Evaluation of Scoring Function Performance on DNA-ligand Complexes

DNA has been a pharmacological target for different types of treatment, such as antibiotics and chemotherapy agents, and is still a potential target in many drug discovery processes. However, most docking and scoring approaches were parameterised for protein-ligand interactions; their suitability for modelling DNA-ligand interactions is uncertain.

This study investigated the performance of four scoring functions on DNA-ligand complexes.

Here, we explored the ability of four docking protocols and scoring functions to discriminate the native pose of 33 DNA-ligand complexes over a compiled set of 200 decoys for each DNA-ligand complexes. The four approaches were the AutoDock, ASP^@GOLD, ChemScore^@GOLD and GoldScore^@GOLD.

Our results indicate that AutoDock performed the best when predicting binding mode and that ChemScore^@GOLD achieved the best discriminative power. Rescoring of AutoDock-generated decoys with ChemScore^@GOLD further enhanced their individual discriminative powers. All four approaches have no discriminative power in some DNA-ligand complexes, including both minor groove binders and intercalators.

This study suggests that the evaluation for each DNA-ligand complex should be performed in order to obtain meaningful results for any drug discovery processes. Rescoring with different scoring functions can improve discriminative power.