Refine Active Residue Selection: Consider expanding your selection of active residues. If you only identified a few active residues, it might be worth revisiting the literature or using computational tools to predict potential binding sites. Use bioinformatics tools like site prediction algorithms or sequence conservation analysis to identify additional potential active residues.

Include Flexibility: Incorporate flexibility in your docking simulations. Proteins are dynamic entities, and allowing flexibility in certain regions may improve the accuracy of the predictions. HADDOCK allows you to define flexible regions during the docking process. Consider including flexibility in the regions that are likely to undergo conformational changes upon binding.

Run Multiple Docking Runs: Run multiple docking simulations with different initial configurations and input parameters. This will help you assess the robustness of the results and reduce the likelihood of obtaining false positives.

Perform Post-docking Analysis: After obtaining docking results, perform thorough analysis to validate the predicted binding modes. Check if the predicted complexes are in agreement with experimental data or known binding interfaces.

Utilize Experimental Data: If available, consider incorporating experimental data, such as mutagenesis studies or structural information, to guide the selection of active residues or validate the predicted binding modes.

Consider Solvent Effects: Take into account the solvent effects during docking. HADDOCK allows you to consider solvent molecules during the simulation, which can affect the accuracy of the predictions.

Sargol Mazraedoost Thank you so much for your advice. I have solved the issues. :)

Nur Arshad Good Luck