A CoMFA analysis with conformational propensity: An attempt to analyze the SAR of a set of molecules with different conformational flexibility using a 3D-QSAR method

CoMFA analysis, a widely used 3D-QSAR method, has limitations to handle a set of SAR data containing diverse conformational flexibility since it does not explicitly include the conformational entropic effects into the analysis. Here, we present an attempt to incorporate the conformational entropy effects of a molecule into a 3D-QSAR analysis. Our attempt is based on the assumption that the conformational entropic loss of a ligand upon making a ligand-receptor complex is small if the ligand in an unbound state has a conformational propensity to adopt an active conformation in a complex state. For a QSAR analysis, this assumption was interpreted as follows: a potent ligand should have a higher conformational propensity to adopt an `active-conformation'-like structure in an unbound state than an inactive one. The conformational propensity value was defined as the populational ratio, Nactive/Nstable, of the number of energetically stable conformers, Nstable, to the number of `active-conformation'-like structures, Nactive. The latter number was calculated by counting the number of conformers that satisfied the structural parameters deduced from the active conformation. A set of SAR data of imidazoleglycerol phosphate dehydratase inhibitors containing 20 molecules with different conformational flexibility was used as a training set for developing a 3D structure-activity relationship by a CoMFA analysis with the conformational propensity value. This resulted in a cross-validated squared correlation coefficient of the CoMFA model with the conformational propensity value (R2cross = 0.640) higher than that of the standard CoMFA model (R2cross = 0.431). Then we evaluated the quality of the CoMFA models by predicting the inhibitory activity for a new molecule.

[1]  Glen Eugene Kellogg,et al.  HINT: A new method of empirical hydrophobic field calculation for CoMFA , 1991, J. Comput. Aided Mol. Des..

[2]  C. Lemmen,et al.  FLEXS: a method for fast flexible ligand superposition. , 1998, Journal of medicinal chemistry.

[3]  A. Ghose,et al.  Prediction of Hydrophobic (Lipophilic) Properties of Small Organic Molecules Using Fragmental Methods: An Analysis of ALOGP and CLOGP Methods , 1998 .

[4]  W. Guida,et al.  Probing the conformational space available to inhibitors in the thermolysin active site using Monte Carlo/energy minimization techniques , 1992 .

[5]  Thomas Lengauer,et al.  Time-efficient flexible superposition of medium-sized molecules , 1997, German Conference on Bioinformatics.

[6]  W. C. Krueger,et al.  Thermodynamics of the interaction of inhibitors with the binding site of recombinant human renin. , 1990, Journal of medicinal chemistry.

[7]  Yvonne C. Martin,et al.  A fast new approach to pharmacophore mapping and its application to dopaminergic and benzodiazepine agonists , 1993, J. Comput. Aided Mol. Des..

[8]  R. Cramer,et al.  Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins. , 1988, Journal of the American Chemical Society.

[9]  Patrick Gaillard,et al.  Molecular Lipophilicity Potential, a tool in 3D QSAR: Method and applications , 1994, J. Comput. Aided Mol. Des..

[10]  G. Chang,et al.  An internal-coordinate Monte Carlo method for searching conformational space , 1989 .

[11]  C. Earnshaw,et al.  Synthesis of Inhibitors of Imidazole Glycerol Phosphate Dehydratase. , 1996 .

[12]  A. Hopfinger,et al.  Construction of 3D-QSAR Models Using the 4D-QSAR Analysis Formalism , 1997 .

[13]  Garland R. Marshall,et al.  3D-QSAR of angiotensin-converting enzyme and thermolysin inhibitors: A comparison of CoMFA models based on deduced and experimentally determined active site geometries , 1993 .

[14]  Jonas Boström,et al.  Conformational energy penalties of protein-bound ligands , 1998, J. Comput. Aided Mol. Des..

[15]  Hugo Kubinyi,et al.  3D QSAR in drug design : theory, methods and applications , 2000 .