Are you using it as your main ide?

(8/8) Code is available at github.com/florisvdf/ch....

(7/8) Despite the outcome, this was still a very fun project to work on. Many thanks my supervisors, Henning Redestig and Dick de Ridder, for their excellent guidance, and Luis-Cascao Pereira and David Estell for inspiring us to explore electrostatic quantities of proteins.

(6/8) We suspect the limitations arise from imperfect computational tools, missing biological context (e.g., post-translational modifications, molecular crowding), and treating proteins as static objects. Still, we believe these results could help narrow the search space for future VEP strategies.

(5/8) We trained and evaluated ChargeNet on datasets from ProteinGym, comparing it to evolutionary models both standalone and in ensemble. Across all tests, ChargeNet offered no advantage—suggesting its physical representations don’t add information beyond what evolutionary models already encode.

(4/8) We tried to design a representation that is evolution agnostic and instead relies on the physical properties. This led to ChargeNet—a pipeline that predicts a variant’s structure with FoldX, computes its 3D electrostatic profile with APBS, and feeds that into a 3D CNN for property prediction.

(3/8) SotA VEP models are evolutionary and excel at spotting “unnatural” mutations, which often correlate with loss of function. However, by pretraining only on natural sequences, such models may miss out on mutations that wouldn’t occur in nature, but still lead to interesting changes in function.

(2/8) Unfortunately, our strategy did not yield the results we hoped for; our model is outperformed by existing models in every scenario we tested. Nevertheless, we find it important to share our findings so that others can build on them, refine their approach, or take more promising directions.

Question: Could the experimental uncertainty arise from the dynamics of the protein in solution? And if so, are there examples where this uncertainty strongly correlates with dynamics?

Once again looking amazing. Are you considering at some point curating a gallery to showcase what's possible with molecular nodes? Or does this already exist and did I miss it? 🫣