Novel simulation methods for flexible docking

Abstract

The binding of small molecule ligands to large protein targets is central to numerous biological processes. The accurate prediction of the binding modes between the ligand and protein is of fundamental importance in modern structure-based drug design. This is commonly referred to as the docking problem and it has been addressed in this thesis using a multiple stage simulation based method.

The methodology presented is a hybrid approach where the first stage is a rapid dock of the ligand to the protein binding site, based on deriving sets of simultaneously satisfied hydrogen bonds using graph theory and a recursive distance geometry algorithm. The output structures are then reduced in number by cluster analysis based on distance similarities. These structures are then submitted to a modified Monte Carlo algorithm which uses the AMBER-AA molecular mechanics force field with the Generalised Born/Surface Area (GB/SA) continuum model. This solvent model is not only less expensive than an explicit representation but also yields increased sampling. Sampling was also increased using a rotamer library to direct some of the protein side chain movements along with the large dihedral moves. Furthermore, a softening function for the non-bonded force field terms was used, enabling the potential energy function to be slowly turned on throughout the course of the simulation.

The docking procedure was optimised on a single complex and validated on a further 14 complexes. For each complex the docking methodology was tested with and without protein side chain flexibility, using full ligand flexibility in both cases.

In the rigid protein dock 13 out of the 15 test cases were able to find the experimental binding mode: this number was reduced to 11 in the flexible protein dock. In these instances, although the experimental binding mode could not always be uniquely identified, in the majority of cases this mode was present in a cluster of low energy structures which were energetically indistinguishable. This suggests that it may be necessary to consider more than one binding conformation during ligand optimisation.

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