https://forum-sceptique.com/archives/45472.html#45472
J'ai quelque peu tardé à vous répondre mais mieux vaut tard que jamais.
J'avais déclaré:
"...Ces connaissances, David, les chercheurs LES ONT, mais ils souhaitent améliorer la vitesse de traitement des données et c'est là que la modélisation informatique entre en jeu..." [Noé]
et vous aviez répondu:
"...L'amélioration pour la prédiction par rapport à la méthode expériementale vient de l'utilisation d'un ordinateur, pas des concepts de l'évolution..." {David]
Non David, car dans chaque cas on utilise l'ordinateur. Comme vous le constaterez en lisant le résumé de l'article ci-dessous, le gain de vitesse est attribuable à la réduction de l'espace de recherche (reduce the search space).
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J Mol Biol 2002 Nov 15;324(1):177-92
Co-evolutionary analysis reveals insights into protein-protein interactions.
Goh CS, Cohen FE.
Program in Biological and Medical Informatics, University of California, San Francisco, CA 94143, USA.
Protein-protein interactions play crucial roles in biological processes. Experimental methods have been developed to survey the proteome for interacting partners and some computational approaches have been developed to extend the impact of these experimental methods. Computational methods are routinely applied to newly discovered genes to infer protein function and plausible protein-protein interactions. Here, we develop and extend a quantitative method that identifies interacting proteins based upon the correlated behavior of the evolutionary histories of protein ligands and their receptors.
We have studied six families of ligand-receptor pairs including: the syntaxin/Unc-18 family, the GPCR/G-alpha's, the TGF-beta/TGF-beta receptor system, the immunity/colicin domain collection from bacteria, the chemokine/chemokine receptors, and the VEGF/VEGF receptor family. For correlation scores above a defined threshold, we were able to find an average of 79% of all known binding partners. We then applied this method to find plausible binding partners for proteins with uncharacterized binding specificities in the syntaxin/Unc-18 protein and TGF-beta/TGF-beta receptor families. ANALYSIS OF THE RESULTS SHOWS THAT CO-EVOLUTIONARY ANALYSIS OF INTERACTING PROTEIN FAMILIES CAN REDUCE THE SEARCH SPACE FOR IDENTIFYING BINDING PARTNERS BY NOT ONLY FINDING BINDING PARTNERS FOR UNCHARACTERIZED PROTEINS BUT ALSO RECOGNIZING POTENTIALLY NEW BINDING PARTNERS FOR PREVIOUSLY CHARACTERIZED PROTEINS. We believe that correlated evolutionary histories provide a route to exploit the wealth of whole genome sequences and recent systematic proteomic results to extend the impact of these studies and focus experimental efforts to categorize physiologically or pathologically relevant protein-protein interactions.
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