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Eliasson, Sondre Hilmar Hopen; de Giovanetti, Marinella; Bore, Sigbjørn Løland; Bortoli, Marco; Cascella, Michele & Eisenstein, Odile
(2023).
Machine Learned Potential for Organolithium in THF.
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Eliasson, Sondre Hilmar Hopen; de Giovanetti, Marinella; Bore, Sigbjørn Løland; Bortoli, Marco & Cascella, Michele
(2023).
Machine Learned Potential for Organolithium Compounds in THF. .
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Cascella, Michele
(2023).
Multiscale approaches for bio/soft matter: investigating self-assembly and dynamics of lipid and surfactants.
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Segura-Pena, Dario; Hovet, Oda; Dawicki-McKenna, Jennine; Wøien, Stine Malene Hansen; Black, Ben E. & Cascella, Michele
[Show all 7 contributors for this article]
(2022).
The structural basis of the multi-step allosteric activation of Aurora B kinase.
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Segura-Pena, Dario; Hovet, Oda; Dawicki-McKenna, Jennine; Wøien, Stine Malene Hansen; Black, Ben E. & Cascella, Michele
[Show all 7 contributors for this article]
(2022).
The structural basis of the multi-step allosteric activation of Aurora B kinase.
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Segura-Pena, Dario; Hovet, Oda; Dawicki-McKenna, Jennine; Wøien, Stine Malene Hansen; Black, Ben E. & Cascella, Michele
[Show all 7 contributors for this article]
(2022).
HDX and MD as tools to elucidate Aurora B kinase activation mechanism .
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Segura-Pena, Dario; Hovet, Oda; Dawicki-McKenna, Jennine; Wøien, Stine Malene Hansen; Black, Ben E. & Cascella, Michele
[Show all 7 contributors for this article]
(2022).
The structural basis of the multi-step allosteric activation of Aurora B kinase.
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Segura-Pena, Dario; Hovet, Oda; Dawicki-McKenna, Jennine; Wøien, Stine Malene Hansen; Black, Ben E. & Cascella, Michele
[Show all 7 contributors for this article]
(2022).
Phosphorylation structurally organizes the [Aurora B/IN-box] complex and introduces a synchronised internal motion of the enzyme resulting in activation .
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Sekulic, Nikolina; Segura-Pena, Dario; Hovet, Oda; Dawicki-McKenna, Jennine; Wøien, Stine Malene Hansen & Black, Ben E.
[Show all 7 contributors for this article]
(2022).
Aurora B activation requires synchronized internal motion initiated by IN-box phosphorylation .
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Cascella, Michele
(2022).
The Grignard reaction - solving a century old problem by molecular simulations.
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Eisenstein, Odile & Cascella, Michele
(2021).
Grignard reagent and Grignard reaction: Computational approach of a chemical puzzle.
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Lund, Reidar & Cascella, Michele
(2021).
Aggregation kinetics and photodynamics of photocontrollable surfactant AzoTMA: a molecular dynamics study.
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Cascella, Michele
(2020).
Recent advances in hybrid particle field: toward biological systems.
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Cascella, Michele
(2019).
Simulating biological systems coupling particles and fields with molecular dynamics.
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Cascella, Michele
(2019).
Simulating biological systems coupling particles and fields with molecular dynamics.
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Cascella, Michele
(2019).
Simulating biological systems coupling particles and fields with molecular dynamics .
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Cascella, Michele
(2019).
Simulating biological soft systems coupling particles and fields with molecular dynamics.
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Cascella, Michele
(2019).
Multiscale simulations of bio/soft-matter using particles and fields.
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Cascella, Michele
(2019).
Simulating Biological Systems Coupling Particles and Fields with Molecular Dynamics.
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Cascella, Michele
(2018).
Toward Molecular-Resolved Mesoscale Simulations of Soft Matter.
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Cascella, Michele
(2018).
Hybrid particle-field molecular dynamics: state of the art and challenges.
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Cascella, Michele
(2018).
Hybrid particle field models for peptide chains .
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Cascella, Michele
(2018).
Entropy-driven polymorphism in micellar aggregates of a charged surfactant — a multi-scale study.
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Cascella, Michele
(2018).
Coarse grained models of protein and peptides using particles and fields
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Cascella, Michele
(2018).
Coarse-graining peptides -- from particles to fields.
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Cascella, Michele
(2018).
Coarse-graining peptides -- From particles to fields.
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Cascella, Michele
(2017).
