How to Use OpenFE Absolute Binding Free Energy

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Ligand/Drug Design & Screening Molecular Dynamics & Simulation Free Energy / Binding Energy Molecular Dynamics Small Molecules

Use OpenFE Absolute Binding Free Energy online to estimate binding from a prepared protein and positioned ligand.

Absolute binding free energy (ABFE) estimates the free-energy change associated with transferring one ligand between a protein binding site and solution. It is useful when a relative ligand series is unavailable or when an absolute thermodynamic estimate is needed for one prepared protein-ligand pose.

The Neurosnap workflow accepts a protein-only Input Structure in PDB format and one Input Ligand in SDF format. The SDF supplies both reliable bond orders and the protein-relative 3D coordinates used by OpenFE to construct the restrained alchemical calculation.

How OpenFE Absolute Binding Free Energy Works

Upload a protein-only PDB as Input Structure, then upload one SDF ligand with valid bond orders and 3D coordinates already positioned in the protein binding site. SMILES and CCD entries are rejected because they do not carry the required bound coordinates. The uploaded SDF coordinates are retained and are not geometry-optimized.

Protocol Repeats, Equilibration Length, and Production Length control the sampling effort. OpenFE applies the absolute binding protocol with automatic restraints and reports the binding free energy in kcal/mol with its repeat-derived uncertainty.

What is Neurosnap?

Neurosnap is the leading platform for bioinformatics and computational science focused on expanding access to powerful modeling and simulation tools. Because many state-of-the-art machine learning systems remain complex to install, configure, and scale, Neurosnap offers a clean, browser-based workspace that removes the burden of infrastructure management, dependency conflicts, and command-line tooling.

Built for biologists, chemists, and cross-disciplinary scientists, the platform enables advanced computational workflows without requiring expertise in software engineering or cloud architecture. Researchers can launch analyses through an intuitive interface, connect programmatically through a comprehensive API, and rely on automated resource management to scale workloads efficiently. By taking care of the underlying compute and operational complexity, Neurosnap allows teams to devote their energy to scientific progress and faster iteration. Security and data protection remain foundational principles, with clear safeguards outlined in our Terms of Use and Privacy Policy to ensure your work stays protected.

Advancing Discovery with OpenFE Absolute Binding Free Energy on Neurosnap

Using OpenFE Absolute Binding Free Energy on Neurosnap could drastically accelerate pose-preserving absolute binding free energy calculations from a prepared protein and SDF ligand.

  • Reliable chemistry and geometry: The SDF carries explicit bond orders and the bound 3D pose in one input.
  • Bound-pose preservation: The uploaded ligand coordinates define the simulated complex.
  • Automated restrained cycle: OpenFE constructs the complex and solvent legs with the required restraints.
  • Reproducible controls: Force field, repeats, and sampling lengths remain explicit.

How to Use OpenFE Absolute Binding Free Energy on Neurosnap

To harness the capabilities of OpenFE Absolute Binding Free Energy, researchers can follow this streamlined workflow within Neurosnap:

  1. Access Neurosnap: Start by logging in to the Neurosnap website.
  2. Select Tool: From the list of available tools, choose OpenFE Absolute Binding Free Energy.
  3. Provide Inputs: Provide all the inputs specified within the submission panel and optionally configure the tool as desired.
  4. Run Tool: Submit the OpenFE Absolute Binding Free Energy job and Neurosnap will execute it in the cloud, automatically notifying you as soon as your results are ready.
  5. Review Output: Explore your results through rich visualizations, including figures, plots, and interactive views designed to help you analyze findings with clarity and confidence.

Citations

Please cite the original work when using OpenFE Absolute Binding Free Energy in publications or research outputs.

Alibay, I. et al. The Open Free Energy library. Zenodo, 2025. https://doi.org/10.5281/zenodo.8344247.

Eastman, P. et al. OpenMM 7: Rapid development of high performance algorithms for molecular dynamics. PLOS Computational Biology, 2017. https://doi.org/10.1371/journal.pcbi.1005659.

Shirts, M.R. & Chodera, J.D. Statistically optimal analysis of samples from multiple equilibrium states. The Journal of Chemical Physics, 2008. https://doi.org/10.1063/1.2978177.

Neurosnap Inc. (2022). Neurosnap: An online platform for computational biology and chemistry. Available at: https://neurosnap.ai/

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