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EnzVolNet

COMPUTATIONAL EVOLUTION OF ENZYME VARIANTS THROUGH CONFORMATIONAL NETWORKS

Total Cost €

0

EC-Contrib. €

0

Partnership

0

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 EnzVolNet project word cloud

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

mutagenesis    rules    underlying    dynamics    tools    biology    experiments    economically    relies    paradigm    magnitude    alone    evaluation    efficiencies    enormous    modern    engineer    heteromeric    mutations    elucidate    chemical    host    predictions    models    catalytic    completely    experimental    reformulating    nature    reactions    complexes    tremendous    functions    extracted    markov    advantageous    enzvolnet    reduces    reducing    catalyze    counterparts    pressures    regulation    extract    biosynthetic    allosterically    efforts    structure    functional    complexity    chemoinformatic    scope    evolution    perform    enzyme    mimicking    regulated    thousands    substrate    alteration    stand    variants    unviable    beneficial    physical    orders    cell    conformational    subunits    random    ing    simplifies    costly    natural    enzymes    protein    unfortunately    isolated    computational    lag    alter    initial    principles    array    strategy    stress    proficient    network    metabolic    revolutionary    accelerating    selective   

Project "EnzVolNet" data sheet

The following table provides information about the project.

Coordinator
UNIVERSITAT DE GIRONA 

Organization address
address: PLACA SANT DOMENEC 3
city: GIRONA
postcode: 17004
website: www.udg.es

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 Spain [ES]
 Project website http://iqcc.udg.edu/wordpress/2017/01/28/marie-curie-fellowship-awarded-javier-iglesias-silvia-osuna/
 Total cost 158˙121 €
 EC max contribution 158˙121 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2016
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2017
 Duration (year-month-day) from 2017-05-01   to  2019-04-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    UNIVERSITAT DE GIRONA ES (GIRONA) coordinator 158˙121.00

Map

 Project objective

Natural enzymes have evolved to perform their functions under complex selective pressures, being capable of accelerating reactions by several orders of magnitude. In particular, heteromeric enzyme complexes catalyze an enormous array of useful reactions that are often allosterically regulated by different protein partners. Unfortunately, the underlying physical principles of this regulation are still under debate, which makes the alteration of enzyme structure towards useful isolated subunits a tremendous challenge for modern chemical biology. Exploitation of isolated enzyme subunits, however, is advantageous for biosynthetic applications as it reduces the metabolic stress on the host cell and greatly simplifies efforts to engineer specific properties of the enzyme. Current approaches to alter natural enzyme complexes are based on the evaluation of thousands of variants, which make them economically unviable and the resulting catalytic efficiencies lag far behind their natural counterparts. The revolutionary nature of EnzVolNet relies on the application of conformational network models (e.g Markov State Models) to extract the essential functional protein dynamics and key conformational states, reducing the complexity of the enzyme design paradigm and completely reformulating previous computational design approaches. Initial mutations are extracted from costly random mutagenesis experiments and chemoinformatic tools are used to identify beneficial mutations leading to more proficient enzymes. This new strategy will be applied to develop stand-alone enzymes from heteromeric protein complexes, with advantageous biosynthetic properties and improve activity and substrate scope. Experimental evaluation of our computational predictions will finally elucidate the potential of the present approach for mimicking Nature’s rules of evolution.

 Publications

year authors and title journal last update
List of publications.
2018 Miguel A. Maria-Solano, Eila Serrano-Hervás, Adrian Romero-Rivera, Javier Iglesias-Fernández, Sílvia Osuna
Role of conformational dynamics in the evolution of novel enzyme function
published pages: 6622-6634, ISSN: 1359-7345, DOI: 10.1039/c8cc02426j
Chemical Communications 54/50 2019-09-17

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The information about "ENZVOLNET" are provided by the European Opendata Portal: CORDIS opendata.

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