Computation of 3D queries for ROCS based virtual screens

Rapid overlay of chemical structures (ROCS) is a method that aligns molecules based on shape and/or chemical similarity. It is often used in 3D ligand-based virtual screening. Given a query consisting of a single conformation of an active molecule ROCS can generate highly enriched hit lists. Typically the chosen query conformation is a minimum energy structure. Can better enrichment be obtained using conformations other than the minimum energy structure? To answer this question a methodology has been developed called CORAL (COnformational analysis, Rocs ALignment). For a given set of molecule conformations it computes optimized conformations for ROCS screening. It does so by clustering all conformations of a chosen molecule set using pairwise ROCS combo scores. The best representative conformation is that which has the highest average overlap with the rest of the conformations in the cluster. It is these best representative conformations that are then used for virtual screening. CORAL was tested by performing virtual screening experiments with the 40 DUD (Directory of Useful Decoys) data sets. Both CORAL and minimum energy queries were used. The recognition capability of each query was quantified as the area under the ROC curve (AUC). Results show that the CORAL AUC values are on average larger than the minimum energy AUC values. This demonstrates that one can indeed obtain better ROCS enrichments with conformations other than the minimum energy structure. As a result, CORAL analysis can be a valuable first step in virtual screening workflows using ROCS.

[1]  Gregory A Landrum,et al.  Conformation mining: an algorithm for finding biologically relevant conformations. , 2005, Journal of medicinal chemistry.

[2]  David Rogers,et al.  Cheminformatics analysis and learning in a data pipelining environment , 2006, Molecular Diversity.

[3]  Anthony Nicholls,et al.  What do we know and when do we know it? , 2008, J. Comput. Aided Mol. Des..

[4]  Kenneth M. Merz,et al.  Can we separate active from inactive conformations? , 2002, J. Comput. Aided Mol. Des..

[5]  Stefan Schmitt,et al.  Do structurally similar ligands bind in a similar fashion? , 2006, Journal of medicinal chemistry.

[6]  C Kooperberg,et al.  Assembly of protein tertiary structures from fragments with similar local sequences using simulated annealing and Bayesian scoring functions. , 1997, Journal of molecular biology.

[7]  Robert D Clark,et al.  Neighborhood behavior: a useful concept for validation of "molecular diversity" descriptors. , 1996, Journal of medicinal chemistry.

[8]  Peter Willett,et al.  Rapid Quantification of Molecular Diversity for Selective Database Acquisition , 1997, J. Chem. Inf. Comput. Sci..

[9]  Brian K. Kobilka,et al.  High resolution crystal structure of human B2-adrenergic G protein-coupled receptor. , 2007 .

[10]  C. Humblet,et al.  Modeling G protein‐coupled receptors for structure‐based drug discovery using low‐frequency normal modes for refinement of homology models: Application to H3 antagonists , 2010, Proteins.

[11]  P. Hawkins,et al.  Comparison of shape-matching and docking as virtual screening tools. , 2007, Journal of medicinal chemistry.

[12]  Simona Distinto,et al.  How To Optimize Shape-Based Virtual Screening: Choosing the Right Query and Including Chemical Information , 2009, J. Chem. Inf. Model..

[13]  F. James Rohlf,et al.  Biometry: The Principles and Practice of Statistics in Biological Research , 1969 .

[14]  J. Hanley,et al.  The meaning and use of the area under a receiver operating characteristic (ROC) curve. , 1982, Radiology.

[15]  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.

[16]  Gary Tresadern,et al.  A comparison of ligand based virtual screening methods and application to corticotropin releasing factor 1 receptor. , 2009, Journal of molecular graphics & modelling.

[17]  J. Andrew Grant,et al.  Molecular shape and electrostatics in the encoding of relevant chemical information , 2005, J. Comput. Aided Mol. Des..

[18]  R. Stevens,et al.  High-Resolution Crystal Structure of an Engineered Human β2-Adrenergic G Protein–Coupled Receptor , 2007, Science.

[19]  Tudor I Oprea,et al.  2D QSAR and similarity studies on cruzain inhibitors aimed at improving selectivity over cathepsin L. , 2008, Bioorganic & medicinal chemistry.

[20]  Dong Xu,et al.  PROSPECT II: protein structure prediction program for genome-scale applications. , 2003, Protein engineering.

[21]  Pang-Ning Tan,et al.  Receiver Operating Characteristic , 2009, Encyclopedia of Database Systems.

[22]  J. A. Grant,et al.  A fast method of molecular shape comparison: A simple application of a Gaussian description of molecular shape , 1996, J. Comput. Chem..

[23]  J. A. Grant,et al.  A shape-based 3-D scaffold hopping method and its application to a bacterial protein-protein interaction. , 2005, Journal of medicinal chemistry.

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

[25]  J. Irwin,et al.  Benchmarking sets for molecular docking. , 2006, Journal of medicinal chemistry.

[26]  Lei Xie,et al.  Using multiple structure alignments, fast model building, and energetic analysis in fold recognition and homology modeling , 2003, Proteins.

[27]  Jonas Boström,et al.  Reproducing the conformations of protein-bound ligands: A critical evaluation of several popular conformational searching tools , 2001, J. Comput. Aided Mol. Des..

[28]  K. Palczewski,et al.  Crystal Structure of Rhodopsin: A G‐Protein‐Coupled Receptor , 2000, Science.

[29]  J. Pin,et al.  Virtual screening workflow development guided by the "receiver operating characteristic" curve approach. Application to high-throughput docking on metabotropic glutamate receptor subtype 4. , 2005, Journal of medicinal chemistry.

[30]  R. Stevens,et al.  The 2.6 Angstrom Crystal Structure of a Human A2A Adenosine Receptor Bound to an Antagonist , 2008, Science.