structural-biology

AlphaFold confidence scores are interpreted using pLDDT for local backbone accuracy and PAE for domain relative positioning. This Skill retrieves AlphaFold DB structures by UniProt accession and annotates these confidence metrics to map functional regions accurately.

To download AlphaFold predicted protein structures in PDB format, provide a UniProt accession to retrieve coordinate data. This Skill fetches AlphaFold DB predictions and generates ready-to-use CIF or PDB coordinate files for downstream structural biology analyses.

Mapping functional regions onto a protein structure requires cross-referencing UniProt features with AlphaFold coordinates. This Skill annotates sequence features across the retrieved 3D structure, using pLDDT scores to validate the biological relevance of mapped functional domains.

Yes, you can retrieve AlphaFold structures for novel protein sequences using sequence context. The Skill applies Python-based workflows to access AlphaFold DB, interpret pLDDT and PAE metrics, and generate confidence reports for novel targets without direct UniProt accessions.

Yes, Python is required to annotate AlphaFold structures and generate confidence reports. The Skill relies on Python-based workflows to access AlphaFold DB, download coordinates, interpret pLDDT and PAE metrics, and produce ready-to-use CIF or PDB files.