secondary structures beyond what is already known and that those secondary structures are identifiable on the basis of sequence conservation with related RNA viruses. Results: By repurposing and expanding an existing computational pipeline de- signed for the detection of structural RNAs in vertebrates, I identified 40 regions of the SARS-CoV-2 genome highly likely to form secondary structure. Partial re- identification of known secondary structures in the SARS-CoV-2 genome was achieved. To further explore the role these structures may fill, the 9 most conservatively pre- dicted structures were analyzed in wild viral samples collected from three Canadian provinces, and distinct patterns of mutation were observed. The 40 regions identi- fied by my modified pipeline were compared against three contemporary works and the differences between findings were quantified. Lastly, Variants of Concern for SARS-CoV-2 were analyzed for prevalent but poorly reported mutations that may influence RNA secondary structure. Code developed for this work is available at https://github.com/aziesel/MSc. / Graduate / 2023-04-06

There has been a notable rise in the alternative protein market in the recent years which promotes an interest in the research of both animal and plant proteins to establish better structure-function relationships. Over the years many analytical tools have been used to study proteins and compare them, however Raman Spectroscopy and Surface Enhanced Raman Spectroscopy (SERS) have not been as much used for this application. SERS consolidates Raman Spectroscopy that primarily measures molecular vibrations and nanostructures that enhance the weak Raman signals. The objective of this study is to explore the capability of the Raman instrumentation in combination with different substrates for spectroscopic analysis of 3 animal proteins viz. whey, k-casein and albumin from chicken egg white and 4 plant proteins namely mung bean, soy, pea and faba bean. Herein, we firstly established a method that could be applied to all proteins to detect characteristic peaks that are related to their structure. Of all the methods, SERS with silver dendrites was the most promising method that detected protein characteristic peaks, particularly the shifts around 700-900 cm-1 attributed to the CN stretch and tryptophan groups. Although different proteins exhibit similar spectral characteristics, they were discriminated using principal component analysis. Then we explored the optimal method to study the effect of different environmental conditions including pH and salt concentration on the protein spectroscopic analysis. The limitations of the substrates were better understood during this process as Ag dendrites failed to provide a spectrum in the high pH range but was compatible with different salt concentrations. The peaks in the Amide-I region were vi used as a marker to study the effect of change in pH and salt. Most proteins showing a shift in the band suggesting a transition from α-sheet to a random coil conformation. The acquired spectra and subsequent PCA results depicted that pea protein was the most susceptible to change in pH amongst other proteins whereas faba bean was susceptible to a change in salt concentration. Finally, these learnings were applied to analyze a real-world food product to compare its spectroscopic characteristic with the standards we have. In conclusion, we demonstrated that Raman Spectroscopy and SERS was able to provide distinct spectroscopic characteristics of plant and animal proteins that may be used to facilitate the quality control or product development of novel plant-based food products. Future work will investigate the relationship between the spectroscopic characteristics and the structural function of proteins.

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