Coarse-graining peptides -- From particles to fields.
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Cascella, Michele
(2015).
Beyond Millisecond Dynamics of Large Macromolecular Systems Using Coarse-Grained and Hybrid Particle/Field Approaches.
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Cascella, Michele
(2015).
A Native Human Protein Nanoconstruct with Acquired Transcytocic Properties through Endothelial Barriers.
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Cascella, Michele
(2015).
A Native Human Protein Nanoconstruct with Acquired Transcytocic Properties through Endothelial Barriers.
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Cascella, Michele
(2015).
A Native Human Protein Nanoconstruct with Acquired Transcytocic Properties through Endothelial Barriers.
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Cascella, Michele
(2015).
Discovery of a Novel Enzymatic Function in Cellular Retinal Binding Protein.
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Cascella, Michele
(2014).
Modulation of protein function by micro-solvation effects: the puzzling case of cis-retinal binding in CRALBP.
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Cascella, Michele
(2014).
Lipid recognition and exchange mechanisms in transporters of the Sec-14 like family.
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Cascella, Michele
(2014).
Lipophilic transporters of the Sec 14-like family: structure, dynamics, and function explored by computer simulations.
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Cascella, Michele
(2014).
Multi-scale simulation of proteins: from the Schroedinger equation to coarse grained modelling.
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Cascella, Michele
(2014).
Multi-scale simulations of proteins: from the Schroedinger equation to coarse-grained modelling.
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Sen, Samiran & Cascella, Michele
(2023).
Advances in Hamiltonian Hybrid Particle–Field Theory: Improving the description of interfacial systems.
University of Oslo, Faculty of Mathematics and Natural Sciences, Department of Chemistry.
ISSN 1501-7710.
2023(2618).
Show summary
Laws of physics govern the motion of molecules that constitute all materials, living and non-living, in a highly hierarchical organisation, across tremendous scales of size and time. Molecular dynamics provides a direct way of operating these laws to reproduce the natural behaviour of molecular systems at the atomic resolution. Analysis of the resulting molecular trajectories provides us with greater insight into the workings of these complex systems.
Soft matter systems such as lipid membranes, proteins and DNA, can vary greatly in their dimensionality from a few nanometres to several millimetres. Computer simulations require a suitable description of their constituting structures and interactions, detailed enough to successfully reproduce their dynamics, yet simple enough for a comprehensive understanding and to costeffectively produce results. High resolution studies call for high computational costs, which, in turn imply limited accessibility to larger systems.
This work discusses a methodology to access mesoscale systems with characteristic sizes and time in the order of micrometres and milliseconds, respectively, with molecular resolution. It describes interactions between particles by coupling them to an external density-dependent field potential.
The theoretical developments of this study are based on the Hamiltonian formulation of the hybrid particle–field theory (hPF). The seed for its foundation was sowed in 2020, and the current work institutes it by extending its theory into a fully functional molecular dynamics mechanism.
In this approach, particle forces are derived from purely mechanical considerations, without resorting to any approximation of statistical mean-field origins. In doing so, rigorous conservation of energy and momentum in grid-converged limits is achieved. Also, by smoothing the densities of the particles, the method is freed from many artefact-causing grid-dependent biases.
Alongside constant energy and constant volume simulations, constant pressure simulation techniques are also developed. The current work derives a complete theoretical framework for calculating the internal pressure of a system, and evidences a natural anisotropy in it. Machine learning strategies are employed to optimise the model parameters in order to represent interactions between particles with greater accuracy. In doing so, stress-free conditions are achieved, manifesting in the correct interfacial properties like surface tension, and undulatory motions of lamellar membranes.
Achieving a direct description of particle-particle correlations is yet another outcome of the theory. In practice, it means to be able to obtain stable solids and co-existing phases, even in systems with a single-species. Preliminary tests on soft-core Lennard Jones systems indeed show such behaviour.
The entire formalism is implemented into the freely available open-source software, HylleraasMD. It uses embarrassingly parallelisable routines written in a combination of Python and Fortran, making it a rather efficient computational approach to achieve equilibrium soft matter systems, for example, self-assembly of lipids both into extended and vesicular structures.
Overall, the discussed developments establish a strong foundation in understanding soft mesoscale systems and show several promising avenues to explore in the coming days. It is time to enter into the realm of more realistic and complex biological interfacial systems.
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Mors, Mira & Cascella, Michele
(2023).
Molecular Modeling of Nucleosome Core Particles.
