Identification of novel human Serum Albumin (SA) inhibitors from Scoparia Dulsis for Urolithiasis.

CURRENT COMPUTER-AIDED DRUG DESIGN(2020)

引用 1|浏览2
暂无评分
摘要
Background: Urolithiasis is the process of forming stones in the kidney, bladder, and/or urinary tract. It has been reported that kidney stones are the third most common disorder among urinary diseases. At present, surgical procedures and Extracorporeal Shock Wave Lithotripsy (ESWL) are commonly employed for the treatment of Urolithiasis. The major drawback of these procedures is the recurrence of stones. Methods: This study aimed to identify potential natural inhibitors against human Serum Albumin (SA) from the plant Scoparia Dulsis for Urolithiasis. As protein-ligand interactions play a key role in structure-based drug design, this study screened 26 compounds from Scoparia Dulsis and investigated their binding affinity against SA by using molecular docking. The three dimensional (3D) structure of SA was retrieved from Protein Data Bank (PDB) and docked with PubChem structures of 26 compounds using PyRX docking tool through Autodock Vina. Moreover, a 3D similarity search on the PubChem database was performed to find the analogs of best scored compound and docking studies were performed. Drug-likeness studies were made using Swiss ADME and Lipinski's rule of five was performed for the compounds to evaluate their anti-urolithiatic activity. Results: The results showed that citrusin c (Eugenyl beta-D-glucopyranoside) exhibited best binding energy of -8.1 kcal/mol with SA followed by aphidicolin, apigenin, luteolin and scutellarein. Two compounds (PubChem CID 46186820, PubChem CID 21579141) analogous to citrusin c were selected based on the lowest binding energy. Conclusion: This study, therefore, reveals that these compounds could be promising candidates for further evaluation for Urolithiasis prevention or management.
更多
查看译文
关键词
Urolithiasis,kidney stone,molecular docking,Scoparia Dulsis,serum albumin,extracorporeal shock wave lithotripsy
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要