Fragment Pose Prediction Using Non-equilibrium Candidate Monte Carlo and Molecular Dynamics Simulations

Part
of early stage drug discovery involves determining how molecules
may bind to the target protein. Through understanding where and how
molecules bind, chemists can begin to build ideas on how to design
improvements to increase binding affinities. In this retrospective
study, we compare how computational approaches like docking, molecular
dynamics (MD) simulations, and a non-equilibrium candidate Monte Carlo
(NCMC)-based method (NCMC + MD) perform in predicting binding modes
for a set of 12 fragment-like molecules, which bind to soluble epoxide
hydrolase. We evaluate each method’s effectiveness in identifying
the dominant binding mode and finding additional binding modes (if
any). Then, we compare our predicted binding modes to experimentally
obtained X-ray crystal structures. We dock each of the 12 small molecules
into the apo-protein crystal structure and then run simulations up
to 1 μs each. Small and fragment-like molecules likely have
smaller energy barriers separating different binding modes by virtue
of relatively fewer and weaker interactions relative to drug-like
molecules and thus likely undergo more rapid binding mode transitions.
We expect, thus, to see more rapid transitions between binding modes
in our study. Following this, we build Markov State Models to define
our stable ligand binding modes. We investigate if adequate sampling
of ligand binding modes and transitions between them can occur at
the microsecond timescale using traditional MD or a hybrid NCMC+MD
simulation approach. Our findings suggest that even with small fragment-like
molecules, we fail to sample all the crystallographic binding modes
using microsecond MD simulations, but using NCMC+MD, we have better
success in sampling the crystal structure while obtaining the correct
populations.