计算机辅助药物设计在新药研发中的应用,计算机辅助药物设计在抗耐药菌药物研发中的应用进展...
[1]
Sliwoski G, Kothiwale S, Meiler J, et al. Computational methods in drug discovery[J]. Pharmacol Rev, 2013, 66(1):334-395.
Sliwoski G, Kothiwale S, Meiler J, et al. Computational methods in drug discovery[J]. Pharmacol Rev, 2013, 66(1):334-395.
[2]
高丽, 刘艾林, 杜冠华. 计算机辅助药物设计在新药研发中的应用进展[J]. 中国药学杂志, 2011, 46(9):641-645.
[3]
Singh G, Arora A, Singh A, et al. Molecular design, synthesis, computational screening, antimicrobial evaluation and molecular docking study of acetylinic isatin hybrids[J]. ChemistrySelect, 2018, 3(6):1942-1952.
Singh G, Arora A, Singh A, et al. Molecular design, synthesis, computational screening, antimicrobial evaluation and molecular docking study of acetylinic isatin hybrids[J]. ChemistrySelect, 2018, 3(6):1942-1952.
[4]
Karthick V, Nagasundaram N, Doss C G, et al. Virtual screening of the inhibitors targeting at the viral protein 40 of Ebola virus[J]. Infec Dis Povert, 2016, 5:12. Doi:10.1186/s40249-016-0105-1.
Karthick V, Nagasundaram N, Doss C G, et al. Virtual screening of the inhibitors targeting at the viral protein 40 of Ebola virus[J]. Infec Dis Povert, 2016, 5:12. Doi:10.1186/s40249-016-0105-1.
[5]
Yu W, Mackerell A D, Jr. Computer-aided drug design methods[J]. Methods Mol Biol, 2017, 1520:85-106.
Yu W, Mackerell A D, Jr. Computer-aided drug design methods[J]. Methods Mol Biol, 2017, 1520:85-106.
[6]
Evanthia L, George S, Demetrios K V, et al. Structure-based virtual screening for drug discovery:principles, applications and recent advances[J]. Curr Top Med Chem, 2014, 14(16):1923-1938.
Evanthia L, George S, Demetrios K V, et al. Structure-based virtual screening for drug discovery:principles, applications and recent advances[J]. Curr Top Med Chem, 2014, 14(16):1923-1938.
[7]
Boibessot T, Zschiedrich C P, Lebeau A, et al. The rational design, synthesis, and antimicrobial properties of thiophene derivatives that inhibit bacterial histidine kinases[J]. J Med Chem, 2016, 59(19):8830-8847.
Boibessot T, Zschiedrich C P, Lebeau A, et al. The rational design, synthesis, and antimicrobial properties of thiophene derivatives that inhibit bacterial histidine kinases[J]. J Med Chem, 2016, 59(19):8830-8847.
[8]
Jakopin Z, Ilas J, Barancokova M, et al. Discovery of substituted oxadiazoles as a novel scaffold for DNA gyrase inhibitors[J]. Eur J Med Chem, 2017, 130:171-184.
Jakopin Z, Ilas J, Barancokova M, et al. Discovery of substituted oxadiazoles as a novel scaffold for DNA gyrase inhibitors[J]. Eur J Med Chem, 2017, 130:171-184.
[9]
Nandi S. Recent advances in ligand and structure based screening of potent quorum sensing inhibitors against antibiotic resistance induced bacterial virulence[J]. Recent Patents Biotech, 2016, 10(2):195-216.
Nandi S. Recent advances in ligand and structure based screening of potent quorum sensing inhibitors against antibiotic resistance induced bacterial virulence[J]. Recent Patents Biotech, 2016, 10(2):195-216.
[10]
Sledz P, Caflisch A. Protein structure-based drug design:from docking to molecular dynamics[J]. Curr Opin Struct Biol, 2017, 48:93-102.
Sledz P, Caflisch A. Protein structure-based drug design:from docking to molecular dynamics[J]. Curr Opin Struct Biol, 2017, 48:93-102.
[11]
Zhou Z T, Ma S T. Recent advances in the discovery of PqsD inhibitors as antimicrobial agents[J]. ChemMedChem, 2017, 12(6):420-425.
Zhou Z T, Ma S T. Recent advances in the discovery of PqsD inhibitors as antimicrobial agents[J]. ChemMedChem, 2017, 12(6):420-425.
[12]
Li X L, Cai Y, Yang F, et al. Synthesis and molecular docking studies of chrysin derivatives as antibacterial agents[J]. Med Chem Res, 2017, 26(10):2225-2234.
Li X L, Cai Y, Yang F, et al. Synthesis and molecular docking studies of chrysin derivatives as antibacterial agents[J]. Med Chem Res, 2017, 26(10):2225-2234.
