1,720,969 research outputs found
Insights Into the Molecular Mechanisms Driving Rare Neurodegenerative Diseases and Therapeutic Strategies Aided By In Silico Modelling
L'abstract è presente nell'allegato / the abstract is in the attachmen
Prediction of Protein–Protein Interactions Between Alsin DH/PH and Rac1 and Resulting Protein Dynamics
In silico investigation of Alsin RLD conformational dynamics and phosphoinositides binding mechanism
Alsin is a protein known for its major role in neuronal homeostasis and whose mutation is associated with early-onset neurodegenerative diseases. It has been shown that its relocalization from the cytoplasm to the cell membrane is crucial to induce early endosomes maturation. In particular, evidences suggest that the N-terminal regulator of chromosome condensation 1 like domain (RLD) is necessary for membrane association thanks to its affinity to phosphoinositides, membrane lipids involved in the regulation of several signaling processes. Interestingly, this domain showed affinity towards phosphatidylinositol 3-phosphate [PI(3)P], which is highly expressed in endosomes membrane. However, Alsin structure has not been experimentally resolved yet and molecular mechanisms associated with its biological functions are mostly unknown. In this work, Alsin RLD has been investigated through computational molecular modeling techniques to analyze its conformational dynamics and obtain a representative 3D model of this domain. Moreover, a putative phosphoinositide binding site has been proposed and PI(3)P interaction mechanism studied. Results highlight the substantial conformational stability of Alsin RLD secondary structure and suggest the role of one highly flexible region in the phosphoinositides selectivity of this domain
Going Beyond Counting First Authors in Author Co-citation Analysis
The 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
Explainable Machine Learning and Deep Learning Models for Predicting TAS2R-Bitter Molecule Interactions
This work aims to develop explainable models to predict the interactions between bitter molecules and TAS2Rs via traditional machine-learning and deep-learning methods starting from experimentally validated data. Bitterness is one of the five basic taste modalities that can be perceived by humans and other mammals. It is mediated by a family of G protein-coupled receptors (GPCRs), namely taste receptor type 2 (TAS2R) or bitter taste receptors. Furthermore, TAS2Rs participate in numerous functions beyond the gustatory system and have implications for various diseases due to their expression in various extra-oral tissues. For this reason, predicting the specific ligand-TAS2Rs interactions can be useful not only in the field of taste perception but also in the broader context of drug design. Considering that in-vitro screening of potential TAS2R ligands is expensive and time-consuming, machine learning (ML) and deep learning (DL) emerged as powerful tools to assist in the selection of ligands and targets for experimental studies and enhance our understanding of bitter receptor roles. In this context, ML and DL models developed in this work are both characterized by high performance and easy applicability. Furthermore, they can be synergistically integrated to enhance model explainability and facilitate the interpretation of results. Hence, the presented models promote a comprehensive understanding of the molecular characteristics of bitter compounds and the design of novel bitterants tailored to target specific TAS2Rs of interest
Elucidating molecular connetion between IAHSP onset and Alsin protein by means of Homology Modelling and Molecular Dynamics
Mechanical communication within the microtubule through network‐based analysis of tubulin dynamics
Conformational Dynamics and Molecular Characterization of Alsin MORN Monomer and Dimeric Assemblies
Despite the ubiquity of membrane occupation recognition nexus (MORN) motifs across diverse species in both eukaryotic and prokaryotic organisms, these protein domains remain poorly characterized. Their significance is underscored in the context of the Alsin protein, implicated in the debilitating condition known as infantile-onset ascending hereditary spastic paralysis (IAHSP). Recent investigations have proposed that mutations within the Alsin MORN domain disrupt proper protein assembly, precluding the formation of the requisite tetrameric configuration essential for the protein's inherent biological activity. However, a comprehensive understanding of the relationship between the biological functions of Alsin and its three-dimensional molecular structure is hindered by the lack of available experimental structures. In this study, we employed and compared several protein structure prediction algorithms to identify a three-dimensional structure for the putative MORN of Alsin. Furthermore, inspired by experimental pieces of evidence from previous studies, we employed the developed models to predict and investigate two homo-dimeric assemblies, characterizing their stability. This study's insights into the three-dimensional structure of the Alsin MORN domain and the stability dynamics of its homo-dimeric assemblies suggest an antiparallel linear configuration stabilized by a noncovalent interaction network
Variations on the Author
“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
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