Pharmacophore Visualization

LigandScout pharmacophores solely consist of chemical features classified as layers 3 and 4 (Table 6.2). Visualization mainly distinguishes between point and vector features point features (layer 4) are defined as a center with a tolerance this group encompasses hydrophobic, positively ionizable and negatively ioniz-able areas, in addition to excluded volume spheres. Hydrogen donors, acceptors and donor-acceptor pairs belong to the vector features group. 

Point features are rendered as spheres with different colors to differentiate them (Fig. 6.5) hydrophobic/lipophilic features are drawn in yellow and positive and negative ionizable features are drawn in red and blue, respectively. Excluded volume spheres use a dark gray color to signify their meaning. 

Spheres are drawn as semi-transparent objects, with a wire frame on their surface to enhance the impression of depth and to make it easier to judge the size of the spheres in the third dimension (Fig. 6.6). 

Vector features are drawn as three-dimensional pointers or as a pair of two opposing pointers in the case of a donor-acceptor pair. 

Any visible object in the visualization may be selected for subsequent user interaction. The distinction between core and environment is useful to restrict the pickable objects to either group. This is especially important when selecting an entire region, because it is likely that unwanted objects in front of or behind the desired ones would otherwise be included in the selection. 

---

These pharmacophore techniques are different in format from the traditional pharmacophore definitions. They can not be easily visualized and mapped to the molecular structures rather, they are encoded as keys or topological/topographical descriptors. Nonetheless, they capture the same idea as the classic pharmacophore concept. Furthermore, this formalism is quite useful in building quantitative predictive models that can be used to classify and predict biological activities. 

Enzyme-inhibitor design, genetic software techniques for, 10 342 Enzyme inhibitor implants, 10 343 Enzyme-inhibitor interactions, visualization of, 10 340 Enzyme-inhibitor models, based on pharmacophores, 10 333 Enzyme inhibitors, 10 317-346 biological effects of, 10 328... 

The final library was designed with the purpose of adding incremental diversity to the first three fragment libraries. The main filtering criterion was novel pharmacophoric triangles not found in the first three libraries. After clustering and visual inspection from a panel of medicinal chemists, only 65 compounds were purchased and 61 compounds passed QC. 

Phase is the pharmacophore generation module provided by Schrodinger [82]. Like other modules available from Schrodinger, Phase uses the Maestro interface [83] as the visualization tool. Maestro provides a molecule sketcher and all the common molecular file formats are supported. 

Partial mapping of the molecules on a pharmacophore model is allowed. At this stage, pharmacophore models and alignments can be visualized. Excluded volumes can be added manually after having aligned the inactive molecules on the pharmacophore models. 

SCAMPI (Statistical Classification of Activities of Molecules for Pharmacophore Identification) is a program developed in C language by Chen et al. [104]. According to the authors, it allows the use of datasets of approximately 1000-2000 compounds. The SCAMPI program s implementation has been done to allow users to visualize the molecules and the generated pharmacophores in the Sybyl environment. 

Figure 2.34. Ligand, methotrexate bound to the protein dihydrofolate reductase visualized in MarvinSpace. Detailed view of the binding pocket. The surface is colored by residue type and it is transparent. Behind it the ball and stick representation of the protein is seen. Lengths of some hydrogen bonds are monitored. Two pharmacophore regions are also defined an acceptor (red sphere) and a hydrophobic region (large yellow sphere), these are also semi-transparent. Image courtesy of ChemAxon...

---