Identification of novel carbonic anhydrase II receptor-targeting drugs for treating myocardial infarction through the mechanism of Xue-Fu-Zhu-Yu decoction.
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引用次数: 0
Abstract
Myocardial infarction (MI) is a significant threat to human health and life. Xue-Fu-Zhu-Yu Decoction (XFZYD), a renowned traditional Chinese medicine prescription for treating myocardial infarction, is known to play a significant role in the management of MI. However, its mechanism of action remains unclear. Through network pharmacology analysis of compound-target interactions, we have identified Carbonic Anhydrase II (CA2) as a critical target for XFZYD in the treatment of MI. Subsequently, we will embark on a target-based drug design approach with a focus on CA2 as the key target: Pharmacophore modeling: Two pharmacophore models were developed and validated to screen for small molecules with CA2 inhibitory features. Virtual screening: Based on two pharmacophore models, small molecules with the property of binding to the CA2 target were screened from a virtual screening library. Molecular docking: Molecular docking was employed to identify small molecules with stable binding affinity to CA2. ADMET prediction: ADMET models were utilized to screen for small molecules with favorable pharmacological properties. Molecular dynamics: Molecular dynamics simulations were further conducted to analyze the binding modes of the selected small molecules with CA2, ultimately resulting in the identification of Ligand 3 and Ligand 5 as small molecule inhibitors targeting CA2. Finally, the mechanisms underlying the anti-MI effects were discussed. The primary objective of this article is to uncover the mechanism by which XFZYD acts on MI and utilize it for drug development. These findings provide novel avenues for the development of anti-MI drugs.Communicated by Ramaswamy H. Sarma.
期刊介绍:
The Journal of Biomolecular Structure and Dynamics welcomes manuscripts on biological structure, dynamics, interactions and expression. The Journal is one of the leading publications in high end computational science, atomic structural biology, bioinformatics, virtual drug design, genomics and biological networks.