Application and Limitations of X‐ray Crystallographic Data in Structure‐Based Ligand and Drug Design

Abstract

Structure‐based design usually focuses upon the optimization of ligand affinity. However, successful drug design also requires the optimization of many other properties. The primary source of structural information for protein–ligand complexes is X‐ray crystallography. The uncertainties introduced during the derivation of an atomic model from the experimentally observed electron density data are not always appreciated. Uncertainties in the atomic model can have significant consequences when this model is subsequently used as the basis of manual design, docking, scoring, and virtual screening efforts. Docking and scoring algorithms are currently imperfect. A good correlation between observed and calculated binding affinities is usually only observed only when very large ranges of affinity are considered. Errors in the correlation often exceed the range of affinities commonly encountered during lead optimization. Some structure‐based design approaches now involve screening libraries by using technologies based on NMR spectroscopy and X‐ray crystallography to discover small polar templates, which are used for further optimization. Such compounds are defined as leadlike and are also sought by more traditional high‐throughput screening technologies. Structure‐based design and HTS technologies show important complementarity and a degree of convergence.