Literature DB >> 18954138

Protein-ligand docking against non-native protein conformers.

Marcel L Verdonk1, Paul N Mortenson, Richard J Hall, Michael J Hartshorn, Christopher W Murray.   

Abstract

In the validation of protein-ligand docking protocols, performance is mostly measured against native protein conformers, i.e. each ligand is docked into the protein conformation from the structure that contained that ligand. In real-life applications, however, ligands are docked against non-native conformations of the protein, i.e. the apo structure or a structure of a different protein-ligand complex. Here, we have constructed an extensive test set for assessing docking performance against non-native protein conformations. This new test set is built on the Astex Diverse Set (which we recently constructed for assessing native docking performance) and contains 1112 non-native structures for 65 drug targets. Using the protein-ligand docking program GOLD, the Astex Diverse Set and the new Astex Non-native Set, we established that, whereas docking performance (top-ranked solution within 2 A rmsd of the experimental binding mode) is approximately 80% for native docking, this drops to 61% for non-native docking. A similar drop-off is observed for sampling performance (any solution within 2 A): 91% for native docking vs 72% for non-native docking. No significant differences were observed between docking performance against apo and nonapo structures. We found that, whereas small variations in protein conformation are generally tolerated by our rigid docking protocol, larger protein movements result in a catastrophic drop-off in performance. Some docking performance and nearly all sampling performance can be recovered by considering dockings produced against a small number of non-native structures simultaneously. Docking against non-native structures of complexes containing ligands that are similar to the docked ligand also significantly improves both docking performance and sampling performance.

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Year:  2008        PMID: 18954138     DOI: 10.1021/ci8002254

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  44 in total

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6.  Discovery of novel checkpoint kinase 1 inhibitors by virtual screening based on multiple crystal structures.

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Journal:  J Chem Inf Model       Date:  2011-10-12       Impact factor: 4.956

7.  Development and validation of an improved algorithm for overlaying flexible molecules.

Authors:  Robin Taylor; Jason C Cole; David A Cosgrove; Eleanor J Gardiner; Valerie J Gillet; Oliver Korb
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8.  Virtual fragment screening: an exploration of various docking and scoring protocols for fragments using Glide.

Authors:  Sameer Kawatkar; Hongming Wang; Ryszard Czerminski; Diane Joseph-McCarthy
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9.  Enhancing Virtual Screening Performance of Protein Kinases with Molecular Dynamics Simulations.

Authors:  Tavina L Offutt; Robert V Swift; Rommie E Amaro
Journal:  J Chem Inf Model       Date:  2016-10-03       Impact factor: 4.956

10.  Recipes for the selection of experimental protein conformations for virtual screening.

Authors:  Manuel Rueda; Giovanni Bottegoni; Ruben Abagyan
Journal:  J Chem Inf Model       Date:  2010-01       Impact factor: 4.956

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