ADMET Predictor在预测资源或模型开发的应用文章汇总（2016-2020）
导 读
凡默谷技术部精取了2016-2020年10月, ADMET Predictor在预测资源或模型开发的应用文章32篇。
有助于您了解QSAR, QSPR模型是如何搭建的，同时也可以了解到常用的ADMET预测工具或模型搭建工具有哪些软件。
其中编号1-8的文章是2019年8月-2020年10月新增的文章。
希望对您的业务或专业学习有所帮助。内容如下：
1. 临床前研究阶段药物发现和开发的计算方法
Computational Approaches in Preclinical Studies on Drug Discovery and Development
Wu F, Zhou Y, Li L, Shen X, Chen G, Wang X, Liang X, Huang Z. Front. Chem., 11 September 2020. IF=3.693
ADMET Predictor 的作用：预测化合物的ADMET性质
2. 潜在新型抗疟疾2-氨基丙基氨基喹诺酮类药物的设计、性质预测和测试
Design and tests of prospective property predictions for novel antimalarial 2-aminopropylaminoquinolones
Clark RD, Morris D, Chinigo G, Lawless M, Prudhomme J, Le Roch KG, Lafuente MJ, Ferrer S, Gamo, FJ, Gadwood R, Woltosz WS. Journal of Computer-Aided Molecular Design. volume 34, pages1117–1132(2020). IF=2.546
ADMET Predictor 的作用：搭建活性QSAR模型，预测化合物的ADMET性质，制定ADMET风险系数
3. 通过蛋白质结构预测和配体分子对接的模拟发现潜在药物的指南
User guide for the discovery of potential drugs via protein structure prediction and ligand docking simulation
Shaker B, Yu MS, Lee J, Lee Y, Jung C, Na D. Journal of Microbiology. 2020 Mar;58(3):235-244. IF=2.845
ADMET Predictor 的作用：预测化合物ADMET的工具
4. 抗结核化合物的药物发现：计算机模拟策略
In Silico Strategies in Tuberculosis Drug Discovery
Macalino SJY, Billones JB, Organo VG, Carrillo MCO. Molecules. 2020, 25(3), 665.IF=3.267
ADMET Predictor 的作用：预测化合物药代动力学PK性质的工具
5. 使用机器学习技术预测人血浆蛋白结合率的新策略
A novel strategy for prediction of human plasma protein binding using machine learning techniques
Yuana Y, Chang S, Zhang Z, Li Z, Li S, Xie P, Yau WP, Ling H, Cai W, Zhang Y, Xiang X. Chemometrics and Intelligent Laboratory Systems. Volume 199, 15 April 2020. IF=2.895
ADMET Predictor 的作用：开发预测血浆蛋白结合率的模型
6. 定量结构-药代动力学关系分析在血液透析清除率预测模型中的应用
Application of a hemodialysis clearance prediction model using quantitative structure-pharmacokinetic relationship analysis
Suzuki D, Aoyama T, Nakajima J, Miyamoto A, Ako Y, Kikkawa A, Hiraki K, Matsumoto Y. Ther Apher Dial. 2020;24:655–667. IF=1.041
ADMET Predictor 的作用：开发预测血液透析后药物清除率的模型
7. 预测化合物在大鼠的口服生物利用度：使用计算机模拟和化学结构参数将体外相关性的洞见转移到（深度）机器学习模型上
Prediction of Oral Bioavailability in Rats: Transferring Insights from in Vitro Correlations to (Deep) Machine Learning Models Using in Silico Model Outputs and Chemical Structure Parameters
Schneckener S, Grimbs S, Hey J, Menz S, Osmers M, Schaper S, Hillisch A, Göller AH. J. Chem. Inf. Model. 2019, 59, 11, 4893–4905. IF=4.549
ADMET Predictor 的作用：预测化合物的理化性质，血浆蛋白结合率，药物游离分数Fu等
8. 通过带有根拓扑扭转指纹的机器学习方法预测pKa：应用到脂肪胺中
Prediction of pKa Using Machine Learning Methods with Rooted Topological Torsion Fingerprints: Application to Aliphatic Amines
Lu Y, Anand S, Shirley W, Gedeck P, Kelley BP, Skolnik S, Rodde S, Nguyen MA, Lindvall MK, Jia W. J. Chem. Inf. Model. 2019, 59, 11, 4706–4719. IF=4.549
ADMET Predictor 的作用：预测化合物的pKa
9. 通过建立定量构效关系QASR模型,预测具有潜在肾毒性的中药成分
Development of quantitative structure-activity relationship models to predict potential nephrotoxic ingredients in traditional Chinese medicines.
YuqingSun, ShaozeShi, YaqiuLi, QiWang. Food and Chemical Toxicology. Volume 128, June 2019, Pages 163-170 IF=4.679
ADMET Predictor 的作用：搭建肾毒性的QASR预测模型
10. 用于辅助化合物生理动力学模型的开发和评价的计算机预测资源
In silico resources to assist in the development and evaluation of physiologically-based kinetic models.
Madden JC, Pawar G, Cronin MTD, Webb S, Tan YM, Paini A. Computational Toxicology. Mar 5, 2019. CiteScore=2.5
ADMET Predictor 的作用：文章列举了用于模型开发的计算机预测资源
11. 重新审视原料药API排放对鱼类的毒性：通过整合乙酰胆碱酯酶基于配体/靶标结构评估，更深地理解机理
Revisiting fish toxicity of active pharmaceutical ingredients: Mechanistic insights from integrated ligand-/structure-based assessments on acetylcholinesterase.
Minovski N, Saçan MT, Eminoğlu EM, Erdem SS, Novič M. Ecotoxicol Environ Saf.Feb 6, 2019. IF=4.872
ADMET Predictor 的作用: 采用自建模型模块获得开发毒性预测模型的化学描述符
12. 开发，验证和集成计算机预测模型，用于具有潜在雄激素活性化学品的识别
Development, validation and integration of in silico models to identify androgen active chemicals.
Manganelli S, Roncaglioni A, Mansouri K, Judson RS, Benfenati E, Manganaro A, Ruiz P. Chemosphere. Feb 6, 2019. IF=5.778
ADMET Predictor 的作用: 采用自建模型模块开发人工神经网络ANN等预测模型
13. 基于机器学习的模型，用于预测化疗引起的周围神经病变
Machine Learning Models for the Prediction of Chemotherapy-Induced Peripheral Neuropathy.
Bloomingdale P, Mager DE. Pharm Res. Feb 1, 2019. IF=3.242
ADMET Predictor 的作用: 采用自建模型模块获得模型开发的化学描述符
14. EDEn-环境电子设计数据库：带有小分子调节剂的离子通道组织表达数据库
EDEn–Electroceutical Design Environment: Ion Channel Tissue Expression Database with Small Molecule Modulators.
Churchill CDM, Winter P, Tuszynski JA, Levin M. iScience. Jan 25, 2019
ADMET Predictor 的作用: 列举数据库开发时需要涉及到的理化等参数
15. 代谢组学研究的工具和资源通讯：2017-2018年更新
Tools and resources for metabolomics research community: A 2017–2018 update.
Misra BB, Mohapatra S. Electrophoresis. 6 November 2018. IF=3.081
ADMET Predictor 的作用: 列举了预测化合物代谢的资源
16. 采用计算机对15,145种有机化学品的体内处置和化学毒性进行排序和推导
In silico scaling and prioritization of chemical disposition and chemical toxicity of 15,145 organic chemicals.
Matthews EJ. Computational Toxicology. 2018 August 2. 2468-1113.CiteScore=2.5
ADMET Predictor 的作用：搭建化学品处置（暴露量）的预测模型
17. 采用有机化学品的理化性质进行人体内暴露量估算与排序的一种计算机方法
Introducing a computational method to estimate and prioritize systemic body exposure of organic chemicals in humans using their physicochemical properties.
Matthews EJ. Computational Toxicology. Aug 10, 2018. CiteScore=2.5
ADMET Predictor 的作用：构建化学品的体内处置的定量结构性质关系QSPR模型
18. 将吸收和代谢纳入草药膳食补充剂的肝毒性预测中：分层的计算机预测QSAR方法Incorporation of
absorption and metabolism into liver toxicity prediction for phytochemicals: A tiered in silico QSAR approach.
Liu Y. Food Chem Toxicol. 2018 Aug; 118:409-415. IF=4.679
ADMET Predictor 的作用：搭建草药膳食补充剂成分肝毒性的QSAR模型
19. 植物次级代谢产物的计算机预测特征
In Silico Characterization of Plant Secondary Metabolites.
Rani AS, Neelima G, Mukhopadhyay R, Jyothi KSN, Sulakshana G. BMC Genomics.Jul 24, 2018. IF=3.594
ADMET Predictor 的作用：列举了预测各种ADMET工具和资源
20. 通过定量构效关系QSAR方法预测污染物的毒性
Quantitative Structure–Activity Relationship Methods for the Prediction of the Toxicity of Pollutants.
Satpathy R. Environ Chem Lett. Jul 20, 2018. IF=5.922
ADMET Predictor 的作用：预测预测毒性的各种软件资源
21. 溶解度方法的简要概述：平衡溶解度测量和预测模型的最新趋势
Brief overview of solubility methods: Recent trends in equilibrium solubility measurement and predictive models.
