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VARIAMOLS SIGNED

VAriable ResolutIon Algorithms for macroMOLecular Simulation

Total Cost €

EC-Contrib. €

Partnership

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Outcomes and
results

VARIAMOLS project word cloud

Explore the words cloud of the VARIAMOLS project. It provides you a very rough idea of what is the project "VARIAMOLS" about.

destroyed models molecular simulate mediated atomistic unfold coarse missing aided molecules representations computer extended strictly prominent atoms resolution elegant gap variety biological simplified size combine uniform machines life membrane coin dynamics complementary optimize simulation soft bridging proteins perform balance spectrum employed systematic realistic variamols relevance alternative accuracy assemblies protein macromolecules antibodies cellular lines algorithmic central computational versatile intertwined scales dramatically biomolecules science within interconnected viruses insurmountable reactions time occupy chemical accurate medical extremely transport limitation reproduction philosophy catalyze foreign bodies grained bind broad efficiency

Project "VARIAMOLS" data sheet

The following table provides information about the project.

Coordinator	UNIVERSITA DEGLI STUDI DI TRENTO Organization address address: VIA CALEPINA 14 city: TRENTO postcode: 38122 website: www.unitn.it contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.
Coordinator Country	Italy [IT]
Project website	http://variamols.physics.unitn.eu
Total cost	1˙339˙351 €
EC max contribution	1˙339˙351 € (100%)
Programme	1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
Code Call	ERC-2017-STG
Funding Scheme	ERC-STG
Starting year	2018
Duration (year-month-day)	from 2018-01-01 to 2022-12-31

Partnership

Take a look of project's partnership.

#	participants	country	role	EC contrib. [€]
1	UNIVERSITA DEGLI STUDI DI TRENTO UNIVERSITA DEGLI STUDI DI TRENTO Organization address address: VIA CALEPINA 14 city: TRENTO postcode: 38122 website: www.unitn.it contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.	IT (TRENTO)	coordinator	1˙339˙351.00

Map

Project objective

Within the broad spectrum of biological soft matter systems, large proteins and protein assemblies occupy a central role. These molecules are extremely versatile: they can catalyze chemical reactions, transport atoms and molecules across the cellular membrane, bind to foreign bodies to be destroyed, or combine into large molecular machines that perform a variety of different tasks. One of the most prominent problems in the computational study of these macromolecules is that the cost of using accurate atomistic models dramatically increases with system size. Simplified, coarse-grained representations offer an elegant and effective alternative to high-resolution models, and enable the simulation of large systems over extended time scales; the other side of the coin, however, is that the missing chemical detail often represents an insurmountable limitation to the realistic reproduction of the properties of interest. The main goal of the VARIAMOLS project is to develop and apply novel computer-aided methods for the study of large molecular assemblies and their dynamics, thus bridging the existing gap between computational cost and chemical accuracy. Specifically, the research will unfold along two intertwined lines: 1) the development of non-uniform resolution models of the system, which optimize the balance between detail and efficiency; and 2) the study of dynamics-mediated properties of protein assemblies. The working philosophy of VARIAMOLS has two complementary and strictly interconnected aspects: on the one hand, the theoretical and algorithmic advancement of the methods currently employed to represent and simulate biomolecules; on the other hand, the systematic application of the developed methods to real-life case studies of great relevance for medical science and technology, with a particular focus on viruses and antibodies.

Publications

List of publications.
year	authors and title	journal	last update
2019	Marco Giulini, Raffaello Potestio A deep learning approach to the structural analysis of proteins published pages: 20190003, ISSN: 2042-8898, DOI: 10.1098/rsfs.2019.0003	Interface Focus 9/3	2019-09-04
2018	Patrick Diggins, Changjiang Liu, Markus Deserno, Raffaello Potestio Optimal Coarse-Grained Site Selection in Elastic Network Models of Biomolecules published pages: 648-664, ISSN: 1549-9618, DOI: 10.1021/acs.jctc.8b00654	Journal of Chemical Theory and Computation 15/1	2019-09-04

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