[13]
Wang T, Wu M B, Zhang R H, et al. Advances in computational structure-based drug design and application in drug discovery[J]. Curr Top Med Chem, 2016, 16(9):901-916.
Wang T, Wu M B, Zhang R H, et al. Advances in computational structure-based drug design and application in drug discovery[J]. Curr Top Med Chem, 2016, 16(9):901-916.
[14]
Fitzpatrick L R, Deml L, Hofmann C, et al. 4SC-101, a novel immunosuppressive drug, inhibits IL-17 and attenuates colitis in two murine models of inflammatory bowel disease[J]. Inflamm Bowel Dis, 2010, 16(10):1763-1777.
Fitzpatrick L R, Deml L, Hofmann C, et al. 4SC-101, a novel immunosuppressive drug, inhibits IL-17 and attenuates colitis in two murine models of inflammatory bowel disease[J]. Inflamm Bowel Dis, 2010, 16(10):1763-1777.
[15]
Coumar M S, Leou J S, Shukla P, et al. Structure-based drug design of novel aurora kinase A inhibitors:structural basis for potency and specificity[J]. J Med Chem, 2009, 52(4):1050-1062.
Coumar M S, Leou J S, Shukla P, et al. Structure-based drug design of novel aurora kinase A inhibitors:structural basis for potency and specificity[J]. J Med Chem, 2009, 52(4):1050-1062.
[16]
Ballester P J, Mangold M, Howard N I, et al. Hierarchical virtual screening for the discovery of new molecular scaffolds in antibacterial hit identification[J]. J R Soc Interface, 2012, 9(77):3196-3207.
Ballester P J, Mangold M, Howard N I, et al. Hierarchical virtual screening for the discovery of new molecular scaffolds in antibacterial hit identification[J]. J R Soc Interface, 2012, 9(77):3196-3207.
[17]
Distinto S, Esposito F, Kirchmair J, et al. Identification of HIV-1 reverse transcriptase dual inhibitors by a combined shape-, 2D-fingerprint-and pharmacophore-based virtual screening approach[J]. Eur J Med Chem, 2012, 50:216-229.
Distinto S, Esposito F, Kirchmair J, et al. Identification of HIV-1 reverse transcriptase dual inhibitors by a combined shape-, 2D-fingerprint-and pharmacophore-based virtual screening approach[J]. Eur J Med Chem, 2012, 50:216-229.
[18]
Gudzera O I, Golub A G, Bdzhola V G, et al. Discovery of potent antituberculosis agents targeting leucyl-tRNA synthetase[J]. Bioorg Med Chem, 2016, 24(5):1023-1031.
Gudzera O I, Golub A G, Bdzhola V G, et al. Discovery of potent antituberculosis agents targeting leucyl-tRNA synthetase[J]. Bioorg Med Chem, 2016, 24(5):1023-1031.
[19]
Zhang F, Du J, Wang Q, et al. Discovery of N-(4-sulfamoylphenyl) thioureas as trypanosoma brucei leucyl-tRNA synthetase inhibitors[J]. Org Biomol Chem, 2013, 11(32):5310-5324.
Zhang F, Du J, Wang Q, et al. Discovery of N-(4-sulfamoylphenyl) thioureas as trypanosoma brucei leucyl-tRNA synthetase inhibitors[J]. Org Biomol Chem, 2013, 11(32):5310-5324.
[20]
Li G B, Abboud M I, Brem J, et al. NMR-filtered virtual screening leads to non-metal chelating metallo-beta-lactamase inhibitors[J]. Chem Sci, 2017, 8(2):928-937.
Li G B, Abboud M I, Brem J, et al. NMR-filtered virtual screening leads to non-metal chelating metallo-beta-lactamase inhibitors[J]. Chem Sci, 2017, 8(2):928-937.
[21]
Macalino S J Y, Gosu V, Hong S, et al. Role of computer-aided drug design in modern drug discovery[J]. Arch Pharm Res, 2015, 38(9):1686-1701.
Macalino S J Y, Gosu V, Hong S, et al. Role of computer-aided drug design in modern drug discovery[J]. Arch Pharm Res, 2015, 38(9):1686-1701.
[22]
Melo-Filho C C, Braga R C, Andrade C H. 3D-QSAR approaches in drug design:perspectives to generate reliable CoMFA models[J]. Curr Comput Aided Drug Des, 2014, 10(2):148-159.
Melo-Filho C C, Braga R C, Andrade C H. 3D-QSAR approaches in drug design:perspectives to generate reliable CoMFA models[J]. Curr Comput Aided Drug Des, 2014, 10(2):148-159.
