Fast and automated functional classification with MED-SuMo: an application on purine-binding proteins

Autor: Alexandre G. de Brevern, Fabrice Moriaud, Olivia Doppelt-Azeroual, François Delfaud
Přispěvatelé: Molecular Extended Distribution in Information Technology (MEDIT), MEDIT SA, Dynamique des Structures et Interactions des Macromolécules Biologiques (DSIMB), Institut National de la Transfusion Sanguine [Paris] (INTS)-Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Santé et de la Recherche Médicale (INSERM), This work was supported by National Institute of Health and Medical Research (INSERM), National Institute of Institute of Blood Transfusion (INTS), University Denis Diderot - Paris 7 and Ministère de la Recherche. ODA‟s PhD is financed by the French technical research association (ANRT) through a CIFRE grant.
Rok vydání: 2010
Předmět:
Zdroj: Protein Science
Protein Science, Wiley, 2010, 19 (4), pp.847-67. ⟨10.1002/pro.364⟩
ISSN: 0961-8368
1469-896X
Popis: International audience; Ligand-protein interactions are essential for biological processes, and precise characterization of protein binding sites is crucial to understand protein functions. MED-SuMo is a powerful technology to localize similar local regions on protein surfaces. Its heuristic is based on a 3D representation of macromolecules using specific surface chemical features associating chemical characteristics with geometrical properties. MED-SMA is an automated and fast method to classify binding sites. It is based on MED-SuMo technology, which builds a similarity graph, and it uses the Markov Clustering algorithm. Purine binding sites are well studied as drug targets. Here, purine binding sites of the Protein DataBank (PDB) are classified. Proteins potentially inhibited or activated through the same mechanism are gathered. Results are analyzed according to PROSITE annotations and to carefully refined functional annotations extracted from the PDB. As expected, binding sites associated with related mechanisms are gathered, for example, the Small GTPases. Nevertheless, protein kinases from different Kinome families are also found together, for example, Aurora-A and CDK2 proteins which are inhibited by the same drugs. Representative examples of different clusters are presented. The effectiveness of the MED-SMA approach is demonstrated as it gathers binding sites of proteins with similar structure-activity relationships. Moreover, an efficient new protocol associates structures absent of cocrystallized ligands to the purine clusters enabling those structures to be associated with a specific binding mechanism. Applications of this classification by binding mode similarity include target-based drug design and prediction of cross-reactivity and therefore potential toxic side effects.
Databáze: OpenAIRE
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