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Transfer learning enhanced graph neural network for aldehyde oxidase metabolism prediction and its experimental application

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Acta Pharmaceutica Sinica B 2024年第2期14卷 623-634页

作者： jiacheng Xiong Rongrong Cui Zhaojun Li wei Zhang Runze Zhang Zunyun Fu Xiaohong Liu Zhenghao Li Kaixian Chen Mingyue Zheng Drug Discovery and Design Center State Key Laboratory of Drug ResearchShanghai Institute of Materia MedicaChinese Academy of SciencesShanghai 201203China University of Chinese Academy of Sciences Beijing 100049China College of Computer and Information Engineering Dezhou UniversityDezhou 253023China AI Department Suzhou Alphama Biotechnology Co.Ltd.Suzhou 215000China Shanghai Institute for Advanced Immunochemical Studies and School of Life Science and TechnologyShanghaiTech UniversityShanghai 200031China State Key Laboratory of Pharmaceutical Biotechnology Nanjing UniversityNanjing 210023China

Aldehyde oxidase(AOX)is a molybdoenzyme that is primarily expressed in the liver and is involved in the metabolism of drugs and other xenobiotics.AOX-mediated metabolism can result in unexpected outcomes,such as the production of toxic metabolites and high metabolic clearance,which can lead to the clinical failure of novel therapeutic agents.Computational models can assist medicinal chemists in rapidly evaluating the AOX metabolic risk of compounds during the early phases of drug discovery and provide valuable clues for manipulating AOX-mediated metabolism liability.In this study,we developed a novel graph neural network called AOMP for predicting AOX-mediated metabolism.AOMP integrated the tasks of metabolic substrate/non-substrate classification and metabolic site prediction,while utilizing transfer learning from 13C nuclear magnetic resonance data to enhance its performance on both tasks.AOMP significantly outperformed the benchmark methods in both cross-validation and external testing.Using AOMP,we systematically assessed the AOX-mediated metabolism of common fragments in kinase inhibitors and successfully identified four new scaffolds with AOX metabolism liability,which were validated through in vitro experiments.Furthermore,for the convenience of the community,we established the first online service for AOX metabolism prediction based on AOMP,which is freely available at https://***.

关键词： Drugmetabolism Aldehyde oxidase Transferlearning Graph neural network Kinase inhibitor

αExtractor: a system for automatic extraction of chemical information from biomedical literature

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Science China(Life Sciences) 2024年第3期67卷 618-621页

作者： jiacheng Xiong Xiaohong Liu Zhaojun Li Hongzhong Xiao Guangchao Wang Zhenjiang Niu Chaoyuan Fei Feisheng Zhong Gang Wang wei Zhang Zunyun Fu Zhiguo Liu Kaixian Chen Hualiang Jiang Mingyue Zheng Drug Discovery and Design Center State Key Laboratory of Drug ResearchShanghai Institute of Materia MedicaChinese Academy of SciencesShanghai 201203China University of Chinese Academy of Sciences Beijing 100049China AI Department Suzhou Alphama Biotechnology Co.Ltd.Suzhou 215125China College of Computer and Information Engineering Dezhou UniversityDezhou 253023China

Dear Editor,Great progress has been made using artificial intelligence(AI) techniques in learning knowledge from biomedical databases in recent years, revolutionizing the study of many fields, such as protein structure prediction and protein design(Madani et al., 2023). However, there is massive biomedical knowledge not curated in the form of structured data but hidden in primary scientific literature.

