1,721,129 research outputs found
Searching the Optimal Folding Routes of a Complex Lasso Protein
Full text linkUnderstanding how polypeptides can efficiently and reproducibly attain a self-entangled conformation is a compelling biophysical challenge that might shed new light on our general knowledge of protein folding. Complex lassos, namely self-entangled protein structures characterized by a covalent loop sealed by a cysteine bridge, represent an ideal test system in the framework of entangled folding. Indeed, because cysteine bridges form in oxidizing conditions, they can be used as on/off switches of the structure topology to investigate the role played by the backbone entanglement in the process. In this work, we have used molecular dynamics to simulate the folding of a complex lasso glycoprotein, granulocyte-macrophage colony-stimulating factor, modeling both reducing and oxidizing conditions. Together with a well-established Gō-like description, we have employed the elastic folder model, a coarse-grained, minimalistic representation of the polypeptide chain driven by a structure-based angular potential. The purpose of this study is to assess the kinetically optimal pathways in relation to the formation of the native topology. To this end, we have implemented an evolutionary strategy that tunes the elastic folder model potentials to maximize the folding probability within the early stages of the dynamics. The resulting protein model is capable of folding with high success rate, avoiding the kinetic traps that hamper the efficient folding in the other tested models. Employing specifically designed topological descriptors, we could observe that the selected folding routes avoid the topological bottleneck by locking the cysteine bridge after the topology is formed. These results provide valuable insights on the selection of mechanisms in self-entangled protein folding while, at the same time, the proposed methodology can complement the usage of established minimalistic models and draw useful guidelines for more detailed simulations
Computational methods in the study of self-entangled proteins: a critical appraisal
No full textThe existence of self-entangled proteins, the native structure of which features a complex topology, unveils puzzling, and thus fascinating, aspects of protein biology and evolution. The discovery that a polypeptide chain can encode the capability to self-entangle in an efficient and reproducible way during folding, has raised many questions, regarding the possible function of these knots, their conservation along evolution, and their role in the folding paradigm. Understanding the function and origin of these entanglements would lead to deep implications in protein science, and this has stimulated the scientific community to investigate self-entangled proteins for decades by now. In this endeavour, advanced experimental techniques are more and more supported by computational approaches, that can provide theoretical guidelines for the interpretation of experimental results, and for the effective design of new experiments. In this review we provide an introduction to the computational study of self-entangled proteins, focusing in particular on the methodological developments related to this research field. A comprehensive collection of techniques is gathered, ranging from knot theory algorithms, that allow detection and classification of protein topology, to Monte Carlo or molecular dynamics strategies, that constitute crucial instruments for investigating thermodynamics and kinetics of this class of proteins
un esempio di riconversione di gallerie minerarie a scopo turistico e scientifico-sperimentale: le miniere dei Pian dei Resinelli.
