Pharmacophore determination process

Defining a pharmacophore model upon a ligand has the advantage that this way the individual features are already correctly aligned in space. In order to account for the great 

FIGURE 28.9 Phanmct hoic features defined based on compound 1. (Red sphere = any positively charged element, orange sphere = aromatic or hydrophobic group, cyan sphere = aromatic ring). 

Apparently, the derived pharmacophore model is too loose-fitting for screening a compound database. Thus, the 

CHAPTER 28 Pharmacophore Identification and Pseudo-Receptor Modeling 

FIGURE 28.10 Pharmacophore model based on compound 1 including the shape feature (van der Waals volume) and the two forbidden volumes (black spheres). 

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The ultimate test of the objectivity of the process of pharmacophore discovery is that these results should conform to the physical reality of the receptor, as determined by independent biophysical experimentation. For example, the standard pharmacophore determined by DANTE for most GPCRs contains a basic amine separated by 5-7 A from an aromatic ring. These groups interact with the conserved Asp on helix III and conserved aromatic residues on helices VI and VII in most protein models of GPCRs. 

In the course of the pharmacophore identification process, clearly two different steps have to be taken in succession. First, a conformational analysis has to be carried out. After this initial step, a common three-dimensional arrangement of functional groups is determined through a superpositioning procedure. During the second step this preliminary sterical pharmacophore model has to be checked and consolidated by electron density calculations and establishment of the corresponding molecular electrostatic potentials (MEPs). 

An alternative metric to describe 3-D properties of molecules is discussed by Ashton et al.26 In their approach, a pharmacophore fingerprint is used in conjunction with conformational searching to determine possible 3-D shapes that molecules can adopt. Tools from Tripos and CDL are available to carry out this type of analysis. However as with other methods there are limitations, the completeness of conformational searching being one. Perhaps the most important limitation of the approach is that it has a tendency to pick the most flexible molecules (that set the most pharmacophore bits). In a lead discovery experiment, following up on flexible molecules can be a long and sometimes fruitless process. 

The pharmacophore concept plays a very important role in guiding the drug discovery process. Pharmacophore models help medicinal chemists gain an insight into the key interactions between ligand and receptor when the receptor structure has not been determined experimentally. A pharmacophore can be used as a basis for the alignment rules in 3D-QSAR analysis for the lead compound optimization... 

LiBrain (103) is a collection of software modules for automated combinatorial library design, including the incorporation of desirable pharmacophoric features and the optimization of the diversity of designed libraries. A Chemistry Simulation Engine module is trained by chemists to determine the suitability of reactants for a specified reaction, to recognize the risk of undesirable side reactions, and to predict the structures of the most likely reaction products, so as to circumvent major bottlenecks associated with automating the process. 

As mentioned Sec. 1, a pharmacophore represents an objective description of what is required for activity, and pharmacophore discovery should represent an objective way of determining that pharmacophore. It is difficult to discern how objective this process has been in the applications Sec. 5.5 (i.e., to determine how much user bias was injected into selecting which of the many pharmacophores consistent with the SAR was chosen). User bias is not necessarily bad —in the hands of a skilled practitioner, this allows judgments to be made based on data from a variety of sources. But, ultimately, this field will best advance if different noncommunicating users applying the same method to the same data achieve the same final result. 

Fig. 28.14. A general process for the rational design of peptide mimetics (A) identification of crucial pharmacophoric groups, (B) determination of the spatial arrangement of these groups, and (C) use of a template to mount the key functional groups in their proper conformation. Groups highlighted with an asterisk comprise the pharmacophore of the heptapeptide. (From Harrold MW. Preparing students for future therapies the development of novel agents to control the renin-angiotensin system. Am J Pharm Educ 1997 61 173-178 with permission.)...

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