Membrane Protein Stability Analyses by Means of Protein Energy Profiles in Case of Nephrogenic Diabetes Insipidus

Diabetes insipidus (DI) is a rare endocrine, inheritable disorder with low incidences in an estimated one per 25,000–30,000 live births. This disease is characterized by polyuria and compensatory polydypsia. The diverse underlying causes of DI can be central defects, in which no functional arginine vasopressin (AVP) is released from the pituitary or can be a result of defects in the kidney (nephrogenic DI, NDI). NDI is a disorder in which patients are unable to concentrate their urine despite the presence of AVP. This antidiuretic hormone regulates the process of water reabsorption from the prourine that is formed in the kidney. It binds to its type-2 receptor (V2R) in the kidney induces a cAMP-driven cascade, which leads to the insertion of aquaporin-2 water channels into the apical membrane. Mutations in the genes of V2R and aquaporin-2 often lead to NDI. We investigated a structure model of V2R in its bound and unbound state regarding protein stability using a novel protein energy profile approach. Furthermore, these techniques were applied to the wild-type and selected mutations of aquaporin-2. We show that our results correspond well to experimental water ux analysis, which confirms the applicability of our theoretical approach to equivalent problems

A multiscale model of the regulation of aquaporin 2 recycling

The response of cells to their environment is driven by a variety of proteins and messenger molecules. In eukaryotes, their distribution and location in the cell are regulated by the vesicular transport system. The transport of aquaporin 2 between membrane and storage region is a crucial part of the water reabsorption in renal principal cells, and its malfunction can lead to Diabetes insipidus. To understand the regulation of this system, we aggregated pathways and mechanisms from literature and derived three models in a hypothesis-driven approach. Furthermore, we combined the models to a single system to gain insight into key regulatory mechanisms of Aquaporin 2 recycling. To achieve this, we developed a multiscale computational framework for the modeling and simulation of cellular systems. The analysis of the system rationalizes that the compartmentalization of cAMP in renal principal cells is a result of the protein kinase A signalosome and can only occur if specific cellular components are observed in conjunction. Endocytotic and exocytotic processes are inherently connected and can be regulated by the same protein kinase A signal

Forensic Analysis of Bloodstain Color

This book chapter delves into the field of colorimetric analysis of bloodstains in forensic science, focusing on its application in crime scene investigation. Therefore it provides a comprehensive overview of the biological background of age-induced color changes. The chapter begins with an introduction to the significance of blood evidence in solving crimes and the emergence of colorimetry as a valuable tool in blood analysis. The principles of forensic spectroscopy are explored, specifically its ability to provide information crucial to crime reconstruction, such as the age of bloodstains. The chapter discusses the transformation of hemoglobin derivatives over time and the corresponding measurable color changes that accompany aging blood traces

2Statistically significant dependence of the Xaa-Pro peptide bond conformation on secondary structure and amino acid sequence

BACKGROUND: A reliable prediction of the Xaa-Pro peptide bond conformation would be a useful tool for many protein structure calculation methods. We have analyzed the Protein Data Bank and show that the combined use of sequential and structural information has a predictive value for the assessment of the cis versus trans peptide bond conformation of Xaa-Pro within proteins. For the analysis of the data sets different statistical methods such as the calculation of the Chou-Fasman parameters and occurrence matrices were used. Furthermore we analyzed the relationship between the relative solvent accessibility and the relative occurrence of prolines in the cis and in the trans conformation. RESULTS: One of the main results of the statistical investigations is the ranking of the secondary structure and sequence information with respect to the prediction of the Xaa-Pro peptide bond conformation. We observed a significant impact of secondary structure information on the occurrence of the Xaa-Pro peptide bond conformation, while the sequence information of amino acids neighboring proline is of little predictive value for the conformation of this bond. CONCLUSION: In this work, we present an extensive analysis of the occurrence of the cis and trans proline conformation in proteins. Based on the data set, we derived patterns and rules for a possible prediction of the proline conformation. Upon adoption of the Chou-Fasman parameters, we are able to derive statistically relevant correlations between the secondary structure of amino acid fragments and the Xaa-Pro peptide bond conformation

Clusterbildung in finiten und expandierenden Systemen

Diese Promotionsarbeit liefert Beiträge zur Nukleationstheorie. Der Prozess der Clusterung von Wassermolekülen in einem finiten übersättigten Wasserdampf wird mittels Mastergleichungformalismus beschrieben. Es erfolgt eine Erweiterung der Beschreibung auf offene expandierende Systeme, wobei ein Teilchenaustausch mit der Umgebeung stattfindet. Ansätze für die Bindungsenergie von Clustern werden getestet

Efficient unfolding pattern recognition in single molecule force spectroscopy data

