Three-dimensional quantitative structure-activity relationship methods

Ekins S, De Groot MJ, Jones JP. Pharmacophore and three-dimensional quantitative structure activity relationship methods for modeling cytochrome P450 active sites. Drug Metab Dispos 2001 29 936-44. [Pg.348]

Agarwal, A., Pearson, P. P., Taylor, E. W., Li, H. B., Dahlgren, T., Herslof, M., et al. Three-Dimensional Quantitative Structure-Activity Relationships of 5-HT Receptor Binding Data for Telrahydropyridinyl Derivatives A Comparison of the Hansch and CoMFA Methods../. Med. Chem. 1993,36, 4006-4014. [Pg.320]

The next step was made by Klebe et al. [50]. Two 3D-QSAR methods were applied to get three-dimensional quantitative structure-activity relationships using a training set of 72 inhibitors of the benzamidine type with respect to their binding affinities toward Factor Xa to yield statistically reliable models of good predictive power [51-54] the widely used CoMFA method (for steric and electrostatic properties) and the comparative molecular similarity index analysis (CoMSlA) method (for steric, electrostatic, hydrophobic, hydrogen bond donor, and hydrogen bond acceptor properties). These methods allowed the consideration of various physicochemical properties, and the resulting contribution maps could be intuitively interpreted. [Pg.9]

So, S.-S. and Karplus, M. (1997a). Three-Dimensional Quantitative Structure-Activity Relationships from Molecular Similarity Matrices and Genetic Neural Networks. 1. Method and Validations. J.Med.Chem., 40,4347-4359. [Pg.648]

THREE-DIMENSIONAL QUANTITATIVE STRUCTURE-ACTIVITY relationship (3D-QSAR) method that uses statistical correlation techniques for the analysis of (a) the quantitative relationship between the biological activity of a set of compounds with a specified alignment and (b) their three-dimensional electronic and steric properties. Other properties such as hydrophobicity and hydrogen bonding can also be incorporated into the analysis. [Pg.54]

B6hm M, StuNrzebecher J, Klebe G (1999) Three-Dimensional quantitative structure-activity relationship analyses using comparative molecular field analysis and comparative molecular similarity indices analysis to elucidate selectivity differences of inhibitors binding to trypsin, thrombin, and factorXa. JMed Chem42(3) 458 77. doi 10.1021/jm981062r Besler BH, Merz KM, Kollman PA (1990) Atomic charges derived from semiempirical methods. J Comp Chem 11(4) 431 39. doi 10.1002/jcc.540110404... [Pg.457]

Ghose AK, Crippen GM. Modeling the benzodiazepine receptor binding site by the general three-dimensional structure-directed quantitative structure-activity relationship method REMOTEDISC. Mol Pharmacol 1990 37 725-734. [Pg.610]

Three-dimensional quantitative structure-aaivity relationships (3D-QSARs) are quantitative models that relate the biological activity of small molecules with their properties calculated in 3D space.All 3D-QSAR methods combine molecular modeling and statistical analysis of the relative biological potency within a set of compounds. In this chapter, we provide... [Pg.183]

A. K. Ghose and G. M. Crippen, Mol. Pharmacol., 37, 725 (1990). Modeling the Benzodiazepine Receptor Binding Site by the General Three-Dimensional Structure-Directed Quantitative Structure-Activity Relationship Method REMOTEDISC. [Pg.235]

In recent years, three-dimensional quantitative structure biological activity relationship methods known as comparative molecular field analysis (CoMFA) has been applied to construct a 3D-QSRR model for prediction of retention data. The CoMFA 3D-QSRR model is obtained by systematically sampling the steric and electrostatic fields surrounding a set of analyte molecules. Next, the differences in these fields are correlated to the corresponding differences in retention. The CoMFA model was successfully applied to HPLC retention data of polycyclic aromatic hydrocarbons [60]. [Pg.527]

In addition, traditional quantitative structure-activity relationship (QSAR) models were reported. Gozalbes et al. attempted to predict the blood-brain barrier permeabilities of four arylacetamides using linear discriminant analysis [65], while Medina-Franco et al. discriminated between active and inactive BCG compounds using two-dimensional (2D) and three-dimensional (3D) structural-similarity methods [66]. [Pg.286]