Integration of Ligand and Structure Based Approaches for CSAR-2014

The prediction of binding poses and
affinities is an area of active
interest in computer-aided drug design (CADD). Given the documented
limitations with either ligand or structure based approaches, we employed
an integrated approach and developed a rapid protocol for binding
mode and affinity predictions. This workflow was applied to the three
protein targets of Community Structure–Activity Resource-2014
(CSAR-2014) exercise: Factor Xa (FXa), Spleen Tyrosine Kinase (SYK),
and tRNA (guanine-N(1))-methyltransferase (TrmD). Our docking and
scoring workflow incorporates compound clustering and ligand and protein
structure based pharmacophore modeling, followed by local docking,
minimization, and scoring. While the former part of the protocol ensures
high-quality ligand alignments and mapping, the subsequent minimization
and scoring provides the predicted binding modes and affinities. We
made blind predictions of docking pose for 1, 5, and 14 ligands docked
into 1, 2, and 12 crystal structures of FXa, SYK, and TrmD, respectively.
The resulting 174 poses were compared with cocrystallized structures
(1, 5, and 14 complexes) made available at the end of CSAR. Our predicted
poses were related to the experimentally determined structures with
a mean root-mean-square deviation value of 3.4 Å. Further, we
were able to classify high and low affinity ligands with the area
under the curve values of 0.47, 0.60, and 0.69 for FXa, SYK, and TrmD,
respectively, indicating the validity of our approach in at least
two of the three systems. Detailed critical analysis of the results
and CSAR methodology ranking procedures suggested that a straightforward
application of our workflow has limitations, as some of the performance
measures do not reflect the actual utility of pose and affinity predictions
in the biological context of individual systems.