title: Rational prediction with molecular dynamics for hit identification.
abstract: Although the motions of proteins are fundamental for their function, for pragmatic reasons, the consideration of protein elasticity has traditionally been neglected in drug discovery and design. This review details protein motion, its relevance to biomolecular interactions and how it can be sampled using molecular dynamics simulations. Within this context, two major areas of research in structure-based prediction that can benefit from considering protein flexibility, binding site detection and molecular docking, are discussed. Basic classification metrics and statistical analysis techniques, which can facilitate performance analysis, are also reviewed. With hardware and software advances, molecular dynamics in combination with traditional structure-based prediction methods can potentially reduce the time and costs involved in the hit identification pipeline.
authors.affiliation: Department of Pharmacology, University of California, San Diego, La Jolla, CA 92093, USA. senichols@ucsd.edu
authors.forename: Sara E
authors.initials: SE
authors.lastname: Nichols
authors.forename: Robert V
authors.initials: RV
authors.lastname: Swift
authors.forename: Rommie E
authors.initials: RE
authors.lastname: Amaro
mesh_terms: D001665:Binding Sites; D019295:Computational Biology / Q000379:methods; D015195:Drug Design; D055808:Drug Discovery / Q000379:methods*; D004353:Drug Evaluation, Preclinical / Q000379:methods*; D062105:Molecular Docking Simulation; D056004:Molecular Dynamics Simulation; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism*; D012372:ROC Curve; D012984:Software
chemical_list: D011506:Proteins