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
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Deep simulated annealing for the discovery of novel dental anesthetics with local anesthesia and anti-inflammatory properties
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 well-known 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.
Acta Pharmaceutica Sinica. BPharmacology, Toxicology and Pharmaceutics-General Pharmacology, Toxicology and Pharmaceutics
CiteScore
22.40
自引率
5.50%
发文量
1051
审稿时长
19 weeks
期刊介绍:
The Journal of the Institute of Materia Medica, Chinese Academy of Medical Sciences, and the Chinese Pharmaceutical Association oversees the peer review process for Acta Pharmaceutica Sinica. B (APSB).
Published monthly in English, APSB is dedicated to disseminating significant original research articles, rapid communications, and high-quality reviews that highlight recent advances across various pharmaceutical sciences domains. These encompass pharmacology, pharmaceutics, medicinal chemistry, natural products, pharmacognosy, pharmaceutical analysis, and pharmacokinetics.
A part of the Acta Pharmaceutica Sinica series, established in 1953 and indexed in prominent databases like Chemical Abstracts, Index Medicus, SciFinder Scholar, Biological Abstracts, International Pharmaceutical Abstracts, Cambridge Scientific Abstracts, and Current Bibliography on Science and Technology, APSB is sponsored by the Institute of Materia Medica, Chinese Academy of Medical Sciences, and the Chinese Pharmaceutical Association. Its production and hosting are facilitated by Elsevier B.V. This collaborative effort ensures APSB's commitment to delivering valuable contributions to the pharmaceutical sciences community.