0.9 Protein-ligand docking, including flexible receptor-flexible  (Page 4/9)

Autodock uses a kinematic model for the ligand based on rotations around single bonds. The ligand begins the search process from a random location and orientation outside the binding site and by exploring the values for translations, rotations and its internal degrees of freedom, it eventually reaches the bound conformation. Each degree of freedom is encoded as a single gene for the purpose of the genetic algorithm.

The receptor is represented as a potential grid. For each atom type, charge, and placement within the grid, an energy value may be rapidly computed, according to the scoring function below. Precomputation of the grid is time-consuming, but each individual energy calculation is very rapid as a result. The drawback of this approach is that there is no obvious way to introduce protein flexibility. If the were allowed to moves, the entire grid would have to be recomputed at great computational expense.

Scoring function

Distinction between docked conformations is carried out by the following empirical scoring function:

Flexx

Link to The FlexX home page

FlexX was developed at the Institute for Algorithms and Scientific Computating at the German National Research Center for Computer Science in Sankt Augustin, Germany. The basic procedure is to break the ligand into fragments, then repeatedly place an anchor fragment and incrementally build the entire ligand in place.

Search technique

For each atom in the ligand and receptor, a set of interaction surfaces is generated and stored. The interaction surfaces represent ideal locations for atoms of the other molecule to form some stabilizing interaction. The shape, size, and location of each surface depends on the type of interaction--hydrogen bonding, electrostatic (ionic), aromatic, or lipophilic (hydrophobic).

The ligand is broken into fragments, separated by rotatable bonds, and a base fragment is chosen. The base fragment is placed by aligning a triangle formed by three of its atoms with interaction surfaces of receptor atoms, using a technique called pose clustering [7] . The choice of base fragment is critical, because a fragment with insufficient interaction surfaces will provide too little guidance for its initial placement. For each sufficiently distinct placement of the base fragment, additional fragments are added in such a way as to maximize interactions and optimize the scoring function.

Because FlexX generates candidate structures by the matching of interaction surfaces, it dramatically decreases the size of the search space compared to a full search of the conformation space, therefore improving the running time. On the other hand, the choice of the anchor fragment is difficult and has the potential to determine which solutions are reachable. In practice, however, FlexX and its derivatives (FlexS, FlexE, and FlexX-Pharm) work well enough to have been incorporated in a number of corporate automated drug discovery applications.