Virksomhedstaksonomien: et værktøjfor praksisfællesskabet

Intet abstract

Tectonics of a K+ channel: The importance of the N-terminus for channel gating

AbstractThe small K+ channel Kcv represents the pore module of complex potassium channels. It was found that its gating can be modified by sensor domains, which are N-terminally coupled to the pore. This implies that the short N-terminus of the channel can transmit conformational changes from upstream sensors to the channel gates. To understand the functional role of the N-terminus in the context of the entire channel protein, we apply combinatorial screening of the mechanical coupling and long-range interactions in the Kcv potassium channel by reduced molecular models. The dynamics and mechanical connections in the channel complex show that the N-terminus is indeed mechanically connected to the pore domain. This includes a long rang coupling to the pore and the inner and outer transmembrane domains. Since the latter domains host the two gates of the channel, the data support the hypothesis that mechanical perturbation of the N-terminus can be transmitted to the channel gates. This effect is solely determined by the topology of the channel; sequence details only have an implicit effect on the coarse-grained dynamics via the fold and not through biochemical details at a smaller scale. This observation has important implications for engineering of synthetic channels on the basis of a K+ channel pore

Computing and visually analyzing mutual information in molecular co-evolution

<p>Abstract</p> <p>Background</p> <p>Selective pressure in molecular evolution leads to uneven distributions of amino acids and nucleotides. In fact one observes correlations among such constituents due to a large number of biophysical mechanisms (folding properties, electrostatics, ...). To quantify these correlations the mutual information -after proper normalization - has proven most effective. The challenge is to navigate the large amount of data, which in a study for a typical protein cannot simply be plotted.</p> <p>Results</p> <p>To visually analyze mutual information we developed a matrix visualization tool that allows different views on the mutual information matrix: filtering, sorting, and weighting are among them. The user can interactively navigate a huge matrix in real-time and search e.g., for patterns and unusual high or low values. A computation of the mutual information matrix for a sequence alignment in FASTA-format is possible. The respective stand-alone program computes in addition proper normalizations for a null model of neutral evolution and maps the mutual information to <it>Z</it>-scores with respect to the null model.</p> <p>Conclusions</p> <p>The new tool allows to compute and visually analyze sequence data for possible co-evolutionary signals. The tool has already been successfully employed in evolutionary studies on HIV1 protease and acetylcholinesterase. The functionality of the tool was defined by users using the tool in real-world research. The software can also be used for visual analysis of other matrix-like data, such as information obtained by DNA microarray experiments. The package is platform-independently implemented in <monospace>Java</monospace> and free for academic use under a GPL license.</p

BioPhysConnectoR: Connecting Sequence Information and Biophysical Models

<p>Abstract</p> <p>Background</p> <p>One of the most challenging aspects of biomolecular systems is the understanding of the coevolution in and among the molecule(s).</p> <p>A complete, theoretical picture of the selective advantage, and thus a functional annotation, of (co-)mutations is still lacking. Using sequence-based and information theoretical inspired methods we can identify coevolving residues in proteins without understanding the underlying biophysical properties giving rise to such coevolutionary dynamics. Detailed (atomistic) simulations are prohibitively expensive. At the same time reduced molecular models are an efficient way to determine the reduced dynamics around the native state. The combination of sequence based approaches with such reduced models is therefore a promising approach to annotate evolutionary sequence changes.</p> <p>Results</p> <p>With the <monospace>R</monospace> package <monospace>BioPhysConnectoR</monospace> we provide a framework to connect the information theoretical domain of biomolecular sequences to biophysical properties of the encoded molecules - derived from reduced molecular models. To this end we have integrated several fragmented ideas into one single package ready to be used in connection with additional statistical routines in <monospace>R</monospace>. Additionally, the package leverages the power of modern multi-core architectures to reduce turn-around times in evolutionary and biomolecular design studies. Our package is a first step to achieve the above mentioned annotation of coevolution by reduced dynamics around the native state of proteins.</p> <p>Conclusions</p> <p><monospace>BioPhysConnectoR</monospace> is implemented as an <monospace>R</monospace> package and distributed under GPL 2 license. It allows for efficient and perfectly parallelized functional annotation of coevolution found at the sequence level.</p

