No abstract

Computational mapping methods place molecular probes (small molecules or functional groups) on a protein surface to identify the most favorable binding positions by calculating an interaction potential. We have developed a novel computational mapping program called CS-Map (computational solvent mapping of proteins), which differs from earlier mapping methods in three respects: (i) it initially moves the ligands on the protein surface toward regions with favorable electrostatics and desolvation, (ii) the final scoring potential accounts for desolvation, and (iii) the docked ligand positions are clustered, and the clusters are ranked on the basis of their average free energies. To understand the relative importance of these factors, we developed alternative algorithms that use the DOCK and GRAMM programs for the initial search. Because of the availability of experimental solvent mapping data, lysozyme and thermolysin are considered as test proteins. Both DOCK and GRAMM speed up the initial search, and the combined algorithms yield acceptable mapping results. However, the DOCK-based approaches place the consensus site farther from its experimentally determined position than CS-Map, primarily because of the lack of a solvation term in the initial search. The GRAMM-based program also finds the correct consensus site for thermolysin. We conclude that good sampling is the most important requirement for successful mapping, but accounting for desolvation and clustering of ligand positions also help to reduce the number of false positives.

The catalytic site of haloalkane dehalogenase DhlA is buried more than 10 A from the protein surface. While potential access channels to this site have been reported, the precise mechanism of substrate import and product export is still unconfirmed. We used computational methods to examine surface pockets and their putative roles in ligand access to and from the catalytic site. Computational solvent mapping moves small organic molecule as probes over the protein surface in order to identify energetically favorable sites, that is, regions that tend to bind a variety of molecules. The mapping of three DhlA structures identifies seven such regions, some of which have been previously suggested to be involved in the binding and the import/export of substrates or products. These sites are the active site, the putative entrance of the channel leading to the active site, two pockets that bind Br- ions, a pocket in the slot region, and two additional sites between the main domain and the cap of DhlA. We also performed mapping and free energy analysis of the DhlA structures using the substrate, 1,2-dichloroethane, and halide ions as probes. The findings were compared to crystallographic data and to results obtained by CAVER, a program developed for finding routes from protein clefts and cavities to the surface. Solvent mapping precisely reproduced all three Br- binding sites identified by protein crystallography and the openings to four channels found by CAVER. The analyses suggest that (i) the active site has the highest affinity for the substrate molecule, (ii) the substrate initially binds at the entrance of the main tunnel, (iii) the site Br2, close to the entrance, is likely to serve as an intermediate binding site in product export, (iv) the site Br3, induced in the structure at high concentrations of Br-, could be part of an auxiliary route for product release, and (v) three of the identified sites are likely to be entrances of water-access channels leading to the active site. For comparison, we also mapped haloalkane dehalogenases DhaA and LinB, both of which contain significantly larger and more solvent accessible binding sites than DhlA. The mapping of DhaA and LinB places the majority of probes in the active site, but most of the other six regions consistently identified in DhlA were not observed, suggesting that the more open active site eliminates the need for intermediate binding sites for the collision complex seen in DhlA.

Computational mapping methods place molecular probes--small molecules or functional groups--on a protein surface in order to identify the most favorable binding positions by calculating an interaction potential. Mapping is an important step in a number of flexible docking and drug design algorithms. We have developed improved algorithms for mapping protein surfaces using small organic molecules as molecular probes. The calculations reproduce the binding of eight organic solvents to lysozyme as observed by NMR, as well as the binding of four solvents to thermolysin, in good agreement with x-ray data. Application to protein tyrosine phosphatase 1B shows that the information provided by the mapping can be very useful for drug design. We also studied why the organic solvents bind in the active site of proteins, in spite of the availability of alternative pockets that can very tightly accommodate some of the probes. A possible explanation is that the binding in the relatively large active site retains a number of rotational states, and hence leads to smaller entropy loss than the binding elsewhere else. Indeed, the mapping reveals that the clusters of the ligand molecules in the protein's active site contain different rotational-translational conformers, which represent different local minima of the free energy surface. In order to study the transitions between different conformers, reaction path and molecular dynamics calculations were performed. Results show that most of the rotational states are separated by low free energy barriers at the experimental temperature, and hence the entropy of binding in the active site is expected to be high.