Kjemisk Institutt, Universitetet i Oslo.
Show summary
Nucleosomes, the basic units of chromatin in eukaryotes, play a critical role in DNA processing such as transcription, replication, and repair. The canonical nucleosome core particle consists of 145 to 147 DNA base pairs wrapped around a histone octamer composed of one (H3-H4)₂ tetramer and two H2A-H2B dimers. This arrangement results in two stacked disks. Although the importance of non-canonical structures with alternative histone conformations in controlling genome organization and regulation has been recognized, our knowledge of them remains limited. In a recent development, unconventional nucleoprotein particles composed of only two types of histones (H3-H4 or CENP-A-H4) have been identified through cryo-electron microscopy. Here, all-atom molecular dynamics simulations are performed on single nucleosome units to elucidate the specific dynamic properties of the octamers forming a di-tetrameric core. The analysis shows that these structures exhibit significant DNA unwrapping compared to the canonical nucleosome. In particular, the histone H3 variant CENP-A, which marks the location of the centromere, shows the most excessive unwrapping of DNA ends from the core, resulting in an almost orthogonal arrangement of the DNA entry/exit sites. The pronounced flexibility for the last ∼ 20 base pairs observed in the simulations is related to the increased interdisk spacing of the DNA superhelical gyres, which is about one and a half times larger than in the corresponding nucleosome core particle with histones H3 or CENP-A. The results consistently indicate that the di-tetrameric stoichiometry of H3-H4 or CENP-A-H4 leads to increased dynamics and to an opening of the core particle, potentially allowing greater access to DNA binding factors.
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Steinnes, Lasse; Cascella, Michele & Hjorth-Jensen, Morten
(2022).
Electrostatics in Mesoscale Simulations of Biological Membranes using the Hybrid-Particle Field Approach.
Universitetet i Oslo.
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Ledum, Morten; Cascella, Michele & Gauss, Jurgen
(2022).
Hamiltonian hybrid particle-field method for biological soft matter: Efficient simulation and machine learning approaches.
Department of Chemistry, Faculty of Mathematics and Natural Sciences, University of Oslo.
ISSN 1501-7710.
2022(2516).
Show summary
Molecular dynamics describes a simulation strategy wherein systems of atoms and molecules interact, subject to known laws of classical physics. The analysis of the resulting molecular trajectories yields an incredibly powerful computational microscope with atomic resolution, providing a cost-effective alternative to chemical experiments.
Although powerful, these techniques are limited by the number of atoms which can be represented simultaneously. Most biologically interesting systems contain billions of individual atoms making up e.g. cells, organelles, viruses, bacteria, or other microorganisms. In order to model such systems, it is necessary to simplify the description. The simplification treated in this thesis involves decoupling separate molecules, allowing interaction only through a slowly varying density-field. In principle this allows further increases in the system size-reaching biologically relevant soft-matter systems at the mesoscale-while retaining molecular resolution.
My work has helped extend this hybrid particle-field model with the development of open-source simulation software, the addition of pressure control schemes, and a novel approach for determining the necessary model parameters by machine learning. Additionally, some theoretical results on the intrinsic approximations made by the model are considered. The research contained in this dissertation provides important steps forward towards truly realistic model representations of soft-matter systems.
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Bore, Sigbjørn Løland; Cascella, Michele & Kvaal, Simen
(2020).
Advances in the Hybrid Particle-Field Approach: Towards Biological Systems.
Matematisk Naturvitenskapelig fakultet, Universitetet i Oslo.
ISSN 1501-7710.
2020(2245).
Show summary
This dissertation aims at advancing the capability of hybrid particle-field simulations of representing various physical phenomena relevant to biological systems. While hybrid particle-field simulations are computationally efficient and well adapted for studying mesoscale systems with molecular resolution, this approach has so far predominantly been applied to simple polymers. The computational investigation of systems of higher complexity, such as DNA and proteins, requires development of new models and an extension of the hybrid particle-field methodology. To this end, six research papers are presented. The main research output of these papers consists in both new methods for representing electrostatics and constant-pressure conditions, and new models for proteins and charged lipids within the hybrid particle-field formalism. The work contained in this thesis thus provides key steps towards large-scale realistic representations of biological systems
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Sekulic, Nikolina; Cascella, Michele & Hovet, Oda
(2020).
Molecular Dynamics Studies on the Essential Mitotic Protein Kinase – Aurora B.
Universitetet i Oslo.
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