High hit rate

These results certainly appear very promising and reassuring in terms of our computational strategies, which emphasize that rigorous validation of QSAR models as well as conservative extrapolation are responsible for a very high hit rate (Tables 16.1 and 16.2). However, additional developments of methodology are certainly required to improve model accuracy since quantitative agreement between actual and predicted anticonvulsant activity is not excellent. 

Fig. 16.5 Computer-aided drug discovery workflow based on combination of QSAR modeling and consensus database mining as applied to the discovery of novel anticonvulsants [10]. The workflow emphasizes the importance of model validation and applicability domain in ensuring high hit rates as a result of database mining with predictive QSAR models.

Fig. 11.4. Targets with observed high (>2%, light bars) and low (<2%, darker bars) Class 1 hit rates compared to the druggability score (Dscore) calculated by SiteMap. The red arrow indicates the minimum Dscore for targets yielding high hit rates for the current data set. With kind permission from Springer Science+Business Media Journal of Computer-Aided Molecular Design, 23, 2009, 603, l-Jen Chen and Roderick...

Polysaccharides are another class of macromolecules that can interfere with cellular and enzyme assays, as demonstrated during the NCI campaign to discover anti-HIV agents from natural sources. Anionic polysaccharides show anti-HIV activity and, to avoid a too high hit rate, had to be removed by 50% aqueous ethanol precipitation.72... 

Figure 9.4 Example substructures with high hit rates. PRI=Promiscuity Ratio Index (see text for explanation). A represents any atom that can form part of an aromatic structure.

The examples demonstrate opportunities of computer-assisted optimization in library design. The quality of combinatorial Hbraries can be improved by computing similarities of virtual compounds or by estimation of activities [9, 136]. However, high diversity and high hit rates are usually not attainable in one library, and must be addressed in different design steps. 

This latter computational approach is computationally more demanding compared with much faster geometry-based and/or energy-based computational methods [58, 59]. Nevertheless, it confirms the very important observation that dmggable cavities can accommodate low molecular weight fragments with high hit rates. 

Figure11.5 Sequentialoriterativescreeningschemestointegratecomputational and HTSefforts. Combining virtual screening and HTS in one or more iterations is expected to yield high hit rates while considerably reducing the experimental effort.

The purpose of virtual screening is to come up vdth hits of novel chemical stracture that bind to the macromolecular target of interest. Thus, success of a virtual screen is defined in terms of finding interesting new scaffolds rather than many hits. Interpretations of VS accuracy should therefore be considered with caution. Low hit rates of interesting scaffolds are clearly preferable over high hit rates of already known scaffolds. 

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