[23]
Shi J C, Zhao D, Luo M, et al. A mechanism-based 3D-QSAR and DFT approach for the prediction of H5N1 entry inhibitory potency of 3-O-beta-chacotriosyl ursolic acid derivatives[J]. Chin J Struct Chem, 2017, 36(12):1987-1999.
Shi J C, Zhao D, Luo M, et al. A mechanism-based 3D-QSAR and DFT approach for the prediction of H5N1 entry inhibitory potency of 3-O-beta-chacotriosyl ursolic acid derivatives[J]. Chin J Struct Chem, 2017, 36(12):1987-1999.
[24]
Lee J Y, Jeong M C, Jeon D, et al. Structure-activity relationshipbased screening of antibiotics against Gram-negative Acinetobacter baumannii[J]. Bioorg Med Chem, 2017, 25(1):372-380.
Lee J Y, Jeong M C, Jeon D, et al. Structure-activity relationshipbased screening of antibiotics against Gram-negative Acinetobacter baumannii[J]. Bioorg Med Chem, 2017, 25(1):372-380.
[25]
Ciura K, Nowakowska J, Rudnicka-Litka K, et al. The study of salting-out thin-layer chromatography and their application on QSRR/QSAR of some macrolide antibiotics[J]. Monatshefte Fur Chemie, 2016, 147(2):301-310.
Ciura K, Nowakowska J, Rudnicka-Litka K, et al. The study of salting-out thin-layer chromatography and their application on QSRR/QSAR of some macrolide antibiotics[J]. Monatshefte Fur Chemie, 2016, 147(2):301-310.
[26]
Vuorinen A, Schuster D. Methods for generating and applying pharmacophore models as virtual screening filters and for bioactivity profiling[J]. Methods, 2015, 71:113-134.
Vuorinen A, Schuster D. Methods for generating and applying pharmacophore models as virtual screening filters and for bioactivity profiling[J]. Methods, 2015, 71:113-134.
[27]
Eissa S I, Farrag A M, Shawer T Z, et al. Design, synthesis, 3D pharmacophore, QSAR, and docking studies of some new (6-methoxy-2-naphthyl) propanamide derivatives with expected anti-bacterial activity as FABI inhibitor[J]. Med Chem Res, 2017, 26(10):2375-2398.
Eissa S I, Farrag A M, Shawer T Z, et al. Design, synthesis, 3D pharmacophore, QSAR, and docking studies of some new (6-methoxy-2-naphthyl) propanamide derivatives with expected anti-bacterial activity as FABI inhibitor[J]. Med Chem Res, 2017, 26(10):2375-2398.
[28]
Koseki Y, Kanetaka H, Tsunosaki J, et al. Tetrahydro-2-furanyl-2,4(1H,3H)-pyrimidinedione derivatives as novel antibacterial compounds against Mycobacterium[J]. Int J Mycobacte, 2017, 6(1):61-69.
Koseki Y, Kanetaka H, Tsunosaki J, et al. Tetrahydro-2-furanyl-2,4(1H,3H)-pyrimidinedione derivatives as novel antibacterial compounds against Mycobacterium[J]. Int J Mycobacte, 2017, 6(1):61-69.
[29]
Huang S Y, Li M, Wang J, et al. HybridDock:a hybrid protein-ligand docking protocol integrating protein-and ligand-based approaches[J]. Chem Inform Mod, 2016, 56(6):1078-1087.
Huang S Y, Li M, Wang J, et al. HybridDock:a hybrid protein-ligand docking protocol integrating protein-and ligand-based approaches[J]. Chem Inform Mod, 2016, 56(6):1078-1087.
[30]
Frey K M, Lombardo M N, Wright D L, et al. Towards the understanding of resistance mechanisms in clinically isolated trimethoprim-resistant, methicillin-resistant Staphylococcus aureus dihydrofolate reductase[J]. J Struct Biol, 2010, 170(1):93-97.
Frey K M, Lombardo M N, Wright D L, et al. Towards the understanding of resistance mechanisms in clinically isolated trimethoprim-resistant, methicillin-resistant Staphylococcus aureus dihydrofolate reductase[J]. J Struct Biol, 2010, 170(1):93-97.
[31]
Drawz S M, Bonomo R A. Three decades of beta-lactamase inhibitors[J]. Clin Microbiol Rev, 2010, 23(1):160-170.
Drawz S M, Bonomo R A. Three decades of beta-lactamase inhibitors[J]. Clin Microbiol Rev, 2010, 23(1):160-170.
[32]
Ferreira R S, Andricopulo A D. Structure-based drug design to overcome drug resistance:challenges and opportunities[J]. Curr Pharm Des, 2014, 20(5):687-693.
Ferreira R S, Andricopulo A D. Structure-based drