Section 22.4.5.9. Protein–ligand binding

The reluctance to use data from the CSD because they do not relate directly to biological systems has been noted earlier. However, in principle, the same forces that drive the inclusion of a new molecule into a growing crystal should also apply to the binding of a ligand to a protein. In both cases, molecule and target need to be de-solvated first (although in the first case not necessarily from a water environment) and then interact in the most favourable way.

Nicklaus and colleagues suggested that on average, the conformational energy of ligands in the protein-bound state is 66 (48) kJ mol⁻¹ above that of the global minimum-energy conformation in vacuo (Nicklaus et al., 1995). This result was based on 33 protein–ligand complexes from the PDB for which the ligand also occurs in a small-molecule structure in the CSD. The same investigation also showed that, although ligand conformations in the protein-bound state are generally different from those observed in small-molecule crystal structures, on average the conformational energy of the ligand in the CSD crystal-structure conformation is 66 (47) kJ mol⁻¹ above that of the global minimum-energy conformation in vacuo, although Boström et al. (1998) have shown that these conformational energies are much lower if calculated in a water environment. The computational work indicates that the forces that affect the conformation of a ligand are of comparable magnitude at a protein binding site to those in a small-molecule crystal-structure environment. Thus, if small-molecule crystal-structure statistics tell us that a given structure fragment can only adopt one conformation, generally there is no reason to believe that a ligand that contains this fragment will adopt a different conformation when it binds to a protein.

In principle, the information on non-bonded interactions derived from the CSD and assembled in the IsoStar library should be very important for the understanding and prediction of interaction geometries. However, in light of the comments above, it is important to know whether these data are generally relevant to interactions that occur in the protein binding site. Work by Klebe (1994) indicated that, at least for a limited set of test cases, the geometrical distributions derived from ligand–protein complexes are similar to those derived from small-molecule crystal structures. Since the IsoStar library contains information from both the PDB and the CSD, it provides the ultimate basis for establishing similarities (or not) between the interaction geometries observed in small-molecule crystal structures and those observed in protein–ligand complexes. Comparing CSD scatter plots with their corresponding plots from the PDB is an obvious way of establishing the relevance of non-bonded interaction data from small-molecule crystal structures to biological systems.

A full systematic comparison of PDB and CSD scatter plots or, more accurately, of PDB and CSD density maps has recently been performed by Verdonk (1998). He calculated residual densities, obtained by subtracting one density map from the other, for each pair of density maps. It appears that, in general, CSD and PDB plots (and thus interaction geometries) are very similar indeed: the average residual density is only 10 (10)%, indicating that 90% of the density in the PDB map is also observed in the CSD map. In Fig. 22.4.5.4(a), the average residual densities of each PDB–CSD comparison are plotted versus the average concentration of contact groups in the scatter plot. The filled circles represent comparisons for which the protonation state of the central group is unambiguous (i.e. carboxylic acid, imidazole etc. were excluded). It appears that the residual density decreases with the amount of data in the plots, obviously caused by the more accurate calculation of the residual density. The `true' residual density seems to be as low as about 6%.

Figure 22.4.5.4| top | pdf | Pairwise comparison of intermolecular-interaction density maps from the CSD and the PDB. Plots of residual density versus plot density, i.e. the average density in the least dense situation (CSD or PDB), for situations where the protonation state of the central group is (a) unambiguous, and (b) ambiguous.

Fig. 22.4.5.4(b) shows a similar graph, but now for those density maps in which the protonation state of the central group is ambiguous. As expected, the spread in the calculated residual densities is much higher, even for very dense plots. By comparing the density map from the PDB with the CSD maps for the different protonation states of the central group, the most frequent protonation state of this central group in the protein structures can be predicted. In Table 22.4.5.1, for example, the residual densities for protein carboxylic acid groups are shown, compared with the CSD plots of the neutral carboxylic acid and with those of the charged carboxylate anion. In all cases, the residual density is lower if the PDB map is compared with the CSD map for charged carboxylate anions. This indicates that the majority of glutamate and aspartate side chains are charged, which is consistent with other evidence.