Florian Heinke

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.

eProS—a database and toolbox for investigating protein sequence–structure–function relationships through energy profiles

Gaining information about structural and functional features of newly identified proteins is often a difficult task. This information is crucial for understanding sequence–structure–function relationships of target proteins and, thus, essential in comprehending the mechanisms and dynamics of the molecular systems of interest. Using protein energy profiles is a novel approach that can contribute in addressing such problems. An energy profile corresponds to the sequence of energy values that are derived from a coarse-grained energy model. Energy profiles can be computed from protein structures or predicted from sequences. As shown, correspondences and dissimilarities in energy profiles can be applied for investigations of protein mechanics and dynamics. We developed eProS (energy profile suite, freely available at http://bioservices.hs-mittweida.de/Epros/), a database that provides ∼76 000 pre-calculated energy profiles as well as a toolbox for addressing numerous problems of structure biology. Energy profiles can be browsed, visualized, calculated from an uploaded structure or predicted from sequence. Furthermore, it is possible to align energy profiles of interest or compare them with all entries in the eProS database to identify significantly similar energy profiles and, thus, possibly relevant structural and functional relationships. Additionally, annotations and cross-links from numerous sources provide a broad view of potential biological correspondences.

Structure Topology Prediction of Discriminative Sequence Motifs in Membrane Proteins with Domains of Unknown Functions

Motivation. Membrane proteins play essential roles in cellular processes of organisms. Photosynthesis, transport of ions and small molecules, signal transduction, and light harvesting are examples of processes which are realised by membrane proteins and contribute to a cells specificity and functionality. The analysis of membrane proteins has shown to be an important part in the understanding of complex biological processes. Genome-wide investigations of membrane proteins have revealed a large number of short, distinct sequence motifs. Results. The in silico analysis of 32 membrane protein families with domains of unknown functions discussed in this study led to a novel approach which describes the separation of motifs by residue-specific distributions. Based on these distributions, the topology structure of the majority of motifs in hypothesised membrane proteins with unknown topology can be predicted. Conclusion. We hypothesise that short sequence motifs can be separated into structure-forming motifs on the one hand, as such motifs show high prediction accuracy in all investigated protein families. This points to their general importance in α-helical membrane protein structure formation and interaction mediation. On the other hand, motifs which show high prediction accuracies only in certain families can be classified as functionally important and relevant for family-specific functional characteristics.

Towards Substrate-independent Age Estimation of Blood Stains based on Dimensionality Reduction and k-Nearest Neighbor Classification of Absorbance Spectroscopic Data

The age determination of blood traces provides important hints for the chronological assessment of criminal events and their reconstruction. Current methods are often expensive, involve significant experimental complexity and often fail to perform when being applied to aged blood samples taken from different substrates. In this work an absorption spectroscopy-based blood stain age estimation method is presented, which utilizes 400-640nm absorption spectra in computation. Spectral data from 72 differently aged pig blood stains (2h to three weeks) dried on three different substrate surfaces (cotton, polyester and glass) were acquired and the turnover-time correlations were utilized to develop a straightforward age estimation scheme. More precisely, data processing includes data dimensionality reduction, upon which classic k-nearest neighbor classifiers are employed. This strategy shows good agreement between observed and predicted blood stain age (r>0.9) in cross-validation. The presented estimation strategy utilizes spectral data from dissolved blood samples to bypass spectral artifacts which are well known to interfere with other spectral methods such as reflection spectroscopy. Results indicate that age estimations can be drawn from such absorbance spectroscopic data independent from substrate the blood dried on. Since data in this study was acquired under laboratory conditions, future work has to consider perturbing environmental conditions in order to assess real-life applicability.

Analysis of Membrane Protein Stability in Diabetes Insipidus

Diabetes insipidus (DI) is a rare endocrine disorder, with an incidence in the general population assessed on one case per 25,000-30,000 people (Robertson, 1995; Ananthakrishnan, 2009; Krysiak, et al., 2010). It is a disease characterized by polyuria and compensatory polydipsia. The underlying causes of DI are diverse and can be central defects, in which no functional arginine-vasopressin is released from the pituitary, or may becaused by defects in the kidney (nephrogenic DI, NDI). Four different types of NDI are known. First, acquired NDI can originate as a side-effect of drugs, with the most prominent being the antibipolar drug lithium. Second and third, autosomal recessive and dominant inheritable NDI, are caused by gene mutations in the AQP2 gene encoding aquaporin-2. Finally, mutations in the AVPR2 gene (Deen et al., 1994; Mulders, 1998), which encodes the V2 vasopressin receptor (V2R), are the cause of the X-linked inheritable form of NDI (Fig. 1 right) (Van den Ouweland et al., 1992; Rosenthal, 1992).

