molclaw-p2rank

To predict ligand binding pockets from a PDB file, this skill applies P2Rank and fpocket to calculate pocket coordinates, site identifiers, and confidence probabilities. It outputs top-ranked pockets and enforces a minimum 25.0 Å per axis docking box for downstream tools.

Standardizing docking box coordinates for virtual screening requires enforcing a minimum 25.0 Å per axis bounding box. This skill automatically generates these standardized box coordinates centered on top-ranked binding pockets predicted from your input protein structure.

Yes, this pocket detection method works directly with single-structure PDB inputs. It processes the protein structure to rank ligand binding pockets by confidence probability, returning precise pocket coordinates and site identifiers for docking preparation.

fpocket prioritization matters for binding pocket annotation because it serves as an integrated alternative algorithm when P2Rank is not explicitly overridden. This dual-tool approach ensures reliable pocket coordinate selection and consistent confidence scoring for docking preparation.

Yes, you can use these predicted pocket coordinates directly in downstream docking tools. The skill outputs standardized coordinates and enforces a minimum 25.0 Å per axis docking box, ensuring robust compatibility for virtual screening and molecular docking tasks.