Small Molecule Rotamers Enable Simultaneous Optimization of Small Molecule and Protein Degrees of Freedom in ROSETTALIGAND Docking

We introduce small molecule rotamers into the rotamer search protocol used in ROSETTA to model small molecule flexibility in docking. Rosetta, a premier protein modeling suite, models side chain flexibility using discrete conformations observed in the Protein Data Bank (PDB). We mimic this concept and build small molecule rotamers based on conformations from the Cambridge Structural Database. We evaluate the small molecule rotamer generation protocol on a test set of 628 conformations, taken from the PDBBind database, of small molecules with ≤ 6 rotatable bonds. Our protocol generates ensembles in which the closest conformation on average is 0.45 ± 0.31 Å RMSD from the crystallized conformation. Furthermore, in two sets of docking benchmarks the native ligand position and conformation is found within the top 1 % of models by energy in 72% and 90% of all cases.

[1]  O. Schueler‐Furman,et al.  Progress in protein–protein docking: Atomic resolution predictions in the CAPRI experiment using RosettaDock with an improved treatment of side‐chain flexibility , 2005, Proteins.

[2]  Roland L. Dunbrack,et al.  Backbone-dependent rotamer library for proteins. Application to side-chain prediction. , 1993, Journal of molecular biology.

[3]  Jonas Boström,et al.  Assessing the performance of OMEGA with respect to retrieving bioactive conformations. , 2003, Journal of molecular graphics & modelling.

[4]  Gerhard Klebe,et al.  A fast and efficient method to generate biologically relevant conformations , 1994, J. Comput. Aided Mol. Des..

[5]  P. Charifson,et al.  Conformational analysis of drug-like molecules bound to proteins: an extensive study of ligand reorganization upon binding. , 2004, Journal of medicinal chemistry.

[6]  F. Allen The Cambridge Structural Database: a quarter of a million crystal structures and rising. , 2002, Acta crystallographica. Section B, Structural science.

[7]  Jeffrey J. Gray,et al.  Protein-protein docking with simultaneous optimization of rigid-body displacement and side-chain conformations. , 2003, Journal of molecular biology.

[8]  Renxiao Wang,et al.  The PDBbind database: collection of binding affinities for protein-ligand complexes with known three-dimensional structures. , 2004, Journal of medicinal chemistry.

[9]  D. Baker,et al.  A large scale test of computational protein design: folding and stability of nine completely redesigned globular proteins. , 2003, Journal of molecular biology.

[10]  J. Meiler,et al.  Using neural networks for (13)c NMR chemical shift prediction-comparison with traditional methods. , 2002, Journal of magnetic resonance.

[11]  Junmei Wang,et al.  Development and testing of a general amber force field , 2004, J. Comput. Chem..

[12]  A. Leach,et al.  Ligand docking to proteins with discrete side-chain flexibility. , 1994, Journal of molecular biology.

[13]  P. Bradley,et al.  Toward High-Resolution de Novo Structure Prediction for Small Proteins , 2005, Science.

[14]  Jens Meiler,et al.  ROSETTALIGAND: Protein–small molecule docking with full side‐chain flexibility , 2006, Proteins.

[15]  D. Baker,et al.  Design of a Novel Globular Protein Fold with Atomic-Level Accuracy , 2003, Science.

[16]  M. Karplus,et al.  Effective energy function for proteins in solution , 1999, Proteins.

[17]  Tanja Kortemme,et al.  Potential functions for hydrogen bonds in protein structure prediction and design. , 2005, Advances in protein chemistry.

[18]  Kam Y. J. Zhang,et al.  Conversion of monomeric protein L to an obligate dimer by computational protein design , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[19]  David E. Kim,et al.  Computational Alanine Scanning of Protein-Protein Interfaces , 2004, Science's STKE.