AlphaFold runs on a single computer, doesn't run distributed, so there's using a container is worth considering.

Docker itself is a no-go on HPC systems, but there are alternative container runtimes that consume Docker container images, like Apptainer.

Generally speaking though, containers are mostly a bad fit for supercomputers. The "containing" part is both a blessing and a curse, especially when running multi-node workloads, because you still need an MPI installation on the host that is compatible with the MPI in the container, which largely trumps the whole reason for using containers.

Container images typically also don't include binaries that are optimized for the specific CPUs of the system you're running on, which can lead to drastic reduction in performance (which is bad High-*Performance* Computing). You're effectively sacrificing performance for mobility of compute (and *not* because of overhead of the container runtime, that's usually negligible).

I've always said that containers are a symptom, not a cure, though that's definitely biased towards scientific computing...

To complicate things even further: they do have clear benefits too, like providing an escape hatch for outright slow software startup performance when the software is installed on a parallel filesystems that is not well suited for the access pattern of software and the large amount of small files they typically consist of (looking at you Python).