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This master's thesis deals with prediction of hot spots in proteins. The theorethical part describes compositions of proteins interfaces and hot spots. There are mentioned basic principles of hot spots prediction. In the practical part is selected method, using the S-Transform, designed to pseudocode and then implmented to Matlab software. Created program is tested on a sample of data and compared with available methods.

According to the law of crime concentration, a certain percentage of crime is predicted to be concentrated at a certain percentage of microgeographic units, and relatively large amounts of crime are predicted to be accounted for by a small percentage of places. Given the lack of research testing the law in a Swedish context and for a whole country, this study set out to examine the concentration of crime at all densely populated areas in Sweden. Analyzing national grid net data, where all densely built-up areas of Sweden were divided into 250 x 250 meter pixels with added police recorded crime data, the study aimed to examine how many percent of the pixels are required to account for 25, 50 and 80% of the crimes in all densely populated areas; how the concentrations differ between small, medium-sized and big cities; how the concentrations differ between violent and property crimes in all of the country; and how an observed crime concentration compares to a counterfactual, randomized concentration. The results indicated a crime concentration that is stronger than the ones observed in most previous studies, with just 0.4, 2.3 and 10.2% of the pixels accounting for 25, 50 and 80% of all crimes in all densely populated areas, respectively. In line with previous research, the results also showed that crime is more strongly concentrated in smaller cities compared to the big ones, that violent crime is more strongly concentrated than property crime, and that the observed concentration of violent crime is considerably stronger than a counterfactual, randomized concentration in the form of a Poisson distribution. Further research on crime concentration in Sweden is requested to build on these findings.

High-density lipoproteins and their major protein, apolipoprotein A-I (apoA-I), remove excess cellular cholesterol and protect against atherosclerosis. However, in acquired amyloidosis, non-variant full-length apoA-I deposits as fibrils in arteries contributing to atherosclerosis. In hereditary amyloidosis (AApoAI), a potentially fatal disease, N-terminal fragments of variant apoA-I deposit in vital organs and damage them. There is no cure for apoA-I amyloidosis and its structural basis is unknown. Previously, AApoAI mutations were mapped on the crystal structure of the human C-terminally truncated Δ(185-243)apoA-I. The results suggested that the mutation-induced destabilization of the lipid-free protein initiates β-aggregation. Our biophysical studies showed that amyloidogenic mutations G26R, W50R, F71Y and L170P did not necessarily destabilize the native structure, prompting us to search for additional triggers of apoA-I misfolding. We mapped residue segments predicted to promote β-aggregation (termed amyloid hot spots) on the atomic structure of ∆(185-243)apoA-I. The results suggested that perturbed packing of these hot spots, particularly residues 14-22, triggers amyloidosis. This enabled us to propose the first molecular mechanism of apoA-I misfolding. To explore a potential mechanism, we combined structural, stability, dynamics and functional studies of several amyloidogenic mutants and a non-amyloidogenic control, L159R. All mutants reduced structural protection of the segment 14-22, supporting our hypothesis that increased dynamics of this segment triggers AApoAI. The non-amyloidogenic mutant showed helical unfolding near the mutation site indicating susceptibility to proteolysis. We propose that the major factors that make apoA-I amyloidogenic are reduced protection of the major amyloidogenic segments combined with the structural integrity of the four-helix bundle to facilitate protein aggregation. Together, our results suggest that the fate of apoA-I in vivo depends on the balance between its misfolding, proteolysis, and protective protein-lipid interactions. Our structural and bioinformatics analysis of other members of the apolipoprotein family (A-II, A-IV, A-V, B, C-I, C-II, C-III, E, SAA) showed that apolipoproteins’ propensity to form amyloid is rooted in the proteins’ hydrophobicity, which is key to the lipid binding ability. The overlap of functional and pathologic interfaces suggests competition between normal protein function and misfolding. Therefore, increasing apolipoprotein retention on the lipid surface provides a potential therapeutic strategy against amyloidosis.

Detection and analysis of protein-ligand binding sites is an important area of research in drug discovery. The FTMap web server is an established computational method for detection of binding hot spots, or regions on the protein surface that contribute disproportionately to the ligand binding free energy. This body of work primarily focuses on the utilization and advancement of FTMap for the study of protein-ligand interactions and their applications to drug discovery. First, the driving forces behind why some proteins require compounds beyond Lipinski’s rule-of-five (bRo5) guidelines are evaluated for 37 protein targets. Three types of proteins are identified on the basis of their binding hot spots, described by FTMap, and their ligand binding affinity profiles. We describe the multifaceted motivations for bRo5 drug discovery for each group of targets, including increased binding affinity, improved selectivity, decreased toxicity, and decreased off-target effects. Second, the conservation of surface binding properties in protein models is evaluated, with particular emphasis on their utility in drug discovery. Here, the probe-binding locations determined by FTMap are used to generate a binding fingerprint, and the Pearson correlation between the binding fingerprint of an experimental structure and a predicted model indicates the level of surface property conservation, without any knowledge of the protein function a priori. This analysis was performed on the protein models submitted to the Critical Assessment of Techniques for Protein Structure Prediction (CASP) rounds 12 and 14, and results were correlated with well-established structure quality metrics. Third, development of the publicly-available FTMove web server (https://ftmove.bu.edu) is described for detection of binding sites and their respective strengths across multiple different conformations of a protein. FTMove was tested on 22 proteins with known allosteric binding sites, and reliably identified both the orthosteric and allosteric binding sites as highly ranked binding sites. The results yield important insight into the dynamics and druggability of such binding sites. Finally, high throughput affinity purified, mass spectrometry data is evaluated for identification of protein-metabolite interactions (PMIs) in Escherichia coli. A detailed search for known PMIs in both the Protein Data Bank and KEGG database is described, and the resulting curated sets of 21 recovered and 37 potentially novel PMIs in E. Coli are presented. Finally, high confidence novel PMIs were evaluated with the template-based small molecule docking program, LigTBM. / 2023-01-26T00:00:00Z

The Utah Department of Transportation (UDOT) Traffic and Safety Division continues to advance the safety of roadway sections throughout the state. In an effort to aid UDOT in meeting their goal, the Department of Civil and Environmental Engineering at Brigham Young University (BYU) has worked with the Statistics Department in developing analysis tools for safety. The most recent of these tools has been the development of a hierarchical Bayesian Poisson Mixture Model (PMM) of traffic crashes known as the Utah Crash Prediction Model (UCPM), a hierarchical Bayesian Binomial statistical model known as the Utah Crash Severity Model (UCSM), and a Bayesian Horseshoe selection method. The UCPM and UCSM models helped with the analysis of safety on UDOT roadways statewide and the integration of the results of these models was applied to Geographic Information System (GIS) framework. This research focuses on the addition of roadway attributes in the selection and analysis of “hot spots.” This is in conjunction with the framework for highway safety mitigation migration in Utah with its six primary steps: network screening, diagnosis, countermeasure selection, economic appraisal, project prioritization, and effectiveness evaluation. The addition of roadway attributes was included as part of the network screening, diagnosis, and countermeasure selection, which are included in the methodology titled “Hot Spot Identification and Analysis.” Included in this research was the documentation of the steps and process for data preparation and model use for the step of network screening and the creation of one of the report forms for the steps of diagnosis and countermeasure selection. The addition of roadway attributes is required at numerous points in the process. Methods were developed to locate and evaluate the usefulness of available data. Procedures and systemization were created to convert raw data into new roadway attributes, such as grade and sag/crest curve location. For the roadway attributes to be useful in selection and analysis, methods were developed to combine and associate the attributes to crashes on problem segments and problem spots. The methodology for “Hot Spot Identification and Analysis” was enhanced to include steps for the inclusion and defining of the roadway attributes. These methods and procedures were used to help in the identification of safety hot spots so that they can be analyzed and countermeasures selected. Examples of how the methods are to function are given with sites from Utah’s state roadway network.

Studies about hot spots of crimes have found that crimes are clustered; few places have many crimes. There is a consensus among criminologists that opportunities for crimes are important when explaining hot spots, at some places, there are more opportunities than at other places. The same applies for hot spots of robberies. Most studies done on the subject are quantitative, relatively little is done using a qualitative approach. Furthermore, little research is done in a Swedish or Scandinavian context. To fill these research gaps this study use participant observations to research five hot spots of robberies in Malmö. The research will try to answer which characteristics are important to explain why the places are hot spots and what the similarities and differences there between the places are. This will be analyzed using the Routine Activity Theory and the Crime Pattern Theory. The findings suggest that place-specific things are important to explain why the places are hot spots, but when using the theories several places are similar.

Protein-protein interactions (PPI) represent a challenging target class in contemporary small molecule drug discovery. The difficulty arises because PPI sites are structurally and physicochemically different from conventional drug binding sites. Moreover, we currently lack a good understanding of the druggability of PPI targets: that is, how the structure and properties of a PPI interface site relates to the properties of small molecules that can bind to that site with high affinity. Efforts to achieve potent drug-like small molecule inhibitors of PPI interfaces, involving a wide range targets, historically have largely been unsuccessful, leading to the conclusion that new inhibitor chemotypes are needed to inhibit this class of target. In this thesis, I describe the application of two approaches to identify inhibitors of the PPI interface between Kelch-like ECH associated protein 1 (KEAP1) and Nuclear factor (erythroid-derived 2)-like 2 (Nrf2): (i) screening a library of synthetic macrocycles, and (ii) fragment-based lead discovery. I validate and characterize the hit compounds obtained. In the case of the fragment hits, I investigate what features of the compounds are required for binding to the target (Chapter Two). In parallel, I investigate the structure of the hot spot ensemble at the KEAP1/Nrf2 binding interface using three complementary methods: alanine scanning mutagenesis, fragment screening, and in silico probe mapping using the FTMap algorithm (Chapter Three). This analysis brings insight into the druggability of KEAP1, and advances our understanding of the utility and limitations of those three widely used methods for characterizing the hot spot ensembles at PPI interfaces (Chapter Three). Finally, to gain additional insight into the energetics of KEAP1/Nrf2 binding, I probe the additivity of combinations of alanine mutants (Chapter Four). I use the results to propose a quantitative approach to categorizing the various degrees of additivity that can be observed at PPI interfaces, and discuss the possible structural basis for these behaviors. The model potentially provides a more general framework for understanding the binding energetics at PPI interfaces using combinations of mutations.

<p>This dissertation, while sometimes broad in scope, attempts to tie together the author’s work with the goal of better understanding the phenomenon of explosives initiation at the mesoscale. Discussion of the need for such an investigation will be covered, including how mesoscale phenomena and the dominant theory of explosives initiation–hot spot theory–are intimately related. Furthermore, some difficulties in designing mesoscale experiments will be mentioned. Sample preparation–one of the more difficult tasks in this regime–will be covered, including single crystal growth, mechanical machining with a quasi-CNC machine, laser machining, and hacks to a tungsten wire saw for novel sample production. The author will go on to show work done in a quasi-static regime, at low strain rates, and at medium- high strain rates. These novel experiments start to show how pore collapse functions in single-crystal HMX. Additional work with thermophosphors, which may be relevant to future experiments, is also presented. New experimental diagnostics designed and constructed by the author are laid out for future reference, along with improvements to a gas gun apparatus.</p>

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