Deep simulated annealing for the discovery of novel dental anesthetics with local anesthesia and anti-inflammatory properties  

作　　者：Yihang Hao Haofan Wang Xianggen Liu Wenrui Gai Shilong Hu Wencheng Liu Zhuang Miao Yu Gan Xianghua Yu Rongjia Shi Yongzhen Tan Ting Kang Ao Hai Yi Zhao Yihang Fu Yaling Tang Ling Ye Jin Liu Xinhua Liang Bowen Ke 

机构地区：[1]State Key Laboratory of Oral Diseases and National Clinical Research Center for Oral Diseases,West China Hospital of Stomatology,Sichuan University,Chengdu 610041,China [2]College of Computer Science,Sichuan University,Chengdu 610065,China [3]Department of Anesthesiology,Laboratory of Anesthesia and Critical Care Medicine,National-Local Joint Engineering Research Centre of Translational Medicine of Anesthesiology,Frontiers Science Center for Disease-Related Molecular Network,West China Hospital,Sichuan University,Chengdu 610041,China

出　　处：《Acta Pharmaceutica Sinica B》2024年第7期3086-3109,共24页药学学报（英文版）

基　　金：supported by the National Natural Science Foundation of China(82273784,China);the Research and Develop Program,West China Hospital of Stomatology Sichuan University(RD-03-202004,China);the 1.3.5 Project for Disciplines of Excellence,West China Hospital,Sichuan University(ZYYC 21002,ZYGD23025,China);the Clinical Research Innovation Project,West China Hospital,Sichuan University(2019 HXCX006,China);the Science and Technology Major Project of Tibetan Autonomous Region of China(XZ202201ZD0001G,China);the Sichuan Science and Technology Program(2023 ZYD0168,China).

摘　　要：Multifunctional therapeutics have emerged as a solution to the constraints imposed by drugs with singular or insufficient therapeutic effects.The primary challenge is to integrate diverse pharmacophores within a single-molecule framework.To address this,we introduced DeepSA,a novel edit-based generative framework that utilizes deep simulated annealing for the modification of articaine,a wellknown local anesthetic.DeepSA integrates deep neural networks into metaheuristics,effectively constraining molecular space during compound generation.This framework employs a sophisticated objective function that accounts for scaffold preservation,anti-inflammatory properties,and covalent constraints.Through a sequence of local editing to navigate the molecular space,DeepSA successfully identified AT-17,a derivative exhibiting potent analgesic properties and significant anti-inflammatory activity in various animal models.Mechanistic insights into AT-17 revealed its dual mode of action:selective inhibition of NaV1.7 and 1.8 channels,contributing to its prolonged local anesthetic effects,and suppression of inflammatory mediators via modulation of the NLRP3 inflammasome pathway.These findings not only highlight the efficacy of AT-17 as a multifunctional drug candidate but also highlight the potential of DeepSA in facilitating AI-enhanced drug discovery,particularly within stringent chemical constraints.

关 键 词：Multifunctional drugs Deep simulated annealing Molecule generation Articaine derivatives AI-enhanced drug discovery 

分 类 号：R614[医药卫生—麻醉学] R78[医药卫生—外科学]