Article

Conformational Analysis of Drug-Like Molecules Bound to Proteins:  An Extensive Study of Ligand Reorganization upon Binding

Vertex Pharmaceuticals, 130 Waverly Street, Cambridge, Massachusetts 02139
J. Med. Chem., 2004, 47 (10), pp 2499–2510
DOI: 10.1021/jm030563w
Publication Date (Web): April 7, 2004
Copyright © 2004 American Chemical Society

Abstract

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This paper describes a large-scale study on the nature and the energetics of the conformational changes drug-like molecules experience upon binding. Ligand strain energies and conformational reorganization were analyzed with different computational methods on 150 crystal structures of pharmaceutically relevant protein−ligand complexes. The common knowledge that ligands rarely bind in their lowest calculated energy conformation was confirmed. Additionally, we found that over 60% of the ligands do not bind in a local minimum conformation. While approximately 60% of the ligands were calculated to bind with strain energies lower than 5 kcal/mol, strain energies over 9 kcal/mol were calculated in at least 10% of the cases regardless of the method used. A clear correlation was found between acceptable strain energy and ligand flexibility, while there was no correlation between strain energy and binding affinity, thus indicating that expensive conformational rearrangements can be tolerated in some cases without overly penalizing the tightness of binding. On the basis of the trends observed, thresholds for the acceptable strain energies of bioactive conformations were defined with consideration of the impact of ligand flexibility. An analysis of the degree of folding of the bound ligands confirmed the general tendency of small molecules to bind in an extended conformation. The results suggest that the unfolding of hydrophobic ligands during binding, which exposes hydrophobic surfaces to contact with protein residues, could be one of the factors accounting for high reorganization energies. Finally, different methods for conformational analysis were evaluated, and guidelines were defined to maximize the prevalence of bioactive conformations in computationally generated ensembles.

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Article Views: 2,898 Times
Received 6 November 2003
Published online 7 April 2004
Published in print 1 May 2004
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