Profile-QSAR and Surrogate AutoShim Protein-Family Modeling of Proteases

The 2D Profile-QSAR and 3D Surrogate AutoShim protein-family
virtual
screening methods were originally developed for kinases. They are
the key components of an iterative medium-throughput screening alternative
to expensive and time-consuming experimental high-throughput screening.
Encouraged by the success with kinases, the S1-serine proteases were
selected as a second protein family to tackle, based on the structural
and SAR similarity among them, availability of structural and bioactivity
data, and the current and future small-molecule drug discovery interest.
A validation study on 24 S1-serine protease assay data sets from 16
unique proteases gave very promising results. Profile-QSAR gave a
median Rext2 = 0.60 for 24 assay data sets, and pairwise
selectivity modeling on 60 protease pairs gave a median Rext2 =
0.64, comparable to the performance for kinases. A 17-structure universal
ensemble S1-serine protease surrogate receptor for Autoshim was developed
from a collection of ∼1500 X-ray structures. The predictive
performance on 24 S1-serine protease assays was good, with a median Rext2 = 0.41, but lower than had been obtained for kinases. Analysis
suggested that the higher structural diversity of the protease structures,
as well as smaller assay data sets and fewer potent compounds, both
contributed to the decreased predictive power. In a prospective virtual
screening application, 32 compounds were ordered from a 1.5 million
archive and tested in a biochemical assay. Thirteen of the 32 compounds
were active at IC50 ≤ 10 μM, a 41% hit-rate.
Three new scaffolds were identified which are being followed up with
testing of additional analogues. A SAR similarity analysis for this
target against 13 other proteases also indicated two potential protease
targets which were positively and negatively correlated with the activity
of the target protease.