1,721,054 research outputs found
VarI-COSI 2018: A forum for research advances in variant interpretation and diagnostics
Full text linkA Minimal Model of Three-State Folding Dynamics of Helical Proteins
No full textA diffusion-collision-like model is proposed for helical proteins with three-state folding dynamics. The model
generalizes a previous scheme based on the dynamics of putatively essential parts of the protein (foldons)
that was successfully tested on proteins with two-state folding. We show that the extended model, unlike the
original one, allows satisfactory calculation of the folding rate and reconstruction of the salient steps of the
folding pathway of two proteins with three-state folding (Im7 and p16). The dramatic reduction of variables
achieved by focusing on the foldons makes our model a good candidate for a minimal description of the
folding process also for three-state folders. Finally, the applicability of the foldon diffusion-collision model
to two-state and three-state folders suggests that different folding mechanisms are amenable to conceptually
homogeneous descriptions. The implications for a unification of the variety of folding theories so far proposed
for helical proteins are discussed in the final discussion
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
ThermoScan: Semi-automatic Identification of Protein Stability Data From PubMed
Full text linkDuring the last years, the increasing number of DNA sequencing and protein mutagenesis studies has generated a large amount of variation data published in the biomedical literature. The collection of such data has been essential for the development and assessment of tools predicting the impact of protein variants at functional and structural levels. Nevertheless, the collection of manually curated data from literature is a highly time consuming and costly process that requires domain experts. In particular, the development of methods for predicting the effect of amino acid variants on protein stability relies on the thermodynamic data extracted from literature. In the past, such data were deposited in the ProTherm database, which however is no longer maintained since 2013. For facilitating the collection of protein thermodynamic data from literature, we developed the semi-automatic tool ThermoScan. ThermoScan is a text mining approach for the identification of relevant thermodynamic data on protein stability from full-text articles. The method relies on a regular expression searching for groups of words, including the most common conceptual words appearing in experimental studies on protein stability, several thermodynamic variables, and their units of measure. ThermoScan analyzes full-text articles from the PubMed Central Open Access subset and calculates an empiric score that allows the identification of manuscripts reporting thermodynamic data on protein stability. The method was optimized on a set of publications included in the ProTherm database, and tested on a new curated set of articles, manually selected for presence of thermodynamic data. The results show that ThermoScan returns accurate predictions and outperforms recently developed text-mining algorithms based on the analysis of publication abstracts. Availability: The ThermoScan server is freely accessible online at https://folding.biofold.org/thermoscan. The ThermoScan python code and the Google Chrome extension for submitting visualized PMC web pages to the ThermoScan server are available at https://github.com/biofold/ThermoScan
Diffusion-collision of foldons elucidates the kinetic effects of point mutations and suggests control strategies of the folding process of helical proteins
Full text linkIn this article we use mutation
studies as a benchmark for a minimal model of the
folding process of helical proteins. The model ascribes
a pivotal role to the collisional dynamics of a
few crucial residues (foldons) and predicts the folding
rates by exploiting information drawn from the
protein sequence. We show that our model rationalizes
the effects of point mutations on the kinetics of
folding. The folding times of two proteins and their
mutants are predicted. Stability and location of
foldons have a critical role as the determinants of
protein folding. This allows us to elucidate two main
mechanisms for the kinetic effects of mutations.
First, it turns out that the mutations eliciting the
most notable effects alter protein stability through
stabilization or destabilization of the foldons. Secondly,
the folding rate is affected via a modification
of the foldon topology by those mutations that lead
to the birth or death of foldons. The few mispredicted
folding rates of some mutants hint at the
limits of the current version of the folding model
proposed in the present article. The performance of
our folding model declines in case the mutated
residues are subject to strong long-range forces.
That foldons are the critical targets of mutation
studies has notable implications for design strategies
and is of particular interest to address the issue
of the kinetic regulation of single proteins in the
general context of the overall dynamics of the interactome
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Network-based strategies for protein characterization
No full textProtein structure characterization is fundamental to understand protein properties, such as folding process and protein resistance to thermal stress, up to unveiling organism pathologies (e.g., prion disease). In this chapter, we provide an overview on how the spectral properties of the networks reconstructed from the Protein Contact Map (PCM) can be used to generate informative observables. As a specific case study, we apply two different network approaches to an example protein dataset, for the aim of discriminating protein folding state, and for the reconstruction of protein 3D structure
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