title: De novo peptide structure prediction: an overview.
abstract: Peptide structure identification is an important contribution to the further characterization of the residues involved in functional interactions. De novo structure peptide prediction has, in the past few years, made significant progresses that make reasonable, for peptides up to 50 amino acids, its use for the fast identification of their structural topologies. Here, we introduce some of the concepts underlying approaches of the field, together with their limits.
authors.affiliation: Molécules Thérapeutiques In Silico, Inserm UMR-S 973, Université Paris Diderot, Sorbonne Paris Cité, 35 rue Helene Brion, 75013, Paris, France.
authors.forename: Pierre
authors.initials: P
authors.lastname: Thévenet
authors.forename: Julien
authors.initials: J
authors.lastname: Rey
authors.forename: Gautier
authors.initials: G
authors.lastname: Moroy
authors.forename: Pierre
authors.initials: P
authors.lastname: Tuffery
mesh_terms: D019295:Computational Biology / Q000379:methods*; D008958:Models, Molecular; D008968:Molecular Conformation; D056004:Molecular Dynamics Simulation; D010455:Peptides / Q000737:chemistry*
chemical_list: D010455:Peptides