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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.

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

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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