Feature-based fingerprints

Often, all alignment-based methods and molecular field and potential calculations are classified as pharmacophore perception techniques. We will include most of these methods in this review however, when using the term pharmacophore model, we will be referring mainly to one specific type of perception, namely three-dimensional feature-based pharmacophore models represented by geometry or location constraints, qualitative or quantitative. An extrapolation of the pharmacophore approach to a set of multi-dimensional descriptors (pharmacophore fingerprints) has been developed mostly for library design and focusing purposes [3-8]. 

Fig. 2e), virtually absent in perfect siUcalite-1 and immediately identified as a fingerprint of TS-1 material [37,52-55,63,70,71]. A qualitative correlation between the intensity of the infrared band at 960 cm and Ti content has been observed since the first synthesis of TS-1. Indeed, the occurrence of that band is one of the distinctive features of the material cited in the original patent [7]. However, the quantitative correlation has been reported only very recently by Ricchiardi et al. [52], owing to very serious experimental problems related to the saturation of the IR framework modes, hi the same work, the nature of the 960 cm band has been discussed in terms of theoretical calculations based on both cluster and periodical approaches. 

Clearly, within the conceptual framework described above, there is extensive room for exploration in creating fingerprints and similarity measures to retrieve molecules based on varying conceptions of similarity [42—441. The simplest types of fingerprint consist simply of features indices that map the presence or absence of a small library of functional groups. The most well known and effective are the MACCS keys. These were initially chemical feature indices, that we later used successfully as a similarity metric. 

Another family of fingerprints available are the MOE pharmacophore fingerprints accessible through software from the Chemical Computing group [51]. In this system, the atoms are generalized into a smaller vocabulary of pharmacophore features, after which the fingerprint is constructed based on connected paths. 

The Accelrys implementation of pharmacophore fingerprint descriptors is called 3D Keys. This application is based on standard Catalyst feature definitions and is a part of the Cerius2 software package [7]. 

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