Download User Manual - Duke University

Chapter 1
Introduction
OSPREY (Open Source Protein REdesign for You) is a suite of programs for computational
structure-based protein design. OSPREY is developed in the lab of Prof. Bruce Donald at Duke
University. This user manual is for OSPREY version 2.2 beta.
OSPREY is free software and can be redistributed and/or modified under the terms of the GNU
Lesser General Public License as published by the Free Software Foundation, either version 3 of the
License, or (optionally) any later version. OSPREY is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY
or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for
more details. Full licensing details, including citation requirements for the various different modules
of the software, are found in the document license.pdf enclosed with this package distribution.
OSPREY is specifically designed to identify protein mutants that possess desired target properties (e.g., improved stability, switch of substrate specificity, etc.). OSPREY can also be used
for predicting small-molecule inhibitors. Beginning with the 2.0 release, OSPREY now supports
protein-protein and protein-peptide interaction design. OSPREY is built around the following
algorithmic modules:
• DEE/A∗ : provably-accurate algorithms for protein design that combine Dead-End Elimination (DEE) rotamer pruning [8, 27] with A∗ conformation enumeration [22]. The DEE/A∗
algorithms score and rank mutation sequences based on the single best conformation for each
sequence, the Global Minimum Energy Conformation (GMEC). Hence, these algorithms are
referred to as GMEC-based. The DEE/A∗ algorithms are typically applied to redesign specific parts of the protein (e.g., the protein core). For problems where the goal is to improve
protein-ligand interactions, the K ∗ algorithm is typically used instead (see below). NOTE:
In this documentation, the term DEE refers to all of traditional DEE [8, 27] (DEE for rigid
rotamers and a rigid backbone), MinDEE [15], and the more efficient iMinDEE [11] (both
implement minimized DEE for continuously-flexible rotamers and a rigid backbone), BD [12]
(DEE for continuously-flexible backbones), Brdee [13] (DEE for backrub protein motions),
and DEEPer [18] (DEE with continuous sidechain and backbone flexibility). In cases where
a specific DEE algorithm is referenced, the corresponding algorithm name (e.g., Brdee) is
used explicitly.
• K ∗ : a provably-accurate algorithm for protein-ligand and protein-protein binding prediction,
as well as enzyme redesign [3, 15, 23]. K ∗ computes a provably-accurate approximation
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