关键词： has such knowledge

面向智能无人通信系统的因果性对抗攻击生成算法

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通信学报 2024年第1期45卷 54-62页

作者：禹树文许威姚嘉铖东南大学移动通信全国重点实验室江苏南京210096 网络通信与安全紫金山实验室江苏南京211111

考虑到基于梯度的对抗攻击生成算法在实际通信系统部署中面临着因果性问题,提出了一种因果性对抗攻击生成算法。利用长短期记忆网络的序列输入输出特征与时序记忆能力,在满足实际应用中存在的因果性约束前提下,有效提取通信信号的时序... 详细信息

考虑到基于梯度的对抗攻击生成算法在实际通信系统部署中面临着因果性问题,提出了一种因果性对抗攻击生成算法。利用长短期记忆网络的序列输入输出特征与时序记忆能力,在满足实际应用中存在的因果性约束前提下,有效提取通信信号的时序相关性,增强针对无人通信系统的对抗攻击性能。仿真结果表明,所提算法在同等条件下的攻击性能优于泛用对抗扰动等现有的因果性对抗攻击生成算法。

关键词：智能通信系统对抗攻击深度学习因果系统长短期记忆网络

Targeting a cryptic allosteric site of SIRT6 with small-molecule inhibitors that inhibit the migration of pancreatic cancer cells

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Acta Pharmaceutica Sinica B 2022年第2期12卷 876-889页

作者： Qiufen Zhang Yingyi Chen Duan Ni Zhimin Huang jiacheng wei Li Feng Jun-Cheng Su Yingqing wei Shaobo Ning Xiuyan Yang Mingzhu Zhao Yuran Qiu Kun Song Zhengtian Yu Jianrong Xu Xinyi Li Houwen Lin Shaoyong Lu Jian Zhang State Key Laboratory of Oncogenes and Related Genes Department of PharmacyRenji HospitalShanghai Jiao Tong University School of MedicineShanghai 200127China Medicinal Chemistry and Bioinformatics Center Shanghai Jiao Tong University School of MedicineShanghai 200025China Nutshell Therapeutics Shanghai 201203China Academy of Integrative Medicine Shanghai University of Traditional Chinese MedicineShanghai 201203China School of Pharmaceutical Sciences Zhengzhou UniversityZhengzhou 450001China

SIRT6 belongs to the conserved NAD^(+)-dependent deacetylase superfamily and mediates multiple biological and pathological processes.Targeting SIRT6 by allosteric modulators represents a novel direction for therapeutics,which can overcome the selectivity problem caused by the structural similarity of orthosteric sites among deacetylases.Here,developing a reversed allosteric strategy Allo Reverse,we identified a cryptic allosteric site,Pocket Z,which was only induced by the bi-directional allosteric signal triggered upon orthosteric binding of NAD^(+).Based on Pocket Z,we discovered an SIRT6 allosteric inhibitor named JYQ-42.JYQ-42 selectively targets SIRT6 among other histone deacetylases and effectively inhibits SIRT6 deacetylation,with an IC50 of 2.33μmol/L.JYQ-42 significantly suppresses SIRT6-mediated cancer cell migration and pro-inflammatory cytokine production.JYQ-42,to our knowledge,is the most potent and selective allosteric SIRT6 inhibitor.This study provides a novel strategy for allosteric drug design and will help in the challenging development of therapeutic agents that can selectively bind SIRT6.

关键词： SIRT6 Molecular dynamics simulations Reversed allostery Allosteric inhibitor Pancreatic cancer Cell migration Cytokine production

基于主动学习方法的随机波场中双浮体极端响应超越概率

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水动力学研究与进展（A辑） 2024年第1期39卷 17-21页

作者：刘义沈佳诚柏小东张伟中国船舶及海洋工程设计研究院上海200011 喷水推进技术重点实验室上海200011 合肥工业大学土木与水利工程学院合肥230006

海上作业过程中,经常存在两个浮体相邻的情况。真实海洋环境中,伴随着随机波浪的影响,相邻浮体可能会产生耦合运动。尤其是在恶劣海况下,浮体的极端运动响应可能导致其倾覆,对海上作业产生严重危害。基于波群参数化和次序采样,结合计算... 详细信息

