For the general question of pharma investing in structure prediction, I think participants in CASP overestimate the importance of structure. It is nice to have and there certainly are structure-driven projects, but docking is so poor that often computational models of how a molecule binds, even when you have a structure of a protein, are unreliable and there are plenty of case studies of them sending teams in the wrong direction. This would only be worse in the case of AlphaFold since, as the post shows, GDT_HA is still quite poor.
From my experience in research, pharma has found that cellular models and phenotypic assays are far more meaningful for pushing projects forward. So, there is far more interest in applying machine learning to that data than for building protein structures. And those same methods can be applied to target-based projects regardless of whether you have structure. And regardless of how flexible your protein is. Huge portions of structure-based modeling has no ability to deal with protein flexibility, even if you know there are open and closed conformations of the protein or a loop that adopts half a dozen configurations.
Basically, academics working on folding often believe far too much in the importance of structure in drug discovery. The author appears to fall into that category.
From my experience in research, pharma has found that cellular models and phenotypic assays are far more meaningful for pushing projects forward. So, there is far more interest in applying machine learning to that data than for building protein structures. And those same methods can be applied to target-based projects regardless of whether you have structure. And regardless of how flexible your protein is. Huge portions of structure-based modeling has no ability to deal with protein flexibility, even if you know there are open and closed conformations of the protein or a loop that adopts half a dozen configurations.
Basically, academics working on folding often believe far too much in the importance of structure in drug discovery. The author appears to fall into that category.