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Simone Orioli

Researcher at University of Copenhagen

Publications -  24
Citations -  672

Simone Orioli is an academic researcher from University of Copenhagen. The author has contributed to research in topics: Folding (chemistry) & Protein folding. The author has an hindex of 10, co-authored 23 publications receiving 398 citations. Previous affiliations of Simone Orioli include University of Trento.

Papers
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Journal ArticleDOI

Allostery in Its Many Disguises: From Theory to Applications

Shoshana J. Wodak, +41 more
- 02 Apr 2019 - 
TL;DR: An overview of the progress and remaining limitations in the understanding of the mechanistic foundations of allostery gained from computational and experimental analyses of real protein systems and model systems is provided.
Journal ArticleDOI

Full atomistic model of prion structure and conversion.

TL;DR: This study provides the most updated, experimentally-driven and physically-coherent model of PrPSc, together with an unprecedented reconstruction of the mechanism underlying the self-catalytic propagation of prions.
Book ChapterDOI

How to learn from inconsistencies: Integrating molecular simulations with experimental data.

TL;DR: This chapter provides an overview of some of the core ideas behind methods that were developed to improve the consistency between experimental information and numerical predictions and distinguishes between situations where experiments are used to refine the understanding and models of specific systems, and situations where tests are used more generally to refine transferable models.
Journal ArticleDOI

Atomic Detail of Protein Folding Revealed by an Ab Initio Reappraisal of Circular Dichroism.

TL;DR: It is demonstrated that the combination of atomistic molecular dynamics simulations of the folding pathways with a quantum chemical evaluation of the excitonic spectra provides the missing key for the folding of canine milk lysozyme protein.
Posted Content

How to learn from inconsistencies: Integrating molecular simulations with experimental data

TL;DR: In this article, the authors provide an overview of some of the core ideas behind methods that were developed to improve the consistency between experimental information and numerical predictions, and distinguish between situations where experiments are used to refine our understanding and models of specific systems, and situations where simulations are used more generally to refine transferable models.