Biomolecular Correlation in Physical and Sequence Space

Investigating correlations is the key to understanding the nature of biological systems. In general, correlations describe the relationship between data sets or specific characteristics of data. To investigate correlations among and within biomolecules we discussed two complementary approaches to advance the understanding of evolution. Mutational dynamics can mainly be seen in the space of sequences whereas the altered phenotype is selected in the biophysical realm. By mutual information, an information-theoretical measure, we can identify potentially coevolving nucleotide or amino acid positions from a set of sequences combined into a multiple sequence alignment. In the biophysical realm, the mechanics of a biomolecule, which is important for its structure and function, is examined by various methods. Since molecular dynamics simulations and normal mode analysis are computationally expensive approaches, coarse-grained protein representations such as elastic network models have been developed. We used such protein models, particularly the Gaussian and the anisotropic network model, to jugde the importance of single residues or amino acid contacts on the dynamics of the biomolecule or distinct portions. In this thesis, we applied this analysis to distinct sets of hammerhead ribozyme sequences of type I and III to reveal coevolutionary hot spots shared among the different sequences. We observed a weaker coevolution of ribozymes originating from prokaryotes and eukaryotes compared to viroid sequences. Additionally, we obtained signals between helical stems I and II which is well-known from experiments. However, we noticed a coevolutionary connection between stems I and III throughout all sets of sequences that have not been reported yet. We applied an established protocol to a structural model of the small viral potassium channel Kcv, where we deleted single contacts and measured the resulting change in dynamics using the Frobenius norm. Here, we observed a mechanical connection of N- and C-terminal residues, whereas the selectivity filter seems almost mechanically uncoupled to the rest of the channel. A similar study was performed for the acetylcholinesterase as well where we additionally correlated mechanical changes with coevolutionary information. By means of coarse-grained protein models, we proposed a protocol for the Kcv to identify the transition from a functional to a non-functional channel upon N-terminal deletions. Furthermore, we utilized reduced molecular models to derive amino acid specific interaction constants directly from a set of protein structures obtained from e.g. from molecular dynamics simulations. To this end, we examined the performance of three approaches to retrieve the input parameters from an artificially constructed system. As it turned out, semidefinite programming is an efficient method for this task and was employed for a realistic application as well

«Jeg har ikke nok kompetanse til å tilrettelegge for elevens sosiale behov». En kvalitativ studie om hvordan en lærer tilrettelegger for sosial inkludering av en elev med autismespekterforstyrrelse i friminuttene.

Problemstilling og forskningsspørsmål: Denne studien har til hensikt å belyse hvordan en lærer tilrettelegger for sosial inkludering av en elev med ASF. Studiens problemstilling lyder som følger: Hvordan tilrettelegger en lærer på 4. trinn for sosial inkludering av en elev med ASF i friminuttene? For å belyse problemstillingen har jeg utformet to forskningsspørsmål: Hva slags kompetanse har læreren om ASF? Og: Hvilke behov fremkommer av læreren ved tilrettelegging for sosial inkludering av eleven med ASF i friminuttene? Metode og materiale: Jeg har anvendt et kvalitativt forskningsdesign og studien er utformet som en case-studie. Mine informanter består av en kontaktlærer på 4. trinn, en elev med ASF tilhørende kontaktlærerens klasse og en assistent på skolen. Jeg har benyttet meg av intervju og observasjon som metode, og dette utgjør studiens datainnsamling. Datamaterialet ble videre kodet og kategorisert i dataprogrammet NVivo 12, og analysert i tråd med studiens vitenskapsfilosofiske forankring: fenomenologi. Resultater og konklusjoner: Læreren i mitt utvalg formidler flere tiltak hen har utformet til eleven for å tilrettelegge for sosial inkludering i friminuttene. Samlet sett omhandler tiltakene enkle påminnelser til eleven, innsetting av assistent og å sikre at tiltakene foregår på elevens premisser. Ifølge læreren har bruk av assistent ført til økt trivsel hos eleven. Til tross for tiltakene tilbringer eleven mye av tiden i friminuttene alene. Funnene i denne studien indikerer at tiltak som fadderprogram og andre tiltak hvor eleven samhandler med én annen medelev er hensiktsmessig for elevens sosiale inkludering, men eleven har utfordringer med å være sosialt inkludert i grupper. Her ser det ut til at barrierer som sosial kommunikasjon, turtaking og mentalisering blir gjeldende. Hva gjelder lærerens kompetanse støtter studiens funn oppunder tidligere forskning (Bartonek et al., 2018; Hart &amp; More, 2013; Hess et al., 2008; Morrier et al., 2011; Sanz-Cervera et al., 2017; Šegota et al., 2020) som konkluderer med et behov for mer kompetanse på ASF og hvordan tilrettelegge for denne elevgruppen. Manglende kompetanse bunner i lite fokus på diagnosen under lærerutdanningen samt manglende kurs eller ytterligere informasjon om ASF som praktiserende lærer. Læreren belyser et behov for mer ressurser til skolen i form av lærere/assistenter og det fremkommer en tydelig sårbarhet hos læreren som følge av manglende ressurser og manglende kompetanse

Distance-dependent classification of amino acids by information theory

Reduced amino acid alphabets are useful to understand molecular evolution as they reveal basal, shared properties of amino acids, which the structures and functions of proteins rely on. Several previous studies derived such reduced alphabets and linked them to the origin of life and biotechnological applications. However, all this previous work presupposes that only direct contacts of amino acids in native protein structures are relevant. We show in this work, using information-theoretical measures, that an appropriate alphabet reduction scheme is in fact a function of the maximum distance amino acids interact at. Although for small distances our results agree with previous ones, we show how long-range interactions change the overall picture and prompt for a revised understanding of the protein design process