Gabriele Corso, co-founder of Boltz, describes wet-lab validation results for targets with no known interactions in the PDB training set.
Opinion
Specialized Equivariant Architectures Vastly Outperform Simple Transformers in Molecular ML
“This field is one of the I would argue very few fields in applied machine learning where we still have kind of architecture. They are Very specialized. And, you know, there are many people that have tried to replace these architectures with, you know, simple t…”
Assertion Supported
Boltz-1 Was the First Open-Source Model Matching AlphaFold 3 Accuracy
“We went ahead and built Pulse One, which was the first fully open source kind of model to approach the level of accuracy of half-fold-free.”
Assertion Supported
Generative Molecular Models Exhibit Dramatic Inference-Time Compute Scaling
“These days we're seeing kind of pretty dramatic inference time scaling of these models where, you know, the more you run them, the better the results are.”
Insight
Model Structural Confidence Is a Poor Predictor of Binding Affinity
“Unfortunately, confidence is not a very good predictor of affinity.”
Assertion Not checkable as stated
Most Protein Design Validation Uses Targets With Training Data Overlap
“One of the things that, you know, we found, ah, with the field was that a lot of the validation, especially outside of the validation that was done on specific problems, was done on targets that have a lot of, you know, known interactions in, in the training d…”
Insight
AlphaFold Resolves Protein Structures Using Dijkstra-Like Pairwise Distance Decoding
“From this evolutionary information about potential contacts, Then it's almost as if the model is sort of running some kind of, you know, Diestro algorithm, where it's sort of decoding, okay, these have to be closed, okay, then if these are closed and this is c…”