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Enzymes catalyse numerous reactions in nature, often causing spectacular accelerations in the catalysis rate. One aspect of understanding how enzymes achieve these feats is to explore how they use the limited set of residue side chains that form their 'catalytic toolkit'. Combinations of different residues form 'catalytic units' that are found repeatedly in different unrelated enzymes. Most catalytic units facilitate rapid catalysis in the enzyme active site either by providing charged groups to polarize substrates and to stabilize transition states, or by modifying the pKa values of other residues to provide more effective acids and bases. Given recent efforts to design novel enzymes, the rise of structural genomics and subsequent efforts to predict the function of enzymes from their structure, these units provide a simple framework to describe how nature uses the tools at her disposal, and might help to improve techniques for designing and predicting enzyme function.

The theory of induced fit predicts that enzymes undergo conformational changes as they bind their substrate. We have analysed the structures of 60 different enzymes to see if conformational changes are observed between the apo form, and the substrate (or substrate analog) bound form. In each enzyme the residues responsible for catalysis and substrate binding are known and are examined to see how the active site area is affected by conformational changes. Surprisingly, we find that induced fit motions in most enzymes is very small (usually 1 A RMSD between the apo and substrate-bound forms across the whole protein). We also find that there is a significant difference between the motions undergone by the binding residues and those undergone by the catalytic residues. The binding residues tend to exhibit larger backbone motions, but both binding and catalytic residues show the same, considerable, amount of side-chain flexibility. Knowing the extent of induced fit in enzymes is important for our understanding of the principles of enzyme catalysis and also for improving ligand docking and structural template searching.

The role of conformational change in substrate binding, catalysis and product release is reviewed for 11 enzymes, for which crystal structures are available for the apo, substrate- and product-bound states. The extent of global conformational changes is measured, and the movements of the functional regions involved in catalysis and ligand binding are compared to the rest of the structure. We find that most of these enzymes undergo relatively small amounts of conformational change and particularly small changes in catalytic residue geometry, usually less than 1 A. In some enzymes there is significant movement of the binding residues, usually on surface loops.

Structural genomics projects aim to provide a sharp increase in the number of structures of functionally unannotated, and largely unstudied, proteins. Algorithms and tools capable of deriving information about the nature, and location, of functional sites within a structure are increasingly useful therefore. Here, a neural network is trained to identify the catalytic residues found in enzymes, based on an analysis of the structure and sequence. The neural network output, and spatial clustering of the highly scoring residues are then used to predict the location of the active site.A comparison of the performance of differently trained neural networks is presented that shows how information from sequence and structure come together to improve the prediction accuracy of the network. Spatial clustering of the network results provides a reliable way of finding likely active sites. In over 69% of the test cases the active site is correctly predicted, and a further 25% are partially correctly predicted. The failures are generally due to the poor quality of the automatically generated sequence alignments. We also present predictions identifying the active site, and potential functional residues in five recently solved enzyme structures, not used in developing the method. The method correctly identifies the putative active site in each case. In most cases the likely functional residues are identified correctly, as well as some potentially novel functional groups.