1 research outputs found
Virtual Screening of PRK1 Inhibitors: Ensemble Docking, Rescoring Using Binding Free Energy Calculation and QSAR Model Development
Protein kinase C Related Kinase 1
(PRK1) has been shown to be involved
in the regulation of androgen receptor signaling and has been identified
as a novel potential drug target for prostate cancer therapy. Since
there is no PRK1 crystal structure available to date, multiple PRK1
homology models were generated in order to address the protein flexibility.
An in-house library of compounds tested on PRK1 was docked into the
ATP binding site of the generated models. In most cases a correct
pose of the inhibitors could be identified by ensemble docking, while
there is still a challenge of finding a reasonable scoring function
that is able to rank compounds according to their biological activity.
We estimated the binding free energy for our data set of structurally
diverse PRK1 inhibitors using the MM-PBÂ(GB)ÂSA and QM/MM-GBSA methods.
The obtained results demonstrate that a correlation between calculated
binding free energies and experimental IC<sub>50</sub> values was
found to be usually higher than using docking scores. Furthermore,
the developed approach was tested on a set of diverse PRK1 inhibitors
taken from literature, which resulted in a significant correlation.
The developed method is computationally inexpensive and can be applied
as a postdocking filter in virtual screening as well as for optimization
of PRK1 inhibitors in order to prioritize compounds for further biological
characterization