Biochemistry and Drug Discovery Lab, Institute of Advanced Study in Science and Technology, Assam, India.
Department of Molecular Biology and Biotechnology, Cotton University, Panbazar, Assam, India.
J Biomol Struct Dyn. 2022;40(24):13799-13811. doi: 10.1080/07391102.2021.1994877. Epub 2021 Oct 28.
Over the years, FK506-binding proteins have been targeted for different pharmaceutical interests. The FK506-binding protein, encoded by the 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 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.
多年来,FK506 结合蛋白一直是各种药物研发的目标。FK506 结合蛋白由 基因编码,与应激和代谢相关的疾病有关,包括癌症。此外,蛋白质的 FKBD-I 结构域是内分泌相关生理疾病的潜在靶点。在本研究中,使用 策略(即药效团建模、分子对接和分子动力学模拟)从 ZINC 数据库中筛选了一组天然化合物,针对 FKBP51 蛋白。采用基于蛋白质配体的药效团模型工作流程来识别小分子。然后使用 ADMET 预测评估所得化合物的毒性。基于 ADMET 预测,选择 4768 种化合物进行分子对接,以阐明其结合模式。根据结合能,选择 857 种化合物,并计算其相似性 Tanimoto 系数,然后根据 Jarvis-Patrick 聚类方法(Jarp)进行聚类。聚类后的单一组分得到 14 个命中化合物。然后对前 05 个命中化合物和 05 个已知化合物进行 100 ns MD 模拟,以检查复合物的稳定性。研究表明,所选复合物在整个 100 ns 模拟过程中都是稳定的;与 FKBP-51(1KT0)晶体结构相比,FKBD-I(4TW6)晶体结构。最后,使用分子力学能量结合泊松-玻尔兹曼方法计算命中复合物的结合自由能。数据表明,所有复合物均显示负的 BFEs,表明命中化合物与蛋白质具有良好的亲和力。因此,前五名化合物是 FKBP51 的潜在抑制剂。