Pharmacophore discovery applications

Langer, T., Hoffmann, R. D. Pharmacophore modeling applications in drug discovery. Exp. Opin. Drug Discov. 2006,1, 261-267. 

The final general aspect of pharmacophore discovery that must be stressed is that, fundamentally, this is a method of inference. By contrast, quantum mechanics is deductive, in that one begins with the laws of quantum mechanics to deduce consequences, the correctness of which is guaranteed by those laws. The results of inference cannot be guaranteed to be correct. Their validity can only be determined by their successful prospective application, prospective emphasizing that these models must be applied to molecules never before seen by the computational scientist. 

Despite the immaturity of these methodologies of pharmacophore discovery, a tremendous variety of apparently successful applications have appeared in the literature. What follows is only a selection of these applications, focusing on applications relevant to drug discovery, categorized by the type of receptor being studied. 

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. 

Langer, T. and Hoffmann, R.D. (2006) Pharmacophore modelling applications in drug discovery. Expert Opinion on Drug Discovery, 1, 261-267. 

The question that needs to be addressed is at what stage is filtering for drug-likeness truly beneficial and how should the filters be used In early lead discovery there are some specific requirements regarding the predictive models used. Since they should be applied to many compounds, their application must be reasonably fast. This typically excludes all models involving pharmacophore matching, force... 

The success of the pharmacophore approach in drug discovery no longer needs to be demonstrated. This book is an additional testimony to this. Successful pharmacophore investigations, however, have unavoidably passed a key step prior to application validation. What we have tried to show throughout this chapter is that this critical stage depends on three practical considerations. 

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