LUDI focuses on the hydrogen bonds and hydrophobic contacts which could be formed
between the ligand and protein. Its central concept are interaction sites, which are discrete
positions in space suitable for forming hydrogen bonds or for filling a hydrophobic pocket
[57]. A set of interaction sites is generated either by searching the database or using the
rules. The fragment is then fitted onto the interaction sites and evaluated by distance criteria.
The final step is the connection of some or all of the fitted fragments to a single molecule.
Stochastic methods search the conformational space by randomly modifying a ligand
conformation or a population of ligands. Monte Carlo (MC) and genetic algorithms are two
typical algorithms that belong to the class of stochastic methods.
Monte Carlo (MC) [58, 59] methods generate poses of the ligand through bond rotation,
rigid-body translation or rotation. The conformation obtained by this transformation is tested
with an energy- based selection criterion. If it passes the criterion, it will be saved and
further modified to generate next conformation. The iterations will proceed until the predefined
quantity of conformations is collected. The main advantage of MC is that the change
can be quite large allowing the ligand to cross the energy barriers on the potential energy
surface, a point that isn’t achieved easily by molecular dynamics based simulation methods.
Examples of applying the Monte Carlo methods include an earlier version of AutoDock
[60], ICM [61], QXP [62] and Affinity [63].