Pharmacophore protein-based

Metabolism is still a barrier to be overcome. Some QSAR, pharmacophore, protein, and rule-based models are available to predict substrates and inhibitors of a specific cytochrome P450 isoenzyme [47-55]. 

The multidisciplinary approach described above has been used to study protein folding phenomena and protein SARs for protein engineering endeavors, as well as protein-based and pharmacophore drug design. The validity of the predicted structure obviously depends on many factors, including the accuracy of the structures... 

A computational elucidation of putative binding sites using the PASS algorithm revealed an internal site as most interesting for small organic molecules to interact with [49], Subsequent more detailed analysis resulted in the derivation of a protein-based pharmacophore (Figure 8.8). 

Several researchers have exploited the wealth of crystal structures of kinase inhibitor complexes to build protein-based pharmacophores for this target class (20). Aronov and Murcko (21) considered the crystal structures of four promiscuous kinase inhibitors, i.e., inhibitors with an affinity of at least 2 pM on five representative kinases. After aligning the structures of the four proteins, they assigned pharmacophoric features to the bound inhibitors, which led to the identification of five clusters of pharmacophoric features. These served to define a five point pharmacophore for kinase frequent hitters (Fig. la). This pharmacophore could discriminate frequent hitters from selective kinase inhibitors. Recently, McGregor (22) aligned 220 kinase crystal structures from the PDB and assigned one of seven possible pharmacophoric types to each atom of the bound ligands. 

Another computational search was performed using a pharmacophore model based on the crystal structure of MDM2 with incorporation of protein flexibility assessed using molecular dynamics simulation [47]. Pharmacophore searching was performed on a database of 35,000 synthetic compounds, followed by evaluation of 24 hits in a fluorescence-polarization MDM2 binding assay that led to the discovery of five non-peptidic, small-molecule MDM2 inhibitors with new scaffolds. 

FIGURE 28.2 (a) Comparison of the pharmacophore-based aUgnment of dihydrofolate reductase Ugands and (b) the experimentally derived protein-based alignment. 

Fig. 6.5 Proliferator-activated receptor (PPARy) partial agonist pharmacophore. Structure-based common pharmacophore derived ifom the alignment of PPARy partial agonists. The pharmacophore is formed by one hydrogen bond acceptor (API) coloured in pink and three hydrophobic sites (HPl, HPl saaAHPS) coloured in gKen. The ligand amorfrutin B (fiom the protein data bank (PDB) entry 4A4W) is also represented as a spatial reference. The pharmacophore was generated by Phase (Schrodinger)...

Since the summation in Eq. (12) may be on any subset of atoms, it can be fine-tuned to best suit the problem at hand. The summation may be over the whole molecule, but it is very common to calculate conformational distances based only on non-hydrogen heavy atoms or, in the case of proteins, even based on only the backbone Ca atoms. Alternatively, in a study related to drug design one may consider, for example, focusing only on atoms that make up the pharmacophore region or that are otherwise known to be functionally important. 

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