Konczol A, Dargo G. Drug Discov Today Technol. 2018 Jul;27:3-10.CiteScore=6.9
ADMET Predictor 的作用：列举了预测化合物在不同介质中溶解度的软件资源
22. 通过计算机预测方法揭示传统植物药的药理物质基础
In silico approach in reveal traditional medicine plants pharmacological material basis.
Yi F, Li L, Xu L, Meng H, Dong Y, Liu H, Xiao P. Chin Med. 2018 Jun 19;13:33.IF=2.96
ADMET Predictor 的作用：列举了ADMET预测软件的资源
23. 采用计算机预测农药在哺乳动物中的代谢和毒性
Predicting mammalian metabolism and toxicity of pesticides in silico.
Clark RD.Pest Manag Sci. May 15, 2018. IF=3.75
ADMET Predictor 的作用：搭建了农药的吸收、代谢、毒性模型
24. 测定pKa的自动化技术：低，中和高通量筛选方法
Automated techniques in pKa determination: Low, medium and high-throughput screening methods.
Dardonville C. Drug Discov Today. May 10, 2018. IF=7.321
ADMET Predictor 的作用：列举了预测pKa的软件资源
25. 在先导化合物优化阶段中的生理药代动力学PBPK模型I：评估GastroPlus在预测系列化合物生物利用度的准确性和适应性
Physiologically-Based Pharmacokinetic Modeling in Lead Optimization I: Evaluation and Adaptation of GastroPlus to Predict Bioavailability of Medchem Series.
Daga PR, Bolger MB, Haworth IS, Clark RD, Martin EJ. Pharmaceutics, 2018, 15 (3), pp 821–830. IF=4.421
ADMET Predictor 的作用：搭建了预测化合物清除率的QSAR模型
26. 在药物发现阶段，用于预测被CYP450代谢的计算方法和工具
Computational Methods and Tools to Predict Cytochrome P450 Metabolism for Drug Discovery.
Tyzack JD, Kirchmair J. Chem Biol Drug Des. 24 November 2018. IF=2.548
ADMET Predictor的作用: 综述-列举预测化合物被CYP450代谢的方法和软件
27. 采用液质联用技术鉴定大环内酯类抗生素的杂质以及构建QSRR模型预测杂质的保留时间
Identification of impurities in macrolides by liquid chromatography–mass spectrometric detection and prediction of retention times of impurities by constructing quantitative structure–retention relationship (QSRR).
Zhang X, Li J, Wang C, Song D, Hu CQ. J Pharm Biomed Anal. Oct 25, 2017.IF=3.209
ADMET Predictor 的作用：搭建杂质保留时间的QSRR模型
28. 采用计算机方法预测化合物在皮肤的代谢，并用于毒性评估
In silico prediction of skin metabolism and its implication in toxicity assessment.
Madden JC, Webb S, Enoch SJ, Colley HE, Murdoch C, Shipley R, Sharma P, Yang C, Cronin MTD. Computational Toxicology. Aug 1, 2017. CiteScore=2.5
ADMET Predictor 的作用：列举了预测化合物在皮肤的代谢的软件资源
29. 大环类化合物的结构和构象决定了它们的细胞渗透性
Structural and conformational determinants of macrocycle cell permeability.
Over B, Matsson P, Tyrchan C, Artursson P, Doak BC, Foley MA, Hilgendorf C, Johnston SE, Lee MD 4th, Lewis RJ, McCarren P, Muncipinto G, Norinder U, Perry MW, Duvall JR, Kihlberg J. Nat Chem Biol. Dec 1, 2016. IF=12.587
ADMET Predictor 的作用：通过自建模型模块的PLS方法搭建预测大环类化合物的细胞渗透性模型，转运体介导的外排模型
30. 基于分类决策树，预测化合物对皮肤致敏性的危害的共识
Consensus of classification trees for skin sensitisation hazard prediction.
Asturiol D, Casati S, Worth A. Toxicol In Vitro. Oct 1, 2016. IF=2.959
ADMET Predictor 的作用：通过自建模型模块获得搭建理化性质预测模型，毒性预测模型
31. 从中草药和对应的分子靶标中发现新的有效化合物的先进研究技术
Advanced research technology for discovery of new effective compounds from Chinese herbal medicine and their molecular targets.
Wong VK, Law BY, Yao X, Chen X, Xu SW, Liu L, Leung EL. Pharm Res. Sep 1, 2016.IF=3.242
ADMET Predictor的作用：列举了ADMET性质预测的软件资源
32. QSAR模型分析中的分子描述符及其筛选的方法：以药物设计为范例
Descriptors and their selection methods in QSAR analysis: paradigm for drug design.
Danishuddin, Khan AU. Drug Discov Today. Jun 18, 2016. IF=7.321
ADMET Predictor的作用：列举了预测各种构建QSAR模型分子描述符的工具和资源