Consecutive dockings using the same input files will not give identical solutions or fitness scores. The reason for this is fundamental to the way in which GOLD determines solutions.

GOLD uses a Genetic Algorithm (GA) for protein ligand docking which works as follows:

  • A population of potential solutions (i.e. possible docked orientations of the ligand) is set up at random.
  • Each member of the population is encoded as a chromosome, which contains information about the mapping of protein ligand interactions.
  • Each chromosome is assigned a fitness score based on its predicted binding affinity and the chromosomes within the population are ranked according to fitness.
  • The population of chromosomes is iteratively optimised. At each step, a point mutation may occur in a chromosome, or two chromosomes may mate to give a child. The selection of parent chromosomes is biased towards fitter members of the population, i.e. chromosomes corresponding to ligand dockings with good fitness scores.

Hence, a solution to a problem solved by a genetic algorithm is evolved as opposed to being determined directly. Therefore, due to the initial random seeding of the algorithm, consecutive dockings are unlikely to give the exact same answer.

Because GOLD is non-deterministic it means that a variety of plausible binding modes of similar score can be retrieved easily.

For further information please refer to the GOLD user manual.​

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