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Future drug discovery最新文献

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Prospects for drug discovery in osteoarthritis 骨关节炎药物发现前景
Pub Date : 2019-08-28 DOI: 10.4155/fdd-2019-0015
C. Malemud
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引用次数: 0
The advent of directed protein degraders in drug discovery 定向蛋白质降解剂在药物发现中的出现
Pub Date : 2019-08-20 DOI: 10.4155/FDD-2019-0019
M. Benchekroun
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引用次数: 3
RxNet Glossary of Drug Discovery RxNet药物发现术语表
Pub Date : 2019-08-01 DOI: 10.4155/fdd-2019-0101s
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引用次数: 1
Welcome to the first issue of Future Drug Discovery 欢迎来到《未来药物发现》的第一期
Pub Date : 2019-07-02 DOI: 10.4155/FDD-2019-0020
F. Lake
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引用次数: 0
Pharma expats: a Q&A with two who made the move to a contract research organization 制药公司的外派人员:与两位转到合同研究机构的人的问答
Pub Date : 2019-06-18 DOI: 10.4155/FDD-2019-0014
I. Waddell, Chris Hill
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引用次数: 0
In silico and in vitro evaluation of brain penetration properties of selected nootropic agents 所选促神经药物脑渗透特性的计算机和体外评估
Pub Date : 2019-06-10 DOI: 10.4155/FDD-2019-0009
Ahmed Alsarrani, P. Kaplita
Aim: Predictive ( in silico) data suggested that nootropic supplements may penetrate the blood–brain barrier (BBB). We evaluated, in vitro, the ability of nootropics to enter the brain based on the high throughput screening (HTS) measurement of interactions with the P-gp efflux transporter and physicochemical properties and correlated these data with the in silico predictions. Methods & results: The software predicted that piracetam, docosahexaenoic acid (DHA), amantadine and thioflavin-T can best penetrate the BBB. The lipophilicity of these compounds may be predicted by measuring the critical micelle concentration (CMC). DHA and verapamil demonstrated high lipophilicity. DHA, verapamil and phosphatidylserine (PS) may be good substrates of the P-gp transporter. Conclusion: Permeability of nootropics may be successfully predicted by high throughput screening-lead optimization assay technologies.
目的:预测(计算机)数据表明益智补充剂可能穿透血脑屏障(BBB)。我们在体外评估了益智药进入大脑的能力,基于高通量筛选(HTS)测量与P-gp外排转运体的相互作用和物理化学性质,并将这些数据与计算机预测相关联。方法与结果:软件预测吡拉西坦、二十二碳六烯酸(DHA)、金刚烷胺和硫黄素- t最能穿透血脑屏障。这些化合物的亲脂性可以通过测定临界胶束浓度(CMC)来预测。DHA和维拉帕米表现出高亲脂性。DHA、维拉帕米和磷脂酰丝氨酸(PS)可能是P-gp转运体的良好底物。结论:高通量筛选-导联优化检测技术可成功预测益智药的通透性。
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引用次数: 4
Benefits of life in a science incubator 在科学孵化器中生活的好处
Pub Date : 2019-06-10 DOI: 10.4155/FDD-2019-0010
Michael S. Holzwarth
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引用次数: 2
Independent consultancy in drug discovery and development: a personal perspective 药物发现和开发的独立咨询:个人视角
Pub Date : 2019-05-28 DOI: 10.4155/FDD-2019-0007
P. Lukey
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引用次数: 1
Application of biomimetic HPLC to estimate in vivo behavior of early drug discovery compounds 应用仿生高效液相色谱法估计早期药物发现化合物的体内行为
Pub Date : 2019-04-26 DOI: 10.4155/FDD-2019-0004
K. Valko
Characterizing the properties of large numbers of compounds and estimating their potential absorption, distribution, metabolism and elimination properties are important early stages in the process of drug discovery and help to reduce later stage attrition. The chromatographic separation principles using stationary phases that contain proteins and phospholipids are more suitable for compound characterization and estimation of the pharmacokinetic properties than the traditional octanol/water partition coefficient. This technology, when standardized, enables the prediction of in vivo behavior and the selection of compounds with the best potential, thus reducing the number of animal experiments. Chromatography may be involved more widely in the future to measure kinetic aspects of compounds’ binding to proteins and receptors which would enable designing compounds that require a lower frequency of doses and have more predictable pharmacokinetic profiles.
表征大量化合物的性质并估计其潜在的吸收、分布、代谢和消除性质是药物发现过程中的重要早期阶段,有助于减少后期损耗。与传统的辛醇/水分配系数相比,使用含有蛋白质和磷脂的固定相的色谱分离原理更适合于化合物表征和药代动力学性质的估计。这项技术一旦标准化,就可以预测体内行为,并选择具有最佳潜力的化合物,从而减少动物实验的数量。色谱法在未来可能会更广泛地用于测量化合物与蛋白质和受体结合的动力学方面,这将使设计需要较低剂量频率并具有更可预测的药代动力学特征的化合物成为可能。
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引用次数: 17
Polyphenol and self-assembly: metal polyphenol nanonetwork for drug delivery and pharmaceutical applications 多酚和自组装:用于药物递送和药物应用的金属多酚纳米网络
Pub Date : 2019-04-12 DOI: 10.4155/FDD-2019-0001
Xingcai Zhang, Gaurav Parekh, Baolin Guo, Xing Huang, Yuqing Dong, W. Han, Xing Chen, G. Xiao
[Formula: see text]
[公式:见正文]
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引用次数: 32
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Future drug discovery
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