title: Applying sequential forward floating selection to protein structure prediction with a study of HIV-1 PR.
abstract: Accurate structural models of target proteins are an essential component to structure-based drug design methods. To aid in this effort, the sequential forward floating selection (SFFS) algorithm is being applied to protein structure prediction. This algorithm demonstrates a reasonable balance between optimity of feature selection and efficiency while using large datasets such as the protein databank (PDB). The resulting protein structure predictions will be used in a study of HIV-1 PR.
authors.affiliation: University of Missouri-Columbia, University Of Missouri, Columbia, MO 65211-4380, USA.
authors.forename: Jeff
authors.initials: J
authors.lastname: Reneker
authors.forename: Chi-Ren
authors.initials: CR
authors.lastname: Shyu
mesh_terms: D000465:Algorithms; D030562:Databases, Protein; D016333:HIV Protease / Q000737:chemistry*; D011487:Protein Conformation
chemical_list: D016333:HIV Protease