3D Flexible Alignment Using 2D Maximum Common Substructure: Dependence of Prediction Accuracy on Target-Reference Chemical Similarity

A protein-bound conformation of a
target molecule can be predicted
by aligning the target molecule on the reference molecule obtained
from the 3D structure of the compound–protein complex. This
strategy is called “similarity-based docking”. For this
purpose, we develop the flexible alignment program fkcombu, which aligns the target molecule based on atomic correspondences
with the reference molecule. The correspondences are obtained by the
maximum common substructure (MCS) of 2D chemical structures, using
our program kcombu. The prediction performance was
evaluated using many target-reference pairs of superimposed ligand
3D structures on the same protein in the PDB, with different ranges
of chemical similarity. The details of atomic correspondence largely
affected the prediction success. We found that topologically constrained
disconnected MCS (TD-MCS) with the simple element-based atomic classification
provides the best prediction. The crashing potential energy with the
receptor protein improved the performance. We also found that the
RMSD between the predicted and correct target conformations significantly
correlates with the chemical similarities between target-reference
molecules. Generally speaking, if the reference and target compounds
have more than 70% chemical similarity, then the average RMSD of 3D
conformations is <2.0 Å. We compared the performance with
a rigid-body molecular alignment program based on volume-overlap scores
(ShaEP). Our MCS-based flexible alignment program
performed better than the rigid-body alignment program, especially
when the target and reference molecules were sufficiently similar.