Tautomer generation speed up

[pechersky]

In the blog, it said

If there are any burning bottlenecks not present in the current set of functions, please do reach out.

In various modeling applications, for bookkeeping of molecules or for physiological-state modeling, one needs to do tautomer enumeration and canonicalization. That is a CPU intensive task that can take an arbitrary amount of time (proportional to complexity of the ligand). It would be great if it could be accelerated.

[scal444]

Thanks for the suggestion!

I looked into this a little, and it seems likely that substructure matching is the main bottleneck in this workflow (will run some perf analyses to double check). That's a topic we've avoided tackling due to the difficulty of reproducing RDKit's recursive query setup and the difficulty of implementing subgraph isomerism on the GPU.

Both of those difficulties are potentially solvable, or at least we could hopefully support enough of SMARTS to cover most usecases. But it would be an experimental development and would take quite some time to even see if it's feasible and if we can get good speedups.

Still, we get a lot of requests for substructure searching so it might be worth the effort to work on it. I'll discuss with my team about our priorities and get back to you.

[pechersky]

Sounds good! Happy to communicate/collaborate. In terms of substructure matching, it's true that it is a very daunting task in the general case. I've had some attempts at more narrow optimizing via trying to port/copy of the steps into the Nauty framework, which is very optimized for that type of work.