Pharmacophore four-point

Applying supervised machine learning techniques, Li et al. [66] proposed a model that differentiates substrates from nonsubstrates of P-gp based on a simple tree using nine distinct pharmacophores. Four-point 3D pharmacophores were employed to increase the amount of shape information and resolution and possessed the ability to distinguish chirality. Relevant features were hydrogen-bond acceptors, hydrophobic-ity indices, and a cationic charge. 

To derive an ACE pharmacophore, four points were defined for each molecule. The derivation of these four points for captopril is shown in Figure 12.8. Five distances (also shown in Figure 12.8) were defined between these four points. Note that one of the points corresponds to the presumed location of the enzyme s zinc atom. The number of rotatable bonds in each inhibitor varied between 3 and 9 and the molecules were considered in order of increasing number of rotatable bonds. The entire conformational space was explored for the first (most... 

Mason, J.S. and Beno, B.R. Library design using BCUT chemistry-space descriptors and multiple four-point pharmacophore fingerprints simultaneous optimization and structure-based diversity. /. Mol. 

Fig. 15.25 Partial display of virtual screen of conformational ensemble of " 75 000 structure library based on multiple templates. A display of fitness scores to a three-point pharmacophore model provides initial signs of similarity of a library design to that model. Subsequent virtual screening against a more stringent four-point pharmacophore model further highlights potentially useful library designs.

If the bioactive conformation of a ligand for a particular receptor is known, then a single three- or four-point 3D pharmacophore that is crucial for the... 

Fig. 1. Schematic illustrating three- and four-point 3D pharmacophores. Three-point 3D pharmacophores encode three functional group types and the three distances separating them, and four-point 3D pharmacophores encode four functional group types and the six distances separating them. Functional group types commonly included are acids, bases, hydrophobes, H-bond acceptors, H-bond donors, and aromatic systems. Distances are assigned to bins (e.g., 2.5-4.0 A) to limit the individual 3D pharmacophore descriptors to a tractable number, and to aid in comparing the individual 3D pharmacophores.

The receptor relevance of BCUT descriptors has inspired several groups to apply them in conjunction with other methods. Beno and Mason reported the use of simulated annealing to optimize library design using BCUT chemistry space and four-point pharmacophores concurrently (33) and the use of chemistry spaces in conjunction with property profiles (52). The application of such composite methods to target class library design is readily apparent. Pirard and Pickett reported the application of the chemometric method, partial least squares discriminant analysis, with BCUT descriptors to successfully classify ATP-site-directed kinase inhibitors active against five different protein kinases... 

Three-point pharmacophores have traditionally been used for many applications but have recently been more and more replaced by four-point pharmacophores (Mason et al. 1999), which increases the complexity of the search but also the resolution of the pharmacophore analysis. This is the case because the additional point increases the total number of inter-point distances from three for a three-point pharmacophore to six for a four-point pharmacophore. Pharmacophore searching is further refined by assigning alternative features to each point (e.g., hydrogen bond acceptors, donors, or charged groups) and ranges to inter-point distances (rather than an exact distance). For example, five different features (e.g., atom types or groups) may be permitted for each point... 

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