title: DOT2: Macromolecular docking with improved biophysical models.
abstract: Computational docking is a useful tool for predicting macromolecular complexes, which are often difficult to determine experimentally. Here, we present the DOT2 software suite, an updated version of the DOT intermolecular docking program. DOT2 provides straightforward, automated construction of improved biophysical models based on molecular coordinates, offering checkpoints that guide the user to include critical features. DOT has been updated to run more quickly, allow flexibility in grid size and spacing, and generate an infinitive complete list of favorable candidate configurations. Output can be filtered by experimental data and rescored by the sum of electrostatic and atomic desolvation energies. We show that this rescoring method improves the ranking of correct complexes for a wide range of macromolecular interactions and demonstrate that biologically relevant models are essential for biologically relevant results. The flexibility and versatility of DOT2 accommodate realistic models of complex biological systems, improving the likelihood of a successful docking outcome.
authors.affiliation: San Diego Supercomputer Center, University of California, San Diego, La Jolla, California 92093, USA. vickie@sdsc.edu
authors.forename: Victoria A
authors.initials: VA
authors.lastname: Roberts
authors.forename: Elaine E
authors.initials: EE
authors.lastname: Thompson
authors.forename: Michael E
authors.initials: ME
authors.lastname: Pique
authors.forename: Martin S
authors.initials: MS
authors.lastname: Perez
authors.forename: L F
authors.initials: LF
authors.lastname: Ten Eyck
mesh_terms: D000465:Algorithms; D019295:Computational Biology; D046911:Macromolecular Substances / Q000737:chemistry; D062105:Molecular Docking Simulation; D011506:Proteins / Q000737:chemistry*; D012984:Software; D055672:Static Electricity
chemical_list: D046911:Macromolecular Substances; D011506:Proteins