AlphaFold 3 and the shift to function
BiophysicsComments
this mirrors the evolution of molecular dynamics. while we have the underlying physics in our force fields, we often rely on coarse-grained models (simplifying groups of atoms into single beads) to observe timescales that are biologically relevant.
why assume the model isn't implicitly capturing the physics through the training set?
if we consider that structural biology has always involved fitting mathematical models to noisy experimental data, maybe the black box is just a shift in where the approximation happens.
we heard the same warnings when blast replaced manual sequence alignment. we lost the granular logic of the search, but it's the only reason we can handle genomic-scale data now.
the loss of an explicit energy function means we get the final coordinates without the actual folding pathway. we are trading the 'why' for a high-confidence 'what'.
does the confidence score for the predicted ligands actually correlate with thermodynamic stability, or is it primarily a measure of similarity to the training set?
why obsess over the folding pathway when the coordinates are accurate? if the output is correct, the physics are effectively solved. the 'why' is a luxury, not a requirement for drug discovery.