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Fig. 2 (a) An overlay of the 2D 1 H- 15 N HSQC spectra for the protein YndB titrated with
increasing amounts of chalcone. The perturbed residues can be used to identify a consensus
binding site. (b) NMR titration data for YndB bound to chalcone ( blue ), flavanone ( green ), flavone
( purple ), and flavanol ( orange ). The magnitude of the chemical shift perturbation can be used to
calculate the dissociation constants for each compound. (Reprinted with permission from [ 112 ],
copyright 2010 by John Wiley and Sons)
[ 79 ]. Recent advances like the SOFAST-HMQC experiment [ 80 , 81 ] and the Fast-
HSQC experiment [ 82 ] have decreased the time and amount of protein necessary
for a target-based screen. Nevertheless, NMR ligand affinity screens are still very
resource intensive, requiring a significant amount of time and material. Also, since
any high-throughput screen produces a significant amount of negative data (most
ligands don't bind or inhibit a protein), a more efficient approach is to screen a
library of compounds with a higher probability of binding the protein target. In
effect, a virtual or in silico screen can be used to enrich a library with likely binders.
3 Molecular Docking
An accurate prediction of the interactions between two molecules requires an in-
depth understanding of the energetics that led to a stable biomolecular complex.
Unfortunately, a model that correctly accounts for all the factors involved in a
productive protein-ligand interaction is currently unknown. Further, the problem is
exponentially more complex than just modeling the specifics of a protein-ligand
interaction. A protein contains thousands of atoms that have specific interactions
with each other, with the solvent, and with other ions; in addition to the bound
ligand. Because of this complexity, computational efforts that attempt to model
protein-ligand interactions require significant amounts of processing power and
time. Many efforts that utilize molecular dynamics and distributed computing
[ 83 , 84 ] are generally limited to a detailed analysis of a single system. These
methods are generally not practical for the majority of researchers interested
in conducting a virtual screen of a library containing upwards of millions of
compounds. To make molecular docking computationally feasible and easily
accessible, many simplifications and trade-offs in the process are necessary.
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