Applying Pose Clustering and MD Simulations To Eliminate
False Positives in Molecular Docking
Version 3 2018-03-09, 14:08
Version 2 2018-03-08, 19:12
Version 1 2018-03-08, 17:04
Posted on 2018-03-09 - 14:08
In
this work, we developed a computational protocol that employs
multiple molecular docking experiments, followed by pose clustering,
molecular dynamic simulations (10 ns), and energy rescoring to produce
reliable 3D models of antibody–carbohydrate complexes. The
protocol was applied to 10 antibody−carbohydrate co-complexes
and three unliganded (apo) antibodies. Pose clustering significantly
reduced the number of potential poses. For each system, 15 or fewer
clusters out of 100 initial poses were generated and chosen for further
analysis. Molecular dynamics (MD) simulations allowed the docked poses
to either converge or disperse, and rescoring increased the likelihood
that the best-ranked pose was an acceptable pose. This approach is
amenable to automation and can be a valuable aid in determining the
structure of antibody–carbohydrate complexes provided there
is no major side chain rearrangement or backbone conformational change
in the H3 loop of the CDR regions. Further, the basic protocol of
docking a small ligand to a known binding site, clustering the results,
and performing MD with a suitable force field is applicable to any
protein ligand system.
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Makeneni, Spandana; Thieker, David F.; Woods, Robert J. (2018). Applying Pose Clustering and MD Simulations To Eliminate
False Positives in Molecular Docking. ACS Publications. Collection. https://doi.org/10.1021/acs.jcim.7b00588
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AUTHORS (3)
SM
Spandana Makeneni
DT
David F. Thieker
RW
Robert J. Woods