Sign in

arianaclerkin.bsky.social

@arianaclerkin.bsky.social
13 followers 26 following 0 posts
PostsRepliesMedia
Reposted by @arianaclerkin.bsky.social
Richard Sever @richardsever.bsky.social · 11/03/2025
Big news: we are setting up a new non-profit organization to run bioRxiv and medRxiv. It's called openRxiv [no it's not a new preprint server; it's dedicated organization to oversee the servers] openrxiv.org 1/n
openrxiv.org
Homepage - openRxiv
openRxiv is an independent non-profit, the new organizational home for bioRxiv and medRxiv, enabling researchers to instantly share groundbreaking findings with the global scientific community.
552558846
Reposted by @arianaclerkin.bsky.social
John Chodera @jchodera.bsky.social · 19/02/2025
Everything is chaos, but I wanted to share some awesome recent science from the lab that hints at where the future of biomolecular simulation is headed: Foundation simulation models that can be fine-tuned to experimental free energy data to produce systematically more accurate predictions.
Figure 1 from arXiv preprint https://doi.org/10.1101/2025.01.06.631610

Fig. 1 Espaloma is an end-to-end differentiable molecular mechanics parameter assignment scheme for arbitrary organic molecules. Espaloma (extensible surrogate potential optimized by message-passing) is a modular approach for directly computing molecular mechanics force field parameters FFF from a chemical graph G such as a small molecule or biopolymer via a process that is fully differentiable in the model parameters FNN. In Stage 1, a graph neural network is used to generate continuous latent atom embeddings describing local chemical environments from the chemical graph. In Stage 2, these atom embeddings are transformed into feature vectors that preserve appropriate symmetries for atom, bond, angle, and proper/improper torsion inference via Janossy pooling.54 In Stage 3, molecular mechanics parameters are directly predicted from these feature vectors using feed-forward neural networks. This parameter assignment process is performed once per molecular species, allowing the potential energy to be rapidly computed using standard molecular mechanics or molecular dynamics frameworks thereafter. The collection of parameters FNN describing the espaloma model can be considered as the equivalent complete specification of a traditional molecular mechanics force field such as GAFF38,39/AM1-BCC55,56 in that it encodes the equivalent of traditional typing rules, parameter assignment tables, and even partial charge models. Reproduced from ref. 49 with permission from the Royal Society of Chemistry.
310530