Self-assembling and molecular folding are ubiquitous in Nature: they drive the organization of systems ranging from living creatures to DNA molecules. Elucidating the complex dynamics underlying these phenomena is of crucial importance. However, a tool for the analysis of the various phenomena involved in protein/peptide aggregation is still missing. Here, an innovative software is developed and validated for the identification and visualization of b-structuring and b-sheet formation in both simulated systems and crystal structures of proteins and peptides. The novel software suite, dubbed Morphoscanner, is designed to identify and intuitively represent b-structuring and b-sheet formation during molecular dynamics trajectories, paying attention to temporary strand-strand alignment, suboligomer formation and evolution of local order. Self-assembling peptides (SAPs) constitute a promising class of biomaterials and an interesting model to study the spontaneous assembly of molecular systems in vitro. With the help of coarse-grained molecular dynamics the self-assembling of diverse SAPs is simulated into molten aggregates. When applied to these systems, Morphoscanner highlights different b-structuring schemes and kinetics related to SAP sequences. It is demonstrated that Morphoscanner is a novel versatile tool designed to probe the aggregation dynamics of self-assembling systems, adaptable to the analysis of differently coarsened simulations of a variety of biomolecules.

Saracino, G., Fontana, F., Jekhmane, S., Silva, J., Weingarth, M., Gelain, F. (2018). Elucidating Self-Assembling Peptide Aggregation via Morphoscanner: A New Tool for Protein-Peptide Structural Characterization. ADVANCED SCIENCE, 5(8) [10.1002/advs.201800471].

Elucidating Self-Assembling Peptide Aggregation via Morphoscanner: A New Tool for Protein-Peptide Structural Characterization

Saracino, GAA;Fontana, F;Gelain, F
2018

Abstract

Self-assembling and molecular folding are ubiquitous in Nature: they drive the organization of systems ranging from living creatures to DNA molecules. Elucidating the complex dynamics underlying these phenomena is of crucial importance. However, a tool for the analysis of the various phenomena involved in protein/peptide aggregation is still missing. Here, an innovative software is developed and validated for the identification and visualization of b-structuring and b-sheet formation in both simulated systems and crystal structures of proteins and peptides. The novel software suite, dubbed Morphoscanner, is designed to identify and intuitively represent b-structuring and b-sheet formation during molecular dynamics trajectories, paying attention to temporary strand-strand alignment, suboligomer formation and evolution of local order. Self-assembling peptides (SAPs) constitute a promising class of biomaterials and an interesting model to study the spontaneous assembly of molecular systems in vitro. With the help of coarse-grained molecular dynamics the self-assembling of diverse SAPs is simulated into molten aggregates. When applied to these systems, Morphoscanner highlights different b-structuring schemes and kinetics related to SAP sequences. It is demonstrated that Morphoscanner is a novel versatile tool designed to probe the aggregation dynamics of self-assembling systems, adaptable to the analysis of differently coarsened simulations of a variety of biomolecules.
Articolo in rivista - Articolo scientifico
coarse-grained molecular dynamics; multilayer graph theory; pattern recognition; self-assembling peptides; β-structures;
coarse-grained molecular dynamics; multilayer graph theory; pattern recognition; self-assembling peptides; β-structures; Medicine (miscellaneous); Chemical Engineering (all); Materials Science (all); Biochemistry, Genetics and Molecular Biology (miscellaneous); Engineering (all); Physics and Astronomy (all)
English
2018
5
8
1800471
reserved
Saracino, G., Fontana, F., Jekhmane, S., Silva, J., Weingarth, M., Gelain, F. (2018). Elucidating Self-Assembling Peptide Aggregation via Morphoscanner: A New Tool for Protein-Peptide Structural Characterization. ADVANCED SCIENCE, 5(8) [10.1002/advs.201800471].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/205633
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