- Working with InhibOx
Ligand-protein docking methods attempt to identify optimal positions, orientations and conformations of a ligand or small molecule with respect to a given protein receptor or enzyme. InhibOx offers extensive expertise and a range of solutions in ligand-protein docking.
InhibOx projects can start from one or more crystal structures of the target site; when these are not available, our team can construct and work from carefully prepared homology-modeled representations of the protein. Of course, no single docking software package can provide the best results in all circumstances. InhibOx therefore exploits three systems, each with its own particular strengths. We use these in tandem in ourprojects, to explore each receptor fully.
AutoDock, co-authored by InhibOx's Garrett M. Morris, is one of the most highly-cited ligand-protein docking programs in the literature. It treats the ligand and optionally, sidechains in the protein, as flexible. This permits these parts of the molecules with rotatable bonds to change conformation during the docking. The combinatorial explosion in conformational flexibility with increasing numbers of rotatable bonds is computationally expensive, but is essential for scientifically meaningful docking experiments.
AutoDock can been used to identify the binding sites of ligands without any a priori knowledge of the active site: there are several examples in the literature of its use for "blind docking".
The great advantage of ligand-protein docking methods is that they can propose structural hypotheses for how a given small molecule may interact with its target macromolecule, something that ligand-based virtual screening methods cannot do. Indeed, a recent perspective on molecular shape by Nicholls et al. points out that while the shape of an active ligand can be extremely valuable for the discovery of novel inhibitors, when the target protein is flexible, the shapes adopted by active ligands may be sufficiently different that a match cannot be found using shape-based ligand-based approaches alone.
The challenge of 'induced fit' can be overcome using multiple conformations of the target protein in the ligand dockings; the "Relaxed Complex Scheme" is one such approach, in which carefully selected, diverse, representative snapshots from Molecular Dynamics simulations of the apo protein are used with a ligand-protein docking program such as AutoDock to dock the ligands to the ensemble of conformations of the target protein. This approach increases the chances of identifying hits in virtual screening, avoiding false negatives that would otherwise arise with an incompatible protein conformation.
InhibOx can apply its technologies to model this protein flexibility and perform virtual screening using DOx and AutoDock to identify novel inhibitors, and potentially discover novel binding pockets and even allosteric pockets, as has recently been reported by the AutoDock-based World Community Gridproject, FightAIDS@Home.
DOx is InhibOx's in-house ligand docking and scoring software. In common with most docking programs it is composed of two main components:
- search: explores position and orientation of the ligand with respect to the protein.
- scoring: evaluates each generated molecular configuration.
The DOx Search Module
There are two main types of search modules for positioning ligands with respect to a protein target: exhaustive and stochastic.
Exhaustive or systematic search methods move and rotate the ligand into every possible position and orientation within the search space using a given “granularity” of search. The success of such programs is often limited by efficiency considerations due to the complexity and scale associated with large proteins and receptors.
The use of an optimal GA configuration for the problem space is very important and was a main consideration for the design of the DOx search component. DOx uses a GA-based search method with a gradient-based optimization module. AutoDock also uses a similar implementation of a hybrid GA by incorporating Lamarckian rules to the operation of the algorithm. DOx also uses a novel chromosome design.
The DOx Scoring Module
The scoring module is used to evaluate the favorability of a generated molecular configuration. A variety of scoring functions have been developed over the past decade. Several recent studies have also evaluated many collections of these scoring functions for accuracy. These studies have indicated the effectiveness of the XScore, DrugScore, PLP and G-Score scoring functions. The PLP and XScore functions have been implemented in DOx.
However, many of the scoring functions available have been developed, tested and evaluated against distinct classes of proteins and may therefore return different results for generalized cases. The best scoring function to use for a particular class of target protein can be difficult to predict. Therefore, a more recent approach to the construction of the scoring module involves the use of consensus scoring: the use of two or more scoring functions for the prediction of the binding affinity. The construction of the final score can be done in many ways. The simplest involves the normalisation of two scores (e.g. PLP and XScore) and using the largest or smallest. A more refined approach involves the scoring of the ligand against a collection of scoring functions and constructing the final score by the parameterized addition of the different scoring function scores. The values of each parameter are dependent on the class of the protein being used.
GOLD is the widely-used docking system developed by InhibOx partners, the Cambridge Crystallographic Data Centre. InhibOx scientists use the GOLD suite of programs alongside AutoDock and DOx in many projects. The product of a collaboration between the University of Sheffield, GlaxoSmithKline plc and CCDC, the carefully-validated and versatile docking software package GOLD is very highly regarded within the molecular modelling community for its accuracy and reliability.
 Garrett M. Morris, David S. Goodsell, Robert S. Halliday, Ruth Huey, William E. Hart, Richard K. Belew, and Arthur J. Olson. Automated docking using a lamarckian genetic algorithm and an empirical binding free energy function. Journal of Computational Chemistry, 19(14):1639–1662, January 1999.
 Todd J. Ewing, Shingo Makino, Geoffrey A. Skillman, and Irwin D. Kuntz. Dock 4.0: Search strategies for automated molecular docking of flexible molecule databases. Journal of Computer-Aided Molecular Design, 15(5):411–428, May 2001.