虚拟筛选
异羟肟酸
分子动力学
对接(动物)
HDAC1型
组蛋白脱乙酰基酶
计算生物学
酶
化学
组蛋白脱乙酰基酶2
HDAC3型
小分子
药物发现
生物化学
药理学
组蛋白
生物
立体化学
计算化学
医学
基因
护理部
作者
S. M. Esther Rubavathy,V. Rajapandian,Muthuramalingam Prakash
标识
DOI:10.1080/07391102.2024.2325104
摘要
Overexpression of histone deacetylase (HDAC) enzymes is linked to a wide variety of illnesses, including malignancies and neurological disorders, which makes HDAC inhibitors potentially therapeutic. However, most HDAC inhibitors lack subclass or isoform selectivity, which can be dangerous. Featuring both enhanced selectivity and toxicity profiles, slow-binding HDAC inhibitors offer promising treatment options for a variety of disorders. Diseases like cardiac, neurodegenerative disorders and diabetes are mainly associated with the HDAC1, HDAC2 and HDAC3 enzymes. The AI-based virtual screening tool PyRMD is implemented to identify the potential inhibitors from ∼2 million compounds. Based on the IC50 values, the top 10 compounds were selected for molecular docking. From the docking and ADMET study, the top-ranked three compounds were selected for molecular dynamics (MD) simulations. Further, to get more insights into the binding/unbinding mechanism of the ligand, we have employed the steered molecular dynamics (SMD) simulations. This study assists in developing Amber force field parameters for the HDAC1, HDAC2 and HDAC3 proteins and sheds light on the discovery of a potent drug. Our study suggests that hydroxamic acid derivative (i.e. referred to as Comp-1, CHEMBL600072) is the potential inhibitor for the series of HDAC-related diseases.
科研通智能强力驱动
Strongly Powered by AbleSci AI