No full textL'approccio olistico del Progetto di Vita per un "Dopo di Noi" durante Noi
No full textIl “progetto di vita” rappresenta il cuore della Legge 112/16 e, data la sua significatività, questo capitolo è dedicato a inquadrare il tema del “progetto di vita” attraverso una approfondita literature review. L’indagine ha lo scopo di definire le caratteristiche del “progetto di vita”, le strategie che guidano la sua formulazione e gli indicatori che lo qualificano come elemento di garanzia per la dignità della persona e per il raggiungimento della qualità della sua vita. Lo studio è stato condotto all’interno del percorso di ricerca dottorale attivato dal Comitato Officina Dopo di Noi. Riporta le riflessioni emerse nel corso dell’esperienza condotta nel gruppo di lavoro interdisciplinare istituito dall’Istituto Superiore di Sanità (ISS) su mandato del Ministero della Salute nell’ambito del progetto Fondo Autismo, per la definizione del “progetto di vita” della persona nello spettro autistico basato sui costrutti di «Quality of Life» e sulle diverse necessità di supporto, livello di funzionamento adattivo ed eventuali disturbi associati. Questo lavoro si avvale della supervisione scientifica di Maria Luisa Scattoni, ricercatrice presso l’ISS, coordinatrice dell’Osservatorio Nazionale Autismo (OssNA) e del Network NIDA (Network italiano per il riconoscimento precoce dei disturbi dello spettro autistico) e, dal 2017, responsabile scientifico del progetto per l’utilizzo del “Fondo per la cura dei soggetti con disturbo dello spettro autistico” finanziato dal Ministero della Salute. L’esito di questo lavoro ha condotto alla pubblicazione inedita della voce “progetto di vita” su Wikipedia, grazie alla quinta edizione del corso “Science, Technology, Society and Wikipedia”, organizzato dalla Scuola di Dottorato del Politecnico di Milano
Protein self-entanglement modulates successful folding to the native state: A multi-scale modeling study
Full text linkThe computer-aided investigation of protein folding has greatly benefited from coarse-grained models, that is, simplified representations at a resolution level lower than atomistic, providing access to qualitative and quantitative details of the folding process that would be hardly attainable, via all-atom descriptions, for medium to long molecules. Nonetheless, the effectiveness of low-resolution models is itself hampered by the presence, in a small but significant number of proteins, of nontrivial topological self-entanglements. Features such as native state knots or slipknots introduce conformational bottlenecks, affecting the probability to fold into the correct conformation; this limitation is particularly severe in the context of coarse-grained models. In this work, we tackle the relationship between folding probability, protein folding pathway, and protein topology in a set of proteins with a nontrivial degree of topological complexity. To avoid or mitigate the risk of incurring in kinetic traps, we make use of the elastic folder model, a coarse-grained model based on angular potentials optimized toward successful folding via a genetic procedure. This light-weight representation allows us to estimate in silico folding probabilities, which we find to anti-correlate with a measure of topological complexity as well as to correlate remarkably well with experimental measurements of the folding rate. These results strengthen the hypothesis that the topological complexity of the native state decreases the folding probability and that the force-field optimization mimics the evolutionary process these proteins have undergone to avoid kinetic traps
Supramolecular cooperativity through the lens of enhanced sampling molecular dynamics
Full text linkSupramolecular polymers are dynamic aggregates whose properties arise from their constitutive bonds, based on reversible, non-covalent interactions. A central aspect in the design and function of these materials is the cooperativity of polymerization, by which the addition of monomers becomes increasingly favorable as the polymer grows. Cooperativity strongly influences both the structure and collective behavior of supramolecular materials, with significant implications for their properties. Understanding the origins and consequences of cooperativity is crucial for the rational design of new functional supramolecular polymer systems. Herein, we systematically explore the cooperativity of supramolecular polymer systems via Molecular Dynamics simulations, powered by On-the-fly Probability Enhanced Sampling, to accurately characterize the free energy landscape associated with polymerization. We validate our approach via ad hoc, minimalistic coarse-grained models of cooperative and non-cooperative self-assembling monomers. We then apply our analysis to ureidopyrimidinone (UPy) supramolecular polymers, widely used in biohydrogel design. Our work provides detailed insights into the UPy polymerization process and how cooperativity can emerge from the hierarchical character of its supramolecular structure. The results underscore the importance of an extensive molecular simulation approach to obtain a quantitative characterization of the self-assembly thermodynamics, which is crucial to guide the rational development of next-generation supramolecular materials
Chemical potential calculations in dense liquids using metadynamics
No full textThe calculation of chemical potential has traditionally been a challenge in atomistic simulations. One of the most used approaches is Widom's insertion method in which the chemical potential is calculated by periodically attempting to insert an extra particle in the system. In dense systems this method fails since the insertion probability is very low. In this paper we show that in a homogeneous fluid the insertion probability can be increased using metadynamics. We test our method on a supercooled high density binary Lennard-Jones fluid. We find that we can obtain efficiently converged results even when Widom's method fails
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
- …
