ci5b00744_si_001.pdf (3.77 MB)
Binding Mode and Induced Fit Predictions for Prospective Computational Drug Design
journal contribution
posted on 2016-03-14, 00:00 authored by Christoph Grebner, Jessica Iegre, Johan Ulander, Karl Edman, Anders Hogner, Christian TyrchanComputer-aided drug design plays
an important role in medicinal
chemistry to obtain insights into molecular mechanisms and to prioritize
design strategies. Although significant improvement has been made
in structure based design, it still remains a key challenge to accurately
model and predict induced fit mechanisms. Most of the current available
techniques either do not provide sufficient protein conformational
sampling or are too computationally demanding to fit an industrial
setting. The current study presents a systematic and exhaustive investigation
of predicting binding modes for a range of systems using PELE (Protein
Energy Landscape Exploration), an efficient and fast protein–ligand
sampling algorithm. The systems analyzed (cytochrome P, kinase, protease,
and nuclear hormone receptor) exhibit different complexities of ligand
induced fit mechanisms and protein dynamics. The results are compared
with results from classical molecular dynamics simulations and (induced
fit) docking. This study shows that ligand induced side chain rearrangements
and smaller to medium backbone movements are captured well in PELE.
Large secondary structure rearrangements, however, remain challenging
for all employed techniques. Relevant binding modes (ligand heavy
atom RMSD < 1.0 Å) can be obtained by the PELE method within
a few hours of simulation, positioning PELE as a tool applicable for
rapid drug design cycles.