7건 · 관련도순
Multi-method binding pocket detection and druggability assessment. Grid-based, fpocket, and P2Rank detection with druggability scoring, visualization, and cross-structure comparison.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Decide whether a protein has a pocket worth targeting, and where it is, before committing to a docking or design campaign. Use this skill to run fpocket cavity detection, rank cavities by druggability and volume, compare apo and holo conformations to spot induced fit, identify allosteric and cryptic cavities that only open in simulation, and convert a chosen cavity into the search box coordinates a docking run needs. Also trigger on fpocket, cavity detection, druggability score, alpha sphere, cryptic pocket, allosteric site, pocket volume, hotspot mapping, or undruggable target assessment.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Performs structure-based virtual screening using AutoDock Vina, SMINA, GNINA (CNN scoring), and DiffDock-L hybrid workflows with explicit choice rules across rigid vs flexible docking, cross-docking vs self-docking, binding-site detection (P2Rank, fpocket), receptor preparation (PDB2PQR, PROPKA), ligand preparation (meeko, OpenBabel), and ultralarge-library screening (ZINC22, Enamine REAL). Use when screening chemical libraries against a protein target to find candidate binders, ranking docking poses, or selecting a docking workflow for a specific scenario.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Performs structure-based virtual screening using AutoDock Vina, SMINA, GNINA (CNN scoring), and DiffDock-L hybrid workflows with explicit choice rules across rigid vs flexible docking, cross-docking vs self-docking, binding-site detection (P2Rank, fpocket), receptor preparation (PDB2PQR, PROPKA), ligand preparation (meeko, OpenBabel), and ultralarge-library screening (ZINC22, Enamine REAL). Use when screening chemical libraries against a protein target to find candidate binders, ranking docking poses, or selecting a docking workflow for a specific scenario.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
End-to-end molecular docking pipeline. Target preparation, pocket detection, protein-ligand docking (DiffDock/Vina), scoring, interaction analysis, and pose ranking.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Performs structure-based virtual screening using AutoDock Vina, SMINA, GNINA (CNN scoring), and DiffDock-L hybrid workflows with explicit choice rules across rigid vs flexible docking, cross-docking vs self-docking, binding-site detection (P2Rank, fpocket), receptor preparation (PDB2PQR, PROPKA), ligand preparation (meeko, OpenBabel), and ultralarge-library screening (ZINC22, Enamine REAL). Use when screening chemical libraries against a protein target to find candidate binders, ranking docking poses, or selecting a docking workflow for a specific scenario.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Performs structure-based virtual screening using AutoDock Vina, SMINA, GNINA (CNN scoring), and DiffDock-L hybrid workflows with explicit choice rules across rigid vs flexible docking, cross-docking vs self-docking, binding-site detection (P2Rank, fpocket), receptor preparation (PDB2PQR, PROPKA), ligand preparation (meeko, OpenBabel), and ultralarge-library screening (ZINC22, Enamine REAL). Use when screening chemical libraries against a protein target to find candidate binders, ranking docking poses, or selecting a docking workflow for a specific scenario.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.