A computational chemistry-based approach to optimizing PD-1/PD-L1 inhibitors

基于计算化学的PD-1/PD-L1抑制剂优化方法

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Abstract

INTRODUCTION: To design effective small molecule inhibitors targeting the immune checkpoint PD-1/PD-L1 and to explore their inhibitory activity. METHODS: In this paper, a total of 69 PD-1/PD-L1 inhibitors with the same backbone were searched through opendatabases, and their docking mechanism with PD-L1 protein was investigatedby molecular docking method, and the active conformation of the inhibitors was explored. The biological activity of the four newly designed inhibitors was also evaluated using ELISA. RESULTS: The most active molecule 58 in the dataset formed six hydrogen bonds with Phe67, Val55, Ile116 and Tyr123, while the second most active molecule 34 formed five hydrogen bonds with Phe67 and Ala121, both of which formed π-π stacking interactions with Tyr56. The analysis of the inhibitor docking results determined that the residues Tyr123, Gln66, Thr20, Met115, Asp122 and Ile116 had the greatest influence on the active conformation of the inhibitor. ELISA assays suggested that the four novel inhibitors designed had high inhibition rates, with the inhibition rate of compound N2 being as high as 68.53%. DISCUSSION: In this paper, we have designed and synthesized various PD-1/PDL1 inhibitors, which provide a basis for drug discovery targeting the PD-1/PDL1 signaling pathway.

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