STERIMOL variable

The Kd(X) values thus obtained (Table 3) were analyzed by the multivariant technique using such parameters as n, a0, Bt, Ibmch, and Ihb, where Bj is a STERIMOL parameter showing the minimum width of substituents from an axis connecting the a-atom of the substituents and the rest of molecule, and Ibrnch, an indicator variable representing the number of branches in a substituent. 

It Is Interesting that In the Individual substituent positions molar volume (MR) was found to be the relevant parameter rather than ff. Eg or the STERIMOL descriptors. This fact and the positive coefficients for MR suggest that the enzyme-Inhibitor Interaction proceeds via London dispersion forces (31, ) and the binding to the enzyme Is favored If the bulky substituents are In meta or para positions, which Is In accordance with the earlier results (11). The parameter H-DO In position I seems to be Important In the regression. It systematically appears In each equation. Its path coefficient and partial r value, however. Is relatively low compared to those of Jit and MRjjj. In addition, the H-DOj variable Is not very useful because these Indicator parameters are the most poorly defined and the number of proton donor substituents (H-DO-1) Is rather small. 

In our earlier equation in ref. (2) dealing with p-nitrophenols ( pIcQ = -0.39 + 2.01B1-1 + 0.97B3-2) two Sterimol parameters provided excellent statistics (n =33, r = 0.97, s = 0.25, f = 217, p <0.0001), whereas in this case we need an additional electronic parameter (o-p). This, however, depends largely on the composition of our present data set. The p-nitrophenol series consisted of compounds which had some electronic variability ortho to the OH-group (H, Cl,... 

Sigma-rho corrections were assigned equally to the substituents at positions 6 and 7. Revised STERIMOL (L, B1 and B5) parameters were calculated following established methods.f27.28l The data matrices consist of lipophilicity (F), molar refractivity (MR), STERIMOL (L, Bl, B5) parameters and de novo indicator variables for substituents in positions 1, 6 and 7. The contribution to the partition coefficient by the substituents at positions 6 and 7 were summed, 2F(6,7), as were the molar refractivity contributions, 2MR(6,7). These two sets of summed variables paralleled a similar approach used by Koga in his QSAR analysis of a set of quinoline derivatives. (231 At the same time, the limitations that apply to summed n values, particularly where there is a significant a-p interaction were kept in mind.f22.29.301 The latter is represented as API in the data tables and its significance was evaluated in some of the regression models. In order to check for parabolic relationships, squared terms for the partition coefficient, molar refraction, and STERIMOL parameters were evaluated. 

Group 4. The benzyl derivatives. These compounds are the most difficult to model. Of those investigated, AMR, and the Sterimol parameter Bj appear to be the best variables, as shown in equation 4. 

In this exercise, we compare MLR and SVMR QSAR models for the benzodiazepine receptor affinity of 52 2-aryl(heteroaryl)-2,5-dihydropyrazo-lo[4,3-c]quinolin-3-(3H)-ones (Figure 53). Both models were developed with five structural descriptors, namely the Hammett electronic parameter Qr, the molar refractivity MRrs, the Sterimol parameter Lr<4<, an indicator variable 7 (1 or 0) for 7-substituted compounds, and the Sterimol parameter The MLR model has a calibration correlation coefficient of 0.798 and fairly good prediction ability ... 

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