海上作业过程中,经常存在两个浮体相邻的情况。真实海洋环境中,伴随着随机波浪的影响,相邻浮体可能会产生耦合运动。尤其是在恶劣海况下,浮体的极端运动响应可能导致其倾覆,对海上作业产生严重危害。基于波群参数化和次序采样,结合计算流体力学(computational fluid dynamics,CFD)模拟,该文研究和分析了在不规则波浪中相邻浮体的横摇运动特性,并基于主动学习方法,采用少量样本有效地预测了浮体随机波浪的极端响应超越概率。此外,还研究了相邻浮体的距离比G/D对运动响应的影响,通过不同G/D下相邻浮体的时间超越概率进行预测和比较,找出了最优的相邻浮体距离,为实际工程应用提供了理论依据。

关键词：相邻浮体极端运动响应主动学习 CFD 次序采样

Mechanism of allosteric activation of SIRT6 revealed by the action of rationally designed activators

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Acta Pharmaceutica Sinica B 2021年第5期11卷 1355-1361页

作者： Shaoyong Lu Yingyi Chen jiacheng wei Mingzhu Zhao Duan Ni Xinheng He Jian Zhang Department of Pathophysiology Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of EducationShanghai Jiao Tong UniversitySchool of MedicineShanghai 200025China State Key Laboratory of Oncogenes and Related Genes Renji HospitalShanghai Jiao Tong UniversitySchool of MedicineShanghai 200127China The Charles Perkins Centre University of SydneySydney NSW 2006Australia

The recent discovery of activator compounds binding to an allosteric site on the NAD+-dependent protein lysine deacetylase,sirtuin 6(SIRT6)has attracted interest and presents a pharmaceutical target for aging-related and cancer diseases.However,the mechanism underlying allosteric activation of SIRT6 by the activator MDL-801 remains largely elusive because no major conformational changes are observed upon activator binding.By combining molecular dynamics simulations with biochemical and kinetic analyses of wild-type SIRT6 and its variant M136 A,we show that conformational rotation of 2-methyl-4-fluoro-5-bromo substituent on the right phenyl ring(R-ring)of MDL-801,which uncovers previously unseen hydrophobic interactions,contributes to increased activating deacetylation activity of SIRT6.This hypothesis is further supported by the two newly synthesized MDL-801 derivatives through the removal of the 5-Br atom on the R-ring(MDL-801-D1)or the restraint of the rotation of the R-ring(MDL-801-D2).We further propose that the 5-Br atom serves as an allosteric driver that controls the ligand allosteric efficacy.Our study highlights the effect of allosteric enzyme catalytic activity by activator binding and provides a rational approach for enhancing deacetylation activity.

关键词： Allosteric driver Allosteric sites Allosteric mechanisms Drug design Enzyme catalysis Protein dynamics

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基于生成神经网络的自适应热控薄膜设计

光学学报 2024年第7期44卷 261-270页

作者：陈嘉诚马蔚朱虹雨周玉晟詹耀辉李孝峰苏州大学光电科学与工程学院江苏苏州215006 江苏省先进光学制造技术重点实验室暨教育部现代光学技术重点实验室江苏苏州215006 浙江大学信息与电子工程学院浙江杭州310027

自适应温度调控器件以其智能开关特性而逐渐成为研究焦点,但是一方面其特殊的光谱要求使得器件设计过程复杂且周期冗长,另一方面器件热控性能亟待提高以满足更加严苛的应用场景。针对以上问题,提出一种深度生成神经网络模型来执行上述... 详细信息

自适应温度调控器件以其智能开关特性而逐渐成为研究焦点,但是一方面其特殊的光谱要求使得器件设计过程复杂且周期冗长,另一方面器件热控性能亟待提高以满足更加严苛的应用场景。针对以上问题,提出一种深度生成神经网络模型来执行上述复杂的优化任务,该网络模型的更新不依赖于数据集,而是将生成神经网络与传输矩阵方法(TMM)相结合,通过TMM返回的梯度信息指导产生符合预期的多层膜结构,并自动优化膜层厚度和材料种类。作为网络优化能力的验证和演示,本课题组使用该方法设计了一种基于二氧化钒的自适应热控器件,实现了高温太阳吸收比低于0.2、高温发射率高于0.9、发射率差值大于0.8的优异性能。与传统的优化算法相比,生成神经网络以高自由度和更快的速度寻找最优解,与普通神经网络相比,全局优化网络考虑整体的优化目标,通过全局搜索寻找全局最优解,设计结果也证明了该方法在复杂设计任务中的实用性。