Novel Computational Techniques for Thin-Layer Chromatography (TLC) Profiling and TLC Profile Similarity Scoring

Thin-layer chromatography (TLC) is an experimental separation technique for multi-compound mixtures widely applied in various fields of industry and research. In contrast to comparable techniques, TLC is straightforward, cost- and time-efficient, and well-applicable in field operations due to its flexibility. In TLC, after applying a mixture sample to the adsorbent layer on the TLC plate, the compounds ascent the plate at different rates due to their individual physicochemical characteristics, whereas separation is eventually achieved.

Simulation of diffusion using a modular cell dynamic simulation system

A variety of mathematical models is used to describe and simulate the multitude of natural processes examined in life sciences. In this paper we present a scalable and adjustable foundation for the simulation of natural systems. Based on neighborhood relations in graphs and the complex interactions in cellular automata, the model uses recurrence relations to simulate changes on a mesoscopic scale. This implicit definition allows for the manipulation of every aspect of the model even during simulation. The definition of value rules ω facilitates the accumulation of change during time steps. Those changes may result from different physical, chemical or biological phenomena. Value rules can be combined into modules, which in turn can be used to create baseline models. Exemplarily, a value rule for the diffusion of chemical substances was designed and its applicability is demonstrated. Finally, the stability and accuracy of the solutions is analyzed.

SequenceCEROSENE: a computational method and web server to visualize spatial residue neighborhoods at the sequence level

BackgroundTo understand the molecular function of biopolymers, studying their structural characteristics is of central importance. Graphics programs are often utilized to conceive these properties, but with the increasing number of available structures in databases or structure models produced by automated modeling frameworks this process requires assistance from tools that allow automated structure visualization. In this paper a web server and its underlying method for generating graphical sequence representations of molecular structures is presented.ResultsThe method, called SequenceCEROSENE (color encoding of residues obtained by spatial neighborhood embedding), retrieves the sequence of each amino acid or nucleotide chain in a given structure and produces a color coding for each residue based on three-dimensional structure information. From this, color-highlightedsequences are obtained, where residue coloring represent three-dimensional residue locations in the structure. This color encoding thus provides a one-dimensional representation, from which spatial interactions, proximity and relations between residues or entire chains can be deduced quickly and solely from color similarity. Furthermore, additional heteroatoms and chemical compounds bound to the structure, like ligands or coenzymes, are processed and reported as well.To provide free access to SequenceCEROSENE, a web server has been implemented that allows generating color codings for structures deposited in the Protein Data Bank or structure models uploaded by the user. Besides retrieving visualizations in popular graphic formats, underlying raw data can be downloaded as well. In addition, the server provides user interactivity with generated visualizations and the three-dimensional structure in question.ConclusionsColor encoded sequences generated by SequenceCEROSENE can aid to quickly perceive the general characteristics of a structure of interest (or entire sets of complexes), thus supporting the researcher in the initial phase of structure-based studies. In this respect, the web server can be a valuable tool, as users are allowed to process multiple structures, quickly switch between results, and interact with generated visualizations in an intuitive manner.The SequenceCEROSENE web server is available at https://biosciences.hs-mittweida.de/seqcerosene.

eProS – A Bioinformatics Knowledgebase, Toolbox and Database for Characterizing Protein Function

Proteins are macromolecules that facilitate virtually every biological process. Information on functional and structural characteristics of proteins is invaluable in life sciences, but remain difficult to obtain, both computationally and experimentally.

eQuant - A Server for Fast Protein Model Quality Assessment by Integrating High-Dimensional Data and Machine Learning

In molecular biology, reliable protein structure models are essential in order to understand the functional role of proteins as well as diseases related to them. Structures are derived by complex and resource-demanding experiments, whereas in silico structure modeling and refinement approaches are established to cope with experimental limitations. Nevertheless, both experimental and computational methods are prone to errors. In consequence, small local regions or even the whole tertiary structure can be unreliable or erroneous, leading the researcher to formulate false hypotheses and draw false conclusions.