: Genetic Optimisation for Ligand Docking

	GOLD is a genetic algorithm (GA) for flexible ligand docking, written by Dr Gareth Jones, University of Sheffield, United Kingdom.

Predicting how a small molecule will bind to a protein is difficult, and no program can guarantee success. The next best thing is to measure as accurately as possible the reliability of the program, i.e. the chance that it will make a successful prediction in a given instance. For that reason, GOLD has been tested on a large number (134) of complexes extracted from the Brookhaven Protein Data Bank. The overall conclusion of these tests was that the top-ranked GOLD solution was correct in 70-80% of cases.

• Details of the GOLD validation.
• GOLD publications and acknowledgements.

Before using GOLD you should read these pages on how to use the software and how to make sure that the input structures have correct atom typing.

• Getting started.
• How to set up input structures; GOLD atom and bond typing.

These pages contain more detailed descriptions of the various components that comprise GOLD.

• The front end.
• GOLD files and programs.
• GOLD genetic-algorithm and fitness parameters.
• The GOLD parameter file.
• Special cases: metals, covalent bonding, docking with constraints.
• Specifying the problem using PDB input files.
• Specifying the problem using MDL SD input files.
• Using torsional distributions.
• Making GOLD go faster.

These pages document some additional research done with GOLD.

• Some activity studies done with GOLD.
• Docking combinatorial libraries with GOLD.