Add OpenFold workflow

[athbaltzis]

Description of feature

Integrate OpenFold into the nf-core/proteinfold pipeline. OpenFold is a faithful but trainable PyTorch reproduction of AlphaFold2.

OpenFold has the following advantages over the reference implementation:

• Faster inference on GPU, sometimes by as much as 2x. The greatest speedups are achieved on (>= Ampere) GPUs.
  Inference on extremely long chains, made possible by our implementation of low-memory attention (Rabe & Staats 2021). OpenFold can predict the structures of sequences with more than 4000 residues on a single A100, and even longer ones with CPU offloading.
• Custom CUDA attention kernels modified from FastFold's kernels support in-place attention during inference and training. They use 4x and 5x less GPU memory than equivalent FastFold and stock PyTorch implementations, respectively.
• Efficient alignment scripts using the original AlphaFold HHblits/JackHMMER pipeline or ColabFold's, which uses the faster MMseqs2 instead.
• FlashAttention support greatly speeds up MSA attention.

Source code: https://github.com/aqlaboratory/openfold
Publication: https://www.biorxiv.org/content/10.1101/2022.11.20.517210v2