Development and Validation of AMANDA, a New Algorithm for Selecting Highly Relevant Regions in Molecular Interaction Fields

Descriptors based on Molecular Interaction Fields (MIF) are highly suitable for drug discovery, but their size (thousands of variables) often limits their application in practice. Here we describe a simple and fast computational method that extracts from a MIF a handful of highly informative points (hot spots) which summarize the most relevant information. The method was specifically developed for drug discovery, is fast, and does not require human supervision, being suitable for its application on very large series of compounds. The quality of the results has been tested by running the method on the ligand structure of a large number of ligand-receptor complexes and then comparing the position of the selected hot spots with actual atoms of the receptor. As an additional test, the hot spots obtained with the novel method were used to obtain GRIND-like molecular descriptors which were compared with the original GRIND. In both cases the results show that the novel method is highly suitable for describing ligand-receptor interactions and compares favorably with other state-of-the-art methods.

[1]  Ismael Zamora,et al.  Discriminant and quantitative PLS analysis of competitive CYP2C9 inhibitors versus non-inhibitors using alignment independent GRIND descriptors , 2002, J. Comput. Aided Mol. Des..

[2]  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.

[3]  Gabriele Cruciani,et al.  Molecular interaction fields : applications in drug discovery and ADME prediction , 2005 .

[4]  W. J. Studden,et al.  Theory Of Optimal Experiments , 1972 .

[5]  G. Caron,et al.  A combined in silico strategy to describe the variation of some 3D molecular properties of beta-cyclodextrin due to the formation of inclusion complexes. , 2006, Journal of molecular graphics & modelling.

[6]  S. Pickett,et al.  GRid-INdependent descriptors (GRIND): a novel class of alignment-independent three-dimensional molecular descriptors. , 2000, Journal of medicinal chemistry.

[7]  David S. Wishart,et al.  DrugBank: a knowledgebase for drugs, drug actions and drug targets , 2007, Nucleic Acids Res..

[8]  T. Blundell,et al.  Probing hot spots at protein-ligand binding sites: a fragment-based approach using biophysical methods. , 2006, Journal of medicinal chemistry.

[9]  Maria I. Zavodszky,et al.  Distilling the essential features of a protein surface for improving protein-ligand docking, scoring, and virtual screening , 2002, J. Comput. Aided Mol. Des..

[10]  Andy Vinter,et al.  Molecular Field Extrema as Descriptors of Biological Activity: Definition and Validation , 2006, J. Chem. Inf. Model..

[11]  P. Goodford A computational procedure for determining energetically favorable binding sites on biologically important macromolecules. , 1985, Journal of medicinal chemistry.

[12]  Ferran Sanz,et al.  Incorporating molecular shape into the alignment-free Grid-Independent Descriptors. , 2004, Journal of medicinal chemistry.