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Over the years, FK506-binding proteins have been targeted for different pharmaceutical interests. The FK506-binding protein, encoded by the FKBP5 gene, is responsible for stress and metabolic-related disorders, including cancer. In addition, the FKBD-I domain of the protein is a potential target for endocrine-related physiological diseases. In the present study, a set of natural compounds from the ZINC database was screened against FKBP51 protein using in silico strategy, namely pharmacophore modeling, molecular docking, and molecular dynamic simulation. A protein-ligand-based pharmacophore model workflow was employed to identify small molecules. The resultant compounds were then assessed for their toxicity using ADMET prediction. Based on ADMET prediction, 4768 compounds were selected for molecular docking to elucidate their binding mode. Based on the binding energy, 857 compounds were selected, and their Similarity Tanimoto coefficient was calculated, followed by clustering according to Jarvis-Patrick clustering methods (Jarp). The clustered singletons resulted in 14 hit compounds. The top 05 hit compounds and 05 known compounds were then subjected to 100 ns MD simulation to check the stability of complexes. The study revealed that the selected complexes are stable throughout the 100 ns simulation; for FKBD-I (4TW6), crystal structure compared with FKBP-51 (1KT0) crystal structure. Finally, the binding free energies of the hit complexes were calculated using molecular mechanics energies combined with Poisson-Boltzmann. The data reveal that all the complexes show negative BFEs, indicating a good affinity of the hit compounds to the protein. The top five compounds are, therefore, potential inhibitors for FKBP51. Communicated by Ramaswamy H. Sarma.