BackgroundSingle-molecule force spectroscopy (SMFS) is a technique that measures the force necessary to unfold a protein. SMFS experiments generate Force-Distance (F-D) curves. A statistical analysis of a set of F-D curves reveals different unfolding pathways. Information on protein structure, conformation, functional states, and inter- and intra-molecular interactions can be derived.ResultsIn the present work, we propose a pattern recognition algorithm and apply our algorithm to datasets from SMFS experiments on the membrane protein bacterioRhodopsin (bR). We discuss the unfolding pathways found in bR, which are characterised by main peaks and side peaks. A main peak is the result of the pairwise unfolding of the transmembrane helices. In contrast, a side peak is an unfolding event in the alpha-helix or other secondary structural element. The algorithm is capable of detecting side peaks along with main peaks.Therefore, we can detect the individual unfolding pathway as the sequence of events labeled with their occurrences and co-occurrences special to bR\u27s unfolding pathway. We find that side peaks do not co-occur with one another in curves as frequently as main peaks do, which may imply a synergistic effect occurring between helices. While main peaks co-occur as pairs in at least 50% of curves, the side peaks co-occur with one another in less than 10% of curves. Moreover, the algorithm runtime scales well as the dataset size increases.ConclusionsOur algorithm satisfies the requirements of an automated methodology that combines high accuracy with efficiency in analyzing SMFS datasets. The algorithm tackles the force spectroscopy analysis bottleneck leading to more consistent and reproducible results

Triangle network motifs predict complexes by complementing high-error interactomes with structural information

BackgroundA lot of high-throughput studies produce protein-protein interaction networks (PPINs) with many errors and missing information. Even for genome-wide approaches, there is often a low overlap between PPINs produced by different studies. Second-level neighbors separated by two protein-protein interactions (PPIs) were previously used for predicting protein function and finding complexes in high-error PPINs. We retrieve second level neighbors in PPINs, and complement these with structural domain-domain interactions (SDDIs) representing binding evidence on proteins, forming PPI-SDDI-PPI triangles.ResultsWe find low overlap between PPINs, SDDIs and known complexes, all well below 10%. We evaluate the overlap of PPI-SDDI-PPI triangles with known complexes from Munich Information center for Protein Sequences (MIPS). PPI-SDDI-PPI triangles have ~20 times higher overlap with MIPS complexes than using second-level neighbors in PPINs without SDDIs. The biological interpretation for triangles is that a SDDI causes two proteins to be observed with common interaction partners in high-throughput experiments. The relatively few SDDIs overlapping with PPINs are part of highly connected SDDI components, and are more likely to be detected in experimental studies. We demonstrate the utility of PPI-SDDI-PPI triangles by reconstructing myosin-actin processes in the nucleus, cytoplasm, and cytoskeleton, which were not obvious in the original PPIN. Using other complementary datatypes in place of SDDIs to form triangles, such as PubMed co-occurrences or threading information, results in a similar ability to find protein complexes.ConclusionGiven high-error PPINs with missing information, triangles of mixed datatypes are a promising direction for finding protein complexes. Integrating PPINs with SDDIs improves finding complexes. Structural SDDIs partially explain the high functional similarity of second-level neighbors in PPINs. We estimate that relatively little structural information would be sufficient for finding complexes involving most of the proteins and interactions in a typical PPIN

Das Auto als forensischer Datenspeicher : Technische Hilfsmittel und Möglichkeiten einer forensischen Auswertung von Kfz-Elektroniksystemen

Heutige Kraftfahrzeuge beinhalten eine große Anzahl an elektronischen Komponenten. Die Steuergeräte sind sowohl intern miteinander über Bussysteme als auch extern vernetzt. In diesen Steuergeräten werden eine Vielzahl an Daten gespeichert, die aus Ermittlersicht zur Aufklärung von Unfällen oder sogar Straftaten herangezogen werden können. In diesem Paper wird die Akquise von Daten aus Kraftfahrzeugen anhand ausgewählter Beispiele dargestellt. Es werden neben der grundlegenden Architektur der in Kraftfahrzeugen verbauten Bus-Systeme verschiedene technische Hilfsmittel aufgezeigt, die zur Datenextraktion Verwendung finden können. Eine besondere Rolle spielen extrahierbare Fehlermeldungen in Steuergeräten, wobei diese Daten via On-Board-Diagnose oder auch direkt aus Steuergeräten auslesbar sind. Es wird dargestellt, welche Informationen diese Fehlermeldungen beinhalten und wie diese für Ermittler verwendbar sind. Im weiteren Verlauf wird dargestellt, wie aus Schlüsseltranspondern Informationen gewonnen werden können, sodass diese Daten mit anderen forensischen Informationen verknüpfbar sind. Ein weiteres Ziel des Papers ist die Darstellung der Analyse von Infotainmentsystemen, die unter anderem Positionsdaten, gespeicherte Routen, Telefondaten oder auch genaue Abstellorte eines Fahrzeugs zu einem definierten Zeitpunkt beinhalten können

Digitale Fortschritte in der Gesichtsweichteilrekonstruktion: Von manuellen Methoden zu Künstlicher Intelligenz

Der Artikel behandelt die Entwicklung der Gesichtsweichteilrekonstruktion (GWR) von analogen zu digitalen Methoden. Letztere umfassen seit geraumer Zeit auch Methoden der Künstlichen Intelligenz (KI), welche als vielversprechender Ansatz zur Verbesserung von Genauigkeit und Effizienz hervorgehoben werden. Die Integration von Maschinellem Lernen, mit Erweiterung der Datengrundlage unter Einbezug von CT- und MRT-Daten, eröffnet neue Perspektiven für die GWR