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Biology & Biomedical Research

GNINA

An open-source command-line program that integrates convolutional-neural-network scoring and ligand optimization into molecular docking.

Last verified

RESEARCH USE

Where GNINA fits

GNINA is most relevant for comparing conventional and neural scoring in protein-ligand docking. It should be treated as one component of a research workflow rather than as a substitute for reading source material, checking methods, or validating scientific conclusions.

What to evaluate before use

  • Check whether its Linux, CLI, GPU workflow fits your existing research environment and export requirements.
  • The recorded access model is open source; limits, institutional terms, and commercial-use conditions may change.
  • Open-source code is available, but code, model weights, hosted services, and data may have different licenses. Review the relevant terms separately.

Verification note

This entry summarizes the tool's role without assessing scientific accuracy or endorsing its outputs. Features and terms can change; consult the official source before adopting it for consequential work.

molecular dockingdeep learning

Last verified: 2026-08-31
Source: official documentation ↗