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.
| Original language | English |
|---|---|
| Article number | 1800471 |
| Journal | Advanced Science |
| Volume | 5 |
| Issue number | 8 |
| DOIs | |
| Publication status | Published - Aug 1 2018 |
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Keywords
- coarse-grained molecular dynamics
- multilayer graph theory
- pattern recognition
- self-assembling peptides
- β-structures
ASJC Scopus subject areas
- Medicine (miscellaneous)
- Chemical Engineering(all)
- Materials Science(all)
- Biochemistry, Genetics and Molecular Biology (miscellaneous)
- Engineering(all)
- Physics and Astronomy(all)
Cite this
Elucidating Self-Assembling Peptide Aggregation via Morphoscanner : A New Tool for Protein-Peptide Structural Characterization. / Saracino, Gloria A.A.; Fontana, Federico; Jekhmane, Shehrazade; Silva, João Medeiros; Weingarth, Markus; Gelain, Fabrizio.
In: Advanced Science, Vol. 5, No. 8, 1800471, 01.08.2018.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Elucidating Self-Assembling Peptide Aggregation via Morphoscanner
T2 - A New Tool for Protein-Peptide Structural Characterization
AU - Saracino, Gloria A.A.
AU - Fontana, Federico
AU - Jekhmane, Shehrazade
AU - Silva, João Medeiros
AU - Weingarth, Markus
AU - Gelain, Fabrizio
PY - 2018/8/1
Y1 - 2018/8/1
N2 - 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.
AB - 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.
KW - coarse-grained molecular dynamics
KW - multilayer graph theory
KW - pattern recognition
KW - self-assembling peptides
KW - β-structures
UR - http://www.scopus.com/inward/record.url?scp=85051744086&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85051744086&partnerID=8YFLogxK
U2 - 10.1002/advs.201800471
DO - 10.1002/advs.201800471
M3 - Article
AN - SCOPUS:85051744086
VL - 5
JO - Advanced Science
JF - Advanced Science
SN - 2198-3844
IS - 8
M1 - 1800471
ER -