msa-search-nim

To generate multiple sequence alignments for protein structure prediction, you can use GPU-accelerated MMSeqs2 via the ColabFold MSA-Search NIM. This skill creates A3M alignments from protein sequences using the UniRef30 database.

Yes, you can run MSA generation locally by deploying the ColabFold MSA-Search NIM via a local Docker container with appropriate database volumes. This supports both standard monomeric alignments and paired alignments for protein complexes.

The best way to accelerate homolog search for protein folding workflows is using GPU-accelerated MMSeqs2. This skill interfaces with the ColabFold MSA-Search NIM to rapidly generate alignments and retrieve structural templates for downstream folding models.

Yes, the msa-search-nim skill supports structural template retrieval for downstream folding models. It generates multiple sequence alignments and retrieves structural templates to accelerate your protein structure prediction pipelines.

No, you do not need a hosted NVIDIA API key to perform protein complex alignments. Flexible deployment supports both hosted NVIDIA API calls and local Docker-based NIM deployment for data privacy and high-throughput needs.

GPU-accelerated MMSeqs2 addresses the computational bottleneck of generating multiple sequence alignments for biomolecular sequences. It provides rapid homolog search and alignment compared to standard approaches, streamlining protein structure prediction workflows.