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Investigating the Dynamic Aspects of Drug-Protein Recognition through a Combination of MD and NMR Analyses: Implications for the Development of Protein-Protein Interaction Inhibitors

In this paper, we investigate the dynamic aspects of the molecular recognition between a small molecule ligand and a flat, exposed protein surface, representing a typical target in the development of protein-protein interaction inhibitors. Specifically, we analyze the complex between the protein Fib...

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Detalles Bibliográficos
Autores principales: Meli, Massimiliano, Pagano, Katiuscia, Ragona, Laura, Colombo, Giorgio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4035249/
https://www.ncbi.nlm.nih.gov/pubmed/24865844
http://dx.doi.org/10.1371/journal.pone.0097153
Descripción
Sumario:In this paper, we investigate the dynamic aspects of the molecular recognition between a small molecule ligand and a flat, exposed protein surface, representing a typical target in the development of protein-protein interaction inhibitors. Specifically, we analyze the complex between the protein Fibroblast Growth Factor 2 (FGF2) and a recently discovered small molecule inhibitor, labeled sm27 for which the binding site and the residues mainly involved in small molecule recognition have been previously characterized. We have approached this problem using microsecond MD simulations and NMR-based characterizations of the dynamics of the apo and holo states of the system. Using direct combination and cross-validation of the results of the two techniques, we select the set of conformational states that best recapitulate the principal dynamic and structural properties of the complex. We then use this information to generate a multi-structure representation of the sm27-FGF2 interaction. We propose this kind of representation and approach as a useful tool in particular for the characterization of systems where the mutual dynamic influence between the interacting partners is expected to play an important role. The results presented can also be used to generate new rules for the rational expansion of the chemical diversity space of FGF2 inhibitors.