title: An empirical energy function for structural assessment of protein transmembrane domains.
abstract: Knowing the structure of a protein is essential to characterize its function and mechanism at the molecular level. Despite major advances in solving structures experimentally, most membrane protein native conformations remain unknown. This lack of available structures, along with the physical constraints imposed by the lipid bilayer environment, constitutes a difficulty for the modeling of membrane protein structures. Assessing the quality of membrane protein models is therefore critical. Using a non-redundant set of 66 membrane protein structures (41 alpha and 25 beta), we have developed an empirical energy function for the structural assessment of alpha-helical and beta-sheet transmembrane domains. This statistical potential quantifies the interatomic distance between residues located in the lipid bilayer. To minimize the problem of insufficient sampling, we have used kernel density estimations of the distance distributions. Following a leave-one-out cross-validation procedure, we show that our method outperforms current statistical potentials in discriminating correct from incorrect membrane protein models. Furthermore, the comparison of our distance-dependent statistical potential with one optimized on globular proteins provides insights into the rules by which residues interact within the lipid bilayer.
authors.affiliation: Inserm U1134, Paris, France; Université Paris Diderot, Sorbonne Paris Cité, UMR_S 1134, Paris, France; Institut National de la Transfusion Sanguine, Paris, France; Laboratory of Excellence GR-Ex, Paris, France. Electronic address: guillaume.postic@univ-paris-diderot.fr.
authors.forename: Guillaume
authors.initials: G
authors.lastname: Postic
authors.affiliation: Inserm U1134, Paris, France; Université Paris Diderot, Sorbonne Paris Cité, UMR_S 1134, Paris, France; Institut National de la Transfusion Sanguine, Paris, France; Laboratory of Excellence GR-Ex, Paris, France.
authors.forename: Yassine
authors.initials: Y
authors.lastname: Ghouzam
authors.affiliation: Inserm U1134, Paris, France; Université Paris Diderot, Sorbonne Paris Cité, UMR_S 1134, Paris, France; Institut National de la Transfusion Sanguine, Paris, France; Laboratory of Excellence GR-Ex, Paris, France. Electronic address: jean-christophe.gelly@univ-paris-diderot.fr.
authors.forename: Jean-Christophe
authors.initials: JC
authors.lastname: Gelly
mesh_terms: D002462:Cell Membrane / Q000737:chemistry*; D019295:Computational Biology / Q000379:methods*; D008565:Membrane Proteins / Q000737:chemistry*; D008958:Models, Molecular; D017433:Protein Structure, Secondary; D017434:Protein Structure, Tertiary; D013816:Thermodynamics
chemical_list: D008565:Membrane Proteins
keywords: Empirical potential; Kernel density estimation; Membrane protein; Model quality assessment