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Pose prediction

Validate your ligand docking results and optimise hits to leads.

Highly configurable constraints

Use your existing knowledge of the system to bias results and focus on known features and behaviours.

Multiple scoring functions

Score and rescore to build a full picture of your system or perform consensus scoring.

Flexible docking

Perform ensemble docking or handle flexible side-chains with soft potentials.

Water handling

Assess how structural waters affect binding, and see if the ligand displaces waters or mediates the interaction during docking.

Virtual screening

Unlimited potential with virtual screening powered by cloud or cluster (HPC).

Python API access

Run dockings programmatically - for parameter optimisation and workflow incorporation.

KNIME component

Perform protein-ligand docking in the KNIME interface to easily build into pipelines of work.

Covalent docking

Understand irreversible binding with covalent docking to explore cancer, immunology, and infectious disease targets.

Included in
Use Cases
Someone using a laptop with the GOLD software shown on screen.

Introduction to docking using GOLD


GOLD offers a range of fitness functions including GoldScore, ChemScore, ChemPLP, and ASP. ChemPLP is a good default to start with, but you can explore the different options depending on your system. See more in the user guide here.

Applying constraints allows you to bias the protein-ligand docking results to account for known features and behaviours.

GOLD allows distance constraints, hydrogen bond constraints, region (hydrophobic) constraints, pharmacophore constraints, similarity constraints, scaffold match constraint and interaction motif constraint to be applied during docking.

GOLD has been validated in the following peer-reviewed publications;

GOLD stands for Genetic Optimisation for Ligand Docking. It is a software based on a genetic algorithm, for docking flexible ligands into protein binding sites.

No, however, we do have high-performance cluster (HPC) tools for virtual screening, and the Python API to write small-scale parallelization scripts. GOLD performs well in a single thread for standard tasks.

GOLD supports common input and output files including .mol (MDL sd), .mol2 (Tripos), .pdb, and .ent.

For a full up-to-date list of file types GOLD supports see our technical FAQ in our knowledgebase here.