Variable selection and specification of robust QSAR models from multicollinear data: arylpiperazinyl derivatives with affinity and selectivity for alpha2-adrenoceptors.
Two QSAR models have been identified that predict the affinity and selectivity of arylpiperazinyl derivatives for alpha1 and alpha2 adrenoceptors (ARs). The models have been specified and validated using 108 compounds whose structures and inhibition constants (Ki) are available in the literature [Barbaro et al., J. Med. Chem., 44 (2001) 2118; Betti et al., J. Med. Chem., 45 (2002) 3603; Barbaro et al., Bioorg. Med. Chem., 10 (2002) 361; Betti et al., J. Med. Chem., 46 (2003) 3555]. One hundred and forty-seven predictors have been calculated using the Cerius 2 software available from Accelrys. This set of variables exhibited redundancy and severe multicollinearity, which had to be identified and removed as appropriate in order to obtain robust regression models free of inflated errors for the beta estimates - so-called bouncing betas. Those predictors that contained information relevant to the alpha2 response were identified on the basis of their pairwise linear correlations with affinity (-log Ki) for alpha2 adrenoceptors; the remaining variables were discarded. Subsequent variable selection made use of Factor Analysis (FA) and Unsupervised Variable Selection (UzFS). The data was divided into test and training sets using cluster analysis. These two sets were characterised by similar and consistent distributions of compounds in a high dimensional, but relevant predictor space. Multiple regression was then used to determine a subset of predictors from which to determine QSAR models for affinity to alpha2-ARs. Two multivariate procedures, Continuum Regression (the Portsmouth formulation) and Canonical Correlation Analysis (CCA), have been used to specify models for affinity and selectivity, respectively. Reasonable predictions were obtained using these in silico screening tools.
Salt
D W
DW
The Centre for Molecular Design, IBBS, University of Porthsmouth, Porthsmouth POI 2D Y, UK.
Maccari
L
L
Botta
M
M
Ford
M G
MG
D008958:Models, Molecular; D010879:Piperazines / Q000737:chemistry*; D021281:Quantitative Structure-Activity Relationship; D018341:Receptors, Adrenergic, alpha-2 / Q000737:chemistry*
D010879:Piperazines; D018341:Receptors, Adrenergic, alpha-2
J Med Chem. 2003 Jul 31;46(16):3555-8
12877594
J Chem Inf Comput Sci. 2000 Sep-Oct;40(5):1160-8
11045809
Trends Pharmacol Sci. 1994 Jun;15(6):167-70
7916507
Prog Drug Res. 1996;47:81-130
8961765
Urol Clin North Am. 1990 Aug;17(3):641-9
1695784
J Androl. 1991 Nov-Dec;12(6):389-94
1722795
Trends Pharmacol Sci. 1989 Dec;Suppl:26-30
2559516
J Med Chem. 2002 Aug 15;45(17):3603-11
12166933
J Med Chem. 2001 Jun 21;44(13):2118-32
11405649
FASEB J. 1989 May;3(7):1825-32
2541037
Prog Med Chem. 1986;23:1-39
2889241
Bioorg Med Chem. 2002 Feb;10(2):361-9
11741785
Trends Pharmacol Sci. 1992 Jul;13(7):277-82
1354903