Protein-Ligand Structure Prediction by Template-Guided Ensemble Docking Strategy.

Abstract

In the 15th Critical Assessment of Techniques for Structure Prediction (CASP15), the category of protein-ligand complexes was introduced to advance the development of protein-ligand structure prediction techniques. CASP16 further expanded this category by introducing four sets of pharmaceutical targets as super-targets. Each super-target consists of multiple protein-ligand complexes involving the same protein but different ligands. Given the outstanding performance of template-based methods in CASP15, we employed a template-guided ensemble docking strategy for ligand (LG) tasks in CASP16. MODELER, AlphaFold3, and AlphaFold-Multimer were used to generate structural ensembles for each target protein. Then, we searched the Protein Data Bank (PDB) for reliable template complexes based on sequence identity, ligand similarity, and maximum common substructure (MCS) coverage score. If templates were identified, we used LSalign to perform ligand 3D alignment. For targets without a template, XDock and MDock were used to predict the binding poses. Finally, a knowledge-based scoring function, ITScore, was employed for energy evaluation. It is shown that our method performed well in the CASP16's LG tasks, ranking 4th out of 38 participating teams.