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6 results for “aggregation kinetics”

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zenodo40/100

Dataset 2 for: Multi-eGO: an in-silico lens to look into protein aggregation kinetics at atomic resolution

<p><strong>Dataset</strong></p> <p>Molecular dynamics simulation trajectories of TTR peptide&nbsp;aggregation kinetics:</p> <ul> <li>multi-eGO-XXmM-Y: aggregation kinetics simulations of TTR using the multi-eGO force field at XXmM concentration replicate Y.</li> </ul>

opencc-by-4.0Feb 2022View details →
dryad36/100

Staphylococcus aureus phenol soluble modulin aggregation kinetics

<p><span>The infective ability of the </span>opportunistic pathogen <i><span>S</span>taphylococcus<span> aureus</span></i><span>, recognized as the most frequent cause of biofilm-associated infections, is associated with biofilm mediated resistance to host immune response. Phenol-soluble modulins (PSM) comprise the structural scaffold of <i>S. aureus</i> biofilms through self-assembly into functional amyloids, but the role of individual PSMs during biofilm formation remains poorly understood and the </span>molecular pathways of PSM self-assembly have yet to be identified<span>. Here, we demonstrate high degree of cooperation between individual PSMs during functional amyloid formation. PSMα3 initiates the aggregation, forming unstable aggregates capable of seeding other PSMs resulting in stable amyloid structures. Using chemical kinetics we dissect the molecular mechanism of aggregation of individual PSMs showing that PSMα1, PSMα3 and PSM</span><span>β</span><span>1 display secondary nucleation whereas PSM</span><span>β</span><span>2 aggregates through primary nucleation and elongation. Our findings suggest that the various PSMs have evolved to ensure fast and efficient biofilm formation through cooperation between individual peptides.</span></p>

opencc-zeroDec 2020View details →
dryad36/100

Staphylococcus aureus phenol soluble modulin aggregation kinetics

Open the record for dataset details and reuse information.

publicDec 2020View details →
zenodo32/100

Dataset 1 for: Multi-eGO: an in-silico lens to look into protein aggregation kinetics at atomic resolution

<p><strong>Dataset</strong></p> <p>Molecular dynamics simulation trajectories of TTR peptide monomers and aggregation kinetics:</p> <ul> <li>Amber99sb_disp: TTR monomer in explicit solvent using amber99disp force field.</li> <li>multi-GO-monomer: TTR monomer simulation using the multi-GO force field.</li> <li>multi-eGO-monomer: TTR monomer simulation using the multi-eGO ensemble force field.</li> <li>multi-eGO-XXmM-Y: aggregation kinetics simulations of TTR using the multi-eGO force field at XXmM concentration replicate Y.</li> <li>.ipynb files: analysis script employed for the aggregation kinetics simulations.</li> <li>TTR aggregation kinetics movies.</li> </ul>

opencc-by-4.0Feb 2022View details →
zenodo32/100

Dataset 3 for: Multi-eGO: an in-silico lens to look into protein aggregation kinetics at atomic resolution

<p><strong>Dataset</strong></p> <p>Multi-GO Molecular dynamics simulation trajectories of TTR peptide and aggregation kinetics; Multi-<em>e</em>GO oligomer&nbsp;structures and trajectories:</p> <ul> <li>multi-GO-XXmM: aggregation kinetics simulations of TTR using the multi-eGO force field at XXmM concentration.</li> <li>TTR structures and trajectories of oligomers from dimers to decamers.</li> </ul>

opencc-by-4.0Apr 2022View details →
zenodo12/100

Multi-eGO: An in silico lens to look into protein aggregation kinetics at atomic resolution

<p>Scalone E, Broggini L, Visentin C, Erba D, Bačić Toplek F, Peqini K, Pellegrino S, Ricagno S, Paissoni C, Camilloni C. Multi-eGO: An in silico lens to look into protein aggregation kinetics at atomic resolution. Proc Natl Acad Sci U S A. 2022 Jun 28;119(26):e2203181119. doi: 10.1073/pnas.2203181119. Epub 2022 Jun 23. PMID: 35737839; PMCID: PMC9245614.</p> <p>Abstract</p> <p>Protein aggregation into amyloid fibrils is the archetype of aberrant biomolecular self-assembly processes, with more than 50 associated diseases that are mostly uncurable. Understanding aggregation mechanisms is thus of fundamental importance and goes in parallel with the structural characterization of the transient oligomers formed during the process. Oligomers have been proven elusive to high-resolution structural techniques, while the large sizes and long time scales, typical of aggregation processes, have limited the use of computational methods to date. To surmount these limitations, we here present multi-<em>e</em>GO, an atomistic, hybrid structure-based model which, leveraging the knowledge of monomers conformational dynamics and of fibril structures, efficiently captures the essential structural and kinetics aspects of protein aggregation. Multi-<em>e</em>GO molecular dynamics simulations can describe the aggregation kinetics of thousands of monomers. The concentration dependence of the simulated kinetics, as well as the structural features of the resulting fibrils, are in qualitative agreement with in vitro experiments carried out on an amyloidogenic peptide from Transthyretin, a protein responsible for one of the most common cardiac amyloidoses. Multi-<em>e</em>GO simulations allow the formation of primary nuclei in a sea of transient lower-order oligomers to be observed over time and at atomic resolution, following their growth and the subsequent secondary nucleation events, until the maturation of multiple fibrils is achieved. Multi-<em>e</em>GO, combined with the many experimental techniques deployed to study protein aggregation, can provide the structural basis needed to advance the design of molecules targeting amyloidogenic diseases.</p>

restrictedJan 2023View details →

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