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.

PRODRG: a tool for high-throughput crystallography of protein–ligand complexes

“…With the rise of structure-based drug-design techniques (reviewed in Davis et al, 2003), it is important to have software available which supports the ligand/inhibitor throughout the entire design process. Firstly, coordinates for the drug need to be built or an existing molecule modi®ed, followed by docking of the drug into the active site and/or re®nement of a protein± drug complex against X-ray diffraction data.…”

“…The protein±drug interaction then needs to be examined in terms of detailed hydrogen-bonding geometry or other scoring functions (reviewed in Brooijmans & Kuntz, 2003). During this process, the drug interacts with different types of software and for each of these types a wide variety of packages are available (Davis et al, 2003). Making these computer programs understand the topology of the drug involved is often a laborious process and, when no structural information is available, prone to errors as bond lengths and angles often have to be guessed .…”

Proteus in the World of Proteins: Conformational Changes in Protein Kinases

“…Ligand binding generally involves some degree of flexibility to allow the ligand to adapt to its receptor binding site and vice versa [85]. This process is known as induced fit and is particularly important for kinase-inhibitor interactions [86].…”

The potential use of single-particle electron microscopy as a tool for structure-based inhibitor design

“…This is not just the case for membrane proteins; other potential drug targets such as viruses and large protein complexes have also proven to be difficult to crystallize for a variety of reasons, including flexibility and size. When a structure is obtained from crystallography there is also the possibility that some of the observed interactions do not fully reflect the native state, for example crystal-packing artefacts (Davis et al, 2003). A further drawback in using crystal structures for structurebased drug design is that they may only reflect a handful of conformational states and not show the full dynamic range of the system.…”