Fast Protein Binding Site Comparison via an Index-Based Screening Technology

We present TrixP, a new index-based method for fast protein
binding site comparison and function prediction. TrixP determines
binding site similarities based on the comparison of descriptors that
encode pharmacophoric and spatial features. Therefore, it adopts the
efficient core components of TrixX, a structure-based virtual screening
technology for large compound libraries. TrixP expands this technology
by new components in order to allow a screening of protein libraries.
TrixP accounts for the inherent flexibility of proteins employing
a partial shape matching routine. After the identification of structures
with matching pharmacophoric features and geometric shape, TrixP superimposes
the binding sites and, finally, assesses their similarity according
to the fit of pharmacophoric properties. TrixP is able to find analogies
between closely and distantly related binding sites. Recovery rates
of 81.8% for similar binding site pairs, assisted by rejecting rates
of 99.5% for dissimilar pairs on a test data set containing 1331 pairs,
confirm this ability. TrixP exclusively identifies members of the
same protein family on top ranking positions out of a library consisting
of 9802 binding sites. Furthermore, 30 predicted kinase binding sites
can almost perfectly be classified into their known subfamilies.