A comparative structure-based virtual screening approach using an optimized AlphaFold model identified a selective HDAC11 inhibitor. HDAC11, a class IV histone deacetylase, lacks a known crystal structure, making conventional homology modeling less reliable. The study optimized an HDAC11 AlphaFold model by incorporating the catalytic zinc ion and minimizing the structure in the presence of known inhibitors. This model was used for virtual screening to identify novel HDAC11 inhibitors. A stepwise virtual screening process successfully identified a hit compound with an IC50 of 3.5 μM for HDAC11 and selective inhibition over other HDAC subtypes at 10 μM. Molecular dynamics simulations confirmed the binding hypothesis from docking studies. The results highlight the effectiveness of the optimized AlphaFold model in drug discovery, particularly for HDAC11. The study also demonstrated the importance of structural optimization and the role of molecular dynamics in validating binding modes. The identified hit compound showed promising selectivity and binding characteristics, supporting its potential as a new HDAC11 inhibitor. The findings underscore the utility of AlphaFold models in virtual screening for drug discovery, especially for targets with limited structural information.A comparative structure-based virtual screening approach using an optimized AlphaFold model identified a selective HDAC11 inhibitor. HDAC11, a class IV histone deacetylase, lacks a known crystal structure, making conventional homology modeling less reliable. The study optimized an HDAC11 AlphaFold model by incorporating the catalytic zinc ion and minimizing the structure in the presence of known inhibitors. This model was used for virtual screening to identify novel HDAC11 inhibitors. A stepwise virtual screening process successfully identified a hit compound with an IC50 of 3.5 μM for HDAC11 and selective inhibition over other HDAC subtypes at 10 μM. Molecular dynamics simulations confirmed the binding hypothesis from docking studies. The results highlight the effectiveness of the optimized AlphaFold model in drug discovery, particularly for HDAC11. The study also demonstrated the importance of structural optimization and the role of molecular dynamics in validating binding modes. The identified hit compound showed promising selectivity and binding characteristics, supporting its potential as a new HDAC11 inhibitor. The findings underscore the utility of AlphaFold models in virtual screening for drug discovery, especially for targets with limited structural information.