Modern molecular modeling needs a new mode of software development. Consortia like Open Free Energy build shared tools and release code under open licenses. @omsf.io aligns incentives across stakeholders, enabling an ecosystems that elevates the entire community. pubs.acs.org/doi/10.1021/...
We’re pleased to announce the 2026 OpenFF Virtual Workshops! Please join us in March and April for workshops on:
- Simulating Post-Translationally Modified Proteins with the OpenFF Rosemary Alpha
- Fitting a SMIRNOFF Force Field with PyTorch
Details linked:
docs.openforcefield.org/en/latest/wo...
Check out the recent webinar that our own Alyssa Travitz gave to @sbgrid.bsky.social, introducing our software!
youtu.be/nCvg13F9Pco
Join our software webinar on February 10th to hear from Alyssa Travitz of the @omsf.io on @openfree.energy: An Open Source Ecosystem for Calculating Free Energies.
Tuesday, February 10, 2026 - 12:00pm ET
Register here: buff.ly/N7AYdjp
#SBGrid #Webinars #StructuralBiology
Hey folks, @omsf.io is hiring a UX Engineer, our first in the org! We are looking for someone to work with us to build new experiences for computational chemists on a part-time contract basis! If this sounds cool, please apply! We would love to have you! omsf.io/community/jo...
What if you could tap into the computational power of thousands of volunteers worldwide to accelerate your drug discovery efforts? That’s what we’ve done by integrating alchemiscale and @openfree.energy with Folding@Home!
Read more: alchemiscale.org/advancements...
#openscience #drugdiscovery
In October of 2025 we released alchemiscale v0.7.0, and followed this up with v0.7.1 and v0.7.2. We wanted to take a moment to highlight these releases, and the improvements they bring for @openfree.energy users!
alchemiscale.org/advancements...
#compchem #opensource #alchemistry #openscience
OpenBind is a new open science effort to dramatically increase the number of protein:ligand structures in the PDB, pairing this with high-quality affinity data to enable a new generation of predictive structure and affinity models for drug discovery. Check it out: openbind.ai
Exciting news! We have a new website: omsf.io/alchemistry
Your one-stop shop for everything related to our conference community. 🎉
BTW, registration is now open, so head over to secure your spot! We'll be sharing updates and details about the event.
Bookmark it as there's plenty more to come!
To our knowledge, this is the first study to report binding free energy benchmarks on a cross-company collection of proprietary datasets. We couldn't have done it without the hard work of our amazing partner companies!
Across a total of 1,700 ligands, OpenFE shows robust performance, generates reproducible results, and achieves both sufficient throughput and rapid convergence.
Our protocol:
- ranks compounds about as well as commercial solutions
- does not require fine-tuning settings for each system
OpenFE is ready for production! chemrxiv.org/engage/chemr...
In collaboration with our industry partners, we ran benchmarking simulations of our hybrid-topology RBFE protocol on a large collection of both public and private protein-ligand binding datasets.
#compchem
Left to right: Mike Henry, Alyssa Travitz, Irfan Alibay, Jennifer Clark, Jeffrey Wagner, Hugo McDermott-Opeskin
Jeff Wagner and Jen Clark ran a workshop at the @mdanalysis.bsky.social UGM in Arizona last week, in coordination with the @openfree.energy team.
Our docs have you covered! We have a "cookbook" demonstrating how to use our API for a variety of tasks in setting up free energy calculations. docs.openfree.energy/en/latest/co...
Our command line interface (CLI) is designed to provide easy access to our tested, production-ready workflow. But if you are developing new methods or pioneering workflows, you may need the power and flexibility of our application programming interface (API) in #Python. #compchem
We've just released openfe v1.7, which includes includes new protocols for Separated Topologies and Absolute Binding Free Energies, as well as up to 2x faster simulations using the default settings.
openfree.energy/science/upda...
We tested Sage 2.3.0rc2 from @openforcefield.org in RBFE benchmarks and found it improves accuracy on some of our benchmark systems like p38. Can't wait to see the GNN charge model become default!
We’re pleased to announce Sage 2.3.0 Release Candidate 2 (rc2)! Sage 2.3.0 will be the first OpenFF force field to use the AshGC neural network charge model, which was trained to AM1BCC ELF10 charges, and allows for rapid charge assignment for molecules with hundreds or thousands of heavy atoms.
Save the date, my fellow computational alchemists! The upcoming '26 Workshop on Free Energy Methods in Drug Design will be held in Barcelona, Spain, on May 4-6, 2026. The registration link will be sent soon!
OpenFE is being used to predict affinity of molecular glues!
Check out the new preprint from the team at Ternary Therapeutics: chemrxiv.org/engage/chemr...
You can find more information starting on slide 20 in our February 2025 update presentation: zenodo.org/records/1486...
To address these challenging cases, the Open Force Field Intitiative provides a tool, “BespokeFit,” for generating custom parameters for the specific chemistry of a target molecule. These custom (or “bespoke”) parameters can be used in RBFE calculations in OpenFE.
Our default force field, OpenFF “Sage,” works well on a wide variety of organic molecules relevant to drug design. However, projects involving more exotic functional groups may be limited by low force field accuracy.
Did you know you can use custom force field parameters in OpenFE? Try out this cookbook to learn more! docs.openfree.energy/en/latest/co... #compchem
This is such cool work. Ivan from the Chodera Lab is implementing a protein mutation protocol in OpenFE, and we can't wait to see what incredible studies people do with it!
It's great to see this work in print! It's not on our roadmap this year, but in the longer term we are interested in optimizing replica spacing and will look closely at your method.
But the ability of Boltz-2 to predict affinity opens up new possibilities for drug design workflows, like the Affinity Funneling approach that David Pearlman describes here.
medium.com/@dapscience/...
Alchemical free energy simulations will remain a crucial step in teh drug design process for their accuracy and reliability, especially in binding pockets that rearrange to accommodate different ligands.
www.deepmirror.ai/post/boltz-2...
#opensource #compchem #boltz2
It's exciting to see our software used as a benchmark for cutting-edge AI methods!
This poster illustrates the substantial flexibility of the open source @openfree.energy ecosystem, enabling unconventional approaches for applying free energy methods. As this ecosystem continues to evolve, I'm excited to see what users do with the advancements we make!
