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Introduction: The PICK1 PDZ domain has been identified as a potential drug target forneurological disorders. After many years of effort, a few inhibitors, such as TAT-C5 and mPD5,have been discovered experimentally to bind to the PDZ domain with a relatively high bindingaffinity. With the rapid growth of computational research, there is an urgent need for more efficientcomputational methods to design viable ligands that target proteins.Method: Recently, a newly developed program called AfDesign (part of ColabDesign) at https://github.com/sokrypton/ColabDesign), an open-source software built on AlphaFold, has beensuggested to be capable of generating ligands that bind to targeted proteins, thus potentially facilitatingthe ligand development process. To evaluate the performance of this program, we exploredits ability to target the PICK1 PDZ domain, given our current understanding of it. We found thatthe designated length of the ligand and the number of recycles play vital roles in generating ligandswith optimal properties.Results: Utilizing AfDesign with a sequence length of 5 for the ligand produced the highest comparableligands to that of prior identified ligands. Moreover, these designed ligands displayed significantlylower binding energy compared to manually created sequences.Conclusion: This work demonstrated that AfDesign can potentially be a powerful tool to facilitatethe exploration of the ligand space for the purpose of targeting PDZ domains.