PREDICTIVE BINDING OF BETA-CARBOLINE INVERSE AGONISTS AND ANTAGONISTS VIA THE COMFA GOLPE APPROACH

The synthesis and affinities of six new 3-substituted beta-carbolines (6-10,12) for the benzodiazepine receptor (BzR) are described. These analogs were used both to probe the dimensions of the hydrophobic pocket in the benzodiazepine receptor and to test the predictive ability of a previously reported 3D-QSAR regression model. Of the new analogs synthesized, the gamma-branched derivatives (isobutoxy, 7, IC50 = 93 nM; isopentoxy, 9, IC50 = 104 nM) display significantly higher affinity for the BzR than either the beta-branched (sec-butoxy, 6, IC50 = 471 nM; tert-butyl ketone, 12, IC50 = 358 nM) or delta-branched (isopentoxy, 8, IC50 = 535 nM) analogs. An exception to this rule is the gamma-branched 3-benzyloxy derivative 10 (IC50 > 1000 nM) which appears to have a chain length that is too long to be accommodated by the BzR. The standard error of prediction for these six new beta-carbolines using the original regression model is significantly lower than the standard error estimate of the cross validation runs on the training set, hence the predictions made using this model are much better than expected. In order to obtain more credible predictions, a new procedure called GOLPE (generating optimal linear PLS estimates) was used to eliminate irrelevant electrostatic and steric descriptors from the regression equation. A substantial reduction in the standard error estimate resulted. The predictions from this new regression equation were somewhat less accurate than the ones obtained with the original regression equation; however the standard error of prediction and the standard error estimate are in much closer agreement. Finally, to probe the effect that the quality of the steric and electrostatic potentials has on 3D-QSAR analyses, the semiempirical MNDO//PRDDOE geometries and Mulliken charges used in the original analyses were replaced with ab initio 3-21G//6-31G* geometries and electrostatic potential fit charges. A modest decrease in the standard error estimate and increase in cross validated R2 resulted.