关键词：薄膜多层膜神经网络自适应温度调控二氧化钒

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碳碳键链接的二维共价有机框架研究进展

化学学报 2024年第1期82卷 75-102页

作者：魏颖王家成李玥汪涛马述威解令海分子系统与有机器件研究中心(CMSOD)、信息材料与纳米技术研究院、有机电子与信息显示国家重点实验室(IAM)、南京邮电大学南京210023

二维共价有机框架(Two-dimensional Covalent-Organic Frameworks,2D COFs)是指一类由π-共轭构筑单元通过共价键连接形成的具有二维拓扑结构的晶态多孔材料.由于其独特的周期性多孔结构、高比表面积、优异的稳定性等特点在离子传输、... 详细信息

二维共价有机框架(Two-dimensional Covalent-Organic Frameworks,2D COFs)是指一类由π-共轭构筑单元通过共价键连接形成的具有二维拓扑结构的晶态多孔材料.由于其独特的周期性多孔结构、高比表面积、优异的稳定性等特点在离子传输、光电材料、催化等领域展现出了巨大的应用潜力.其中,碳碳键链接的共价有机框架因兼具优异的稳定性和良好的结晶性,被认为是最具有前景的二维聚合物材料之一.近年来,基于不同的设计原则和合成策略涌现出了许多具有不同结构和优异性能的碳碳键链接共价有机框架.在这篇综述中,按照构筑单元的拓扑结构对碳碳键链接共价有机框架进行分类,并归纳总结了迄今为止C=C和C—C键链接的二维共价有机框架在合成方法、结构创新、性能提升以及实际应用领域的研究进展.该综述旨在为相关领域的研究人员更好地设计和合成具有多种功能的多孔结晶材料提供参考,从而促进碳碳键链接共价有机框架材料在光电领域的进一步发展和应用.

关键词：二维聚合物二维共价聚合物共价有机框架碳碳键链接多孔结晶材料

基于改进自适应多种群遗传算法的结构-控制系统一体化优化

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中南大学学报（自然科学版） 2024年第2期55卷 799-809页

作者：梅真龚嘉诚高毅超魏琳李海锋华侨大学土木工程学院福建厦门361021 中建四局建设发展有限公司福建厦门361006

提出一种改进的自适应多种群遗传算法,以更好地解决建筑结构-主动控制系统一体化优化问题,即同时对被控结构参数、控制算法参数、主动作动器布置位置进行优化。该遗传算法对编码方法、初始种群生成、选择策略、交叉概率和变异概率的自... 详细信息

提出一种改进的自适应多种群遗传算法,以更好地解决建筑结构-主动控制系统一体化优化问题,即同时对被控结构参数、控制算法参数、主动作动器布置位置进行优化。该遗传算法对编码方法、初始种群生成、选择策略、交叉概率和变异概率的自适应调整、多种群协同进化中移民策略等进行改进。研究结果表明:改进的自适应多种群遗传算法和改进的基本遗传算法优化结果总体一致,表明前者分析结果是正确的,并且具有较高的精度;改进的自适应多种群遗传算法和改进的基本遗传算法首次得到优化分析最优解的平均进化代数分别为320与730,表明前者比后者收敛速度更快;改进的自适应多种群遗传算法每次能达到或接近最优解,可有效克服基本遗传算法优化结果随机性较强的缺点;经改进的自适应多种群遗传算法优化的主动控制系统取得明显减振效果,E1 Centro波输入时,主动控制结构层间位移角峰值和绝对加速度峰值较无控时分别平均减小54.5%与46.7%。算例结果表明了改进的自适应多种群遗传算法的有效性,实现了对建筑结构-主动控制系统的一体化优化。

关键词：主动控制结构-控制系统一体化优化自适应遗传算法多种群