Rosettaligand: Protein-small Molecule Docking with Full Side-chain Flexibility.
From: Vanderbilt University, Department of Chemistry, Center for Structural Biology, Nashville, TN 37235-8725, USA. jens@jens-meiler.de
Proteins
- Publish Date: Nov 2006
- ISSN: 1097-0134
- Volume: 65
- Issue: 3
- Pages: 538-48
- Medium: Internet
- Language: English
- Citation (JAMA): Meiler Jens, Baker David, et al. Rosettaligand: Protein-small Molecule Docking with Full Side-chain Flexibility.. Proteins Nov 2006;65:538-48
Abstract
Protein-small molecule docking algorithms provide a means to model the structure of protein-small molecule complexes in structural detail and play an important role in drug development. In recent years the necessity of simulating protein side-chain flexibility for an accurate prediction of the protein-small molecule interfaces has become apparent, and an increasing number of docking algorithms probe different approaches to include protein flexibility. Here we describe a new method for docking small molecules into protein binding sites employing a Monte Carlo minimization procedure in which the rigid body position and orientation of the small molecule and the protein side-chain conformations are optimized simultaneously. The energy function comprises van der Waals (VDW) interactions, an implicit solvation model, an explicit orientation hydrogen bonding potential, and an electrostatics model. In an evaluation of the scoring function the computed energy correlated with experimental small molecule binding energy with a correlation coefficient of 0.63 across a diverse set of 229 protein- small molecule complexes. The docking method produced lowest energy models with a root mean square deviation (RMSD) smaller than 2 A in 71 out of 100 protein-small molecule crystal structure complexes (self-docking). In cross-docking calculations in which both protein side-chain and small molecule internal degrees of freedom were varied the lowest energy predictions had RMSDs less than 2 A in 14 of 20 test cases.
Mesh Headings (Keywords): Algorithms, Binding Sites, Models, Molecular, Monte Carlo Method, Protein Conformation, Proteins, Thermodynamics
Check for Full Text / PubMed Unique Identifier (PMID): 16972285
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