Interaction of helical peptides in implicit membrane: Monte Carlo simulations of the homodimer of glycophorin ADifficulties in experimental determination of spatial structure of membrane proteins oligomers stimulate the evolution of alternative approaches to structural investigations. One of such techniques is Monte Carlo conformational search in implicit membrane. This approach has been previously widely used for analysis of interaction of different monomeric peptides and proteins with membrane (see other topics). Here we present one of the first attempts to predict the dimer structure formed by transmembrane helices of human glycophorin A (GpA), surface protein from membrane of erythrocytes. ResultsThe calculations permit delineation of several possible models of the dimer structure. Residues, whose replacements significantly decrease stability of the dimer, are located on the monomer–monomer interface. One of the models (model I) is close to the NMR-derived structure. Presence of other structural models could be explained by several reasons: (1) Dependence of the structure on the environment features. Thus, other models could be realized in other model membranes e.g., in lipid bilayers. (2) Several models could simultaneously exist in a dynamic equilibrium. (3) Poor accuracy of the membrane treatment. This problem could be solved by relaxation of the MC models via molecular dynamics in full-atom lipid bilayers.
ConclusionsProposed approach permits effective exploration of the peptides conformational space and provides adequate structural models of transmembrane helices dimers. The agreement of the calculated models with experimental data provides that this approach represents a powerfull tool for prediction of 3D structures of TM helix–helix oligomers in the membrane. Predictive power of the proposed approach could be enlarged via relaxation of calculated models using molecular dynamics in explicit bilayers. The approach has a strong perspective in modeling of other membrane proteins such as tyrosine kinase receptors, GPCRs, etc. (Authors: Yana Vereshaga, Pavel Volynsky, Dmitry Nolde, Roman Efremov). |
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