We provides advanced protein–protein and protein–ligand / peptide docking services, integrating physics-based molecular docking with AI- and quantum-enhanced scoring strategies. The goal is simple but uncompromising: to identify realistic binding modes, characterize interaction interfaces, and prioritize hypotheses that are most likely to survive experimental validation.
This service is designed not as a standalone computation, but as a core component of protein analysis, bridging sequence, structure, and functional readouts.
Key Capabilities
- Multi-level docking strategies
From global rigid docking to local flexible refinement, enabling efficient exploration of conformational space while preserving biological plausibility. - High-confidence scoring and ranking
Combined energy functions and AI-assisted evaluation reduce false positives and highlight interaction modes closest to native states. - Interface and hotspot analysis
Detailed mapping of hydrogen bonds, hydrophobic contacts, salt bridges, and key residues critical for binding strength and specificity. - Experiment-ready outputs
Docking results are formatted to directly support downstream validation such as SPR, BLI, TR-FRET, Co-IP, mutagenesis, and functional assays.
Typical Applications
- Mechanistic analysis of novel protein–protein interactions
- Binding mode prediction and optimization for antibodies, protein therapeutics, and multispecific formats
- Early-stage design and prioritization of PPI inhibitors or stabilizers
- Structural interpretation of ambiguous or conflicting experimental data
Why Protein Docking Belongs in Protein Analysis
Docking is not just modeling—it is analytical reasoning at the molecular level. By integrating docking into the protein analysis workflow, KUAI enables a closed loop where computational prediction informs experiments, and experimental data refines computation.