An Extensive and Diverse Set of Molecular Overlays
for the Validation of Pharmacophore Programs
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Abstract
The pharmacophore hypothesis plays
a central role in both the design
and optimization of drug-like ligands. Pharmacophore patterns are
invoked to explain the binding affinity of ligands and to enable the
design of chemically distinct scaffolds that show affinity for a protein
target of interest. The importance of pharmacophores in rationalizing
ligand affinity has led to numerous algorithms that seek to overlay
ligands based on their pharmacophoric features. All such algorithms
must be validated with respect to known ligand overlays, usually by
extracting ligand overlay sets from the Protein Data Bank (PDB). This
validation step creates the problem of which of the known overlays
to select and from which proteins. The large number of structures
and protein families in the PDB makes it difficult to establish a
definitive overlay set; as a result, validation studies have rarely
employed the same data sets. We have therefore undertaken an exhaustive
analysis of the RCSB PDB to identify 121 distinct ligand overlay sets.
We have defined a robust protein overlay protocol, which is free from
subjective interpretation over which residues to include, and we have
analyzed each overlay set on the basis of whether they provide evidence
for the pharmacophore hypothesis. Our final data set spans a broad
range of structural types and degrees of difficulty and includes overlays
that any algorithm should be able to reproduce, as well as some for
which there is very weak evidence for a conserved pharmacophore at
all. We provide this set in the hope that it will prove definitive,
at least until the PDB is greatly enriched with further structures
or with radically different protein folds and families. Upon publication,
the data set will be available for free download from the Web site
of the Cambridge Crystallographic Data Centre