Rowan
@RowanSci
molecular design and simulation tools for scientists. (also see our literature-posting account @RowanReads.) (cover image from @owl_posting)
Our platform's changed a lot since we recorded our last "Intro to Rowan" video!
We've just refreshed our "Intro to Rowan" demo video that walks through our web-based computational chemistry platform + its features. If you're curious about what @RowanSci is or what it does, take a look!
This new BDE-prediction workflow is live for Rowan subscribers!
New preprint! Bond-dissociation energies tell us how strong bonds are; these values are useful but historically slow to compute. Can modern low-cost methods fix this? Jonathon Vandezande and I gathered a dataset of experimental BDEs (below) and benchmarked lots of methods.
New preprint! Bond-dissociation energies tell us how strong bonds are; these values are useful but historically slow to compute. Can modern low-cost methods fix this? Jonathon Vandezande and I gathered a dataset of experimental BDEs (below) and benchmarked lots of methods.
@RowanSci is making molecular modeling actually usable, so I built an MCP server that lets you access their tools through natural conversation.
You can now download structures from Rowan as .sdf files, making it significantly easier to load outputs from Rowan into the rest of the ecosystem of life-science software! From a completed calculation, this takes just two clicks:
Great to see Rowan's redox potential and Fukui-index calculations used to help with total synthesis. Congrats @mccarson23 @KozlowskiMarisa and co-workers!
Redox calculations performed on @RowanSci informed some of the observed chemo- and regioselectivity of the phenol coupling.
In January, we released a workflow to quantify the strength of hydrogen-bond acceptors in complex molecules. Since then, lots of scientists have asked us "what about hydrogen-bond donors?" As of today, we've updated our paper and workflow to also compute donor strength:
Few know this, but Rowan hosts a free 2D/3D structure viewer and editor at labs.rowansci.com/editor. You can go from SMILES to .xyz, edit structures, change dihedrals, add a periodic cell, and download the final structure—all totally free, no account needed. Here's a quick demo:
The past few years of "AI for life sciences" has been all about the models: AF3, NNPs, PLMs, binder generation, docking, co-folding, ADMET, &c. But Chai-2, and lots of related work, shows us that the vibes are shifting. Models themselves are becoming just a building block; the…
What is Chai-2? It is a "series of models." This includes a "multimodal generative architecture, integrating all-atom structure prediction and generative modeling" (to me this sounds like AF3 and their earlier Chai-1). The release is a bit vague; this graphic is the best info: