GOLD

GOLD: the validated, configurable protein-ligand docking software for expert drug discovery. For virtual screening through to lead optimization.

Customize with constraints to guide results towards known features or behaviours, and assess the impact of water molecules on the docking. Or use the wizard for quick protein-ligand docking results.

The extensively validated scoring functions in GOLD are trusted by scientists globally for pose prediction and virtual screening - with results seen across the literature.


Selective inhibitor SC-558 docking
Selective inhibitor SC-558 docking with the 1CX2 structure of COX-2 in GOLD


Features

Pose prediction

Pose prediction.

Validate your ligand docking results and optimise hits to leads.


Configurable constraints

Highly configurable constraints.

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


Scoring functions

Multiple scoring functions.

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


Flexible docking

Flexible docking.

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


water handling

Water handling.

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


Hit identification

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.


Learn more

  

Case Study: GOLD virtual screen to repurpose drugs for COVID-19


FAQs

How do I choose a scoring function?

  • 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.

 

What constraints can be applied when docking with GOLD?

 

What does GOLD stand for?

  • 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.

 

Can GOLD be used with multi-threading?

  • 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.

 

For technical FAQs and user guidance see our support resources here.

 


GOLD docking in the literature

Binding to GPCR target with a good fit to experimental results

Salmas et al, ACS Chem. Neurosci. 2017

Binding affinity calculations of antipsychotics binding to dopamine receptor D2 (D2R), a GPCR target, were performed using GOLD. Ensemble docking and single-target docking were performed. Results fit well with experimental results.

Combining GOLD scoring functions for binding insights

Greenidge et al, Chem. Bio. & Drug Design. 2016

Here a group at Novartis rank the performance of the ChemPLP scoring function in GOLD. They find that combining different algorithms and scoring functions including GOLD provides the best insight - a function now possible through the Python API.

Whitepaper: Ultra-large docking with GOLD using cloud resources

CCDC - Download here

This whitepaper uses GOLD with AWS cloud to run docking against an ultra-large library of compounds. The paper covers the setup, security, costs, and results of the test and finds a good return of known active molecules among the ~126 million structures docked from ZINC.

Binding natural products and designing novel mimetics

Merk et al, J. Med. Chem. 2018

Three novel natural products targeting the retinoid X receptor were investigated using GOLD by a group at ETH Zurich. One was found to bind selectively to the beta form and served as a template for ligand-based design of novel mimetics.

 

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