> In that sense life is obviously not a computation: it makes some sense to view DNA as symbolic but it is misleading to do the same for the proteins they encode.

Proteins can also be seen as sequence of symbols: one symbol for each aminoacid. But that's beyond the point. Computational theory uses Turing Machines as a conceptual model. The theories employ some human-imposed conceptual translation to encode what happens in a digital processor or a Lego computer, even if those are not made with a tape and a head. Anybody who actually understands these theories could try to make a rigorous argument of why biological systems are Turning Machines, and I give them very high chances of succeeding.

> These proteins are solving physical problems, not expressing symbolic solutions to symbolic problems

This sentence is self-contradictory. If a protein solves a physical problem and it can only do so because of its particular structure, then its particular structure is an encoding of the solution to the physical problem. How can that encoding be "symbolic" is more of a problem for the beholder (us, humans), but as stated before, using the aminoacid sequence gives one such symbolic encoding. Another symbolic encoding could be the local coordinates of each atom of the protein, up to the precision limits allowed by quantum physics.

The article correctly states that biological computation is full of randomness, but it also explains that computational theories are well furnished with revolving doors between randomness and determinism (Pseudo-random numbers and Hopfield networks are good examples of conduits in either direction).

> ... whatever.

Please don't use this word to finish an argument where there are actual scientists who care about the subject.