A concerted, long-term (~10 year) effort to develop the models, theory, and tools necessary to simulate a prokaryotic cell. This is not the kind of thing that’s

A concerted, long-term (~10 year) effort to develop the models, theory, and tools necessary to simulate a prokaryotic cell. This is not the kind of thing that’s being funded by the NIH, given their translational shift, and it’s not the kind of thing that can be done by industry because of the time horizon. Nonetheless it’s foundational to building a quantitatively predictive biology. It’s the sort of thing that can enable entirely new applied sciences and industries. And I think it’s possible. There’s a certain way to doing this which I believe is key to success. It can’t be about doing molecular dynamics from atoms on up, because of computational considerations, and because that’s useless anyway (one wouldn’t learn anything beyond the known physics and maybe better force fields and sampling techniques). It also can’t be like the kludgy attempts that have been made so far (e.g. Markus Covert’s paper in Cell from a few years back—it’s perfectly alright work, but won’t get us closer to solving this particular problem.) Instead, I think the key is to develop a new layer of abstraction for describing biological phenomena, much like say organic chemistry is a genuinely new abstraction built on top of physical chemistry (which is itself built on top of QM), that hides away the irrelevant details (e.g. most of QM) while capturing what’s salient about the biological phenomena of interest. It would require advances in the aforementioned areas of models, theory, and tools, that are made in concert with the aim of simulating a cell.