Virtual screening and biological evaluation of natural products as urate transporter 1 (URAT1) inhibitors

Abstract

Hyperuricemia is mainly caused by insufficient renal urate excretion. Urate transporter 1 (URAT1), an organic anion transporter, is the main protein responsible for urate reabsorption. In this study, we utilized artificial intelligence-based AlphaFold2 program to construct URAT1 structural model. After molecular docking and conformational evaluation, four e-pharmacophoric models were constructed based on the complex structures of probenecid-URAT1, benzbromarone-URAT1, lesinurad-URAT1, and verinurad-URAT1. Combining pharmacophore modeling, molecular docking, MM/GBSA calculation and ADME prediction, 25 flavonoids were selected from the natural products database containing 10,968 molecules. Then, a model of HEK-293T cells overexpressing URAT1 was constructed, and the inhibitory activity to URAT1 of 25 flavonoids was evaluated by measuring their effect on cellular uptake of 6-carboxyfluorescein (6-CFL). Fisetin, baicalein, and acacetin showed the best activity with IC₅₀ values of 12.77, 26.71, and 57.30 µM, respectively. Finally, the structure-activity relationship of these three flavonoids was analyzed by molecular docking and molecular dynamics simulations. The results showed that the carbonyl group on C-4 and hydroxyl group on C-7, C-4', and C-5’ in flavonoids were conducive for URAT1 inhibitory effects. This study facilitates the application of flavonoids in the development of URAT1 inhibitors.

Communicated by Ramaswamy H. Sarma

Keywords:

• URAT1
• hyperuricemia
• natural products
• virtual screening
• structure-activity relationship

Author contributions

• Chunying Du: Investigation, formal analysis, visualization, writing—original draft.

• Hua Yin: Project administration, supervision, writing—review & editing.

• Aowei Xie: Data curation, formal analysis, visualization, writing—review.

• Junhong Yu: Project administration, supervision, writing—review & editing.

• Yifan Wang: Investigation, formal analysis, visualization, writing—original draft.

• Fengli Yao: Writing—review & editing.

• Siyu Zhang: Investigation, data curation

• Yidan Zhang: Methodology, writing—review & editing.

• Lu Liu: Investigation, data curation.

• Peng Wang: Conceptualization, project administration, supervision.

• Jianjun Dong: Resources, methodology, data curation.

• Ximing Xu: Resources, methodology, data curation.

Disclosure statement

The authors declare that they do not have any conflicts of interest.

Additional information

Funding

This work was supported by the Qingdao Science and Technology Project (22-3-7-xdny-2-nsh) and the Major Science and Technology Innovation Project of Qingdao West Coast (ZDKC-2022-01), National Nature Science Foundation of China (82373794), and Shandong Provincial Nature Science Foundation (ZR2023MB058).