Omeir Khan

1 Introduction Understanding the three-dimensional structures of protein–protein and protein–ligand complexes is crucial for gaining insights into biological function and for structure-based drug discovery. Experimental techniques such as X-ray crystallography, NMR spectroscopy, and cryo-electron microscopy can determine complex structures, but they are time-consuming and costly, leaving many known interactions unresolved. Hence, computational prediction of such complexes is important.

The neural network-based program AlphaFold2 (AF2) provides high accuracy structure prediction for a large fraction of globular proteins. An important question is whether these models are accurate enough for reliably docking small ligands. Several recent papers and the results of CASP15 reveal that local conformational errors reduce the success rates of direct ligand docking.