title: Paircoil2: improved prediction of coiled coils from sequence.
abstract: We introduce Paircoil2, a new version of the Paircoil program, which uses pairwise residue probabilities to detect coiled-coil motifs in protein sequence data. Paircoil2 achieves 98% sensitivity and 97% specificity on known coiled coils in leave-family-out cross-validation. It also shows superior performance compared with published methods in tests on proteins of known structure.
authors.affiliation: Mathematics Department, Computer Science and Artificial Intelligence Laboratory, Cambridge, MA 02139, USA.
authors.forename: A V
authors.initials: AV
authors.lastname: McDonnell
authors.forename: T
authors.initials: T
authors.lastname: Jiang
authors.forename: A E
authors.initials: AE
authors.lastname: Keating
authors.forename: B
authors.initials: B
authors.lastname: Berger
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D003198:Computer Simulation; D008956:Models, Chemical; D008958:Models, Molecular; D008969:Molecular Sequence Data; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D020539:Sequence Analysis, Protein / Q000379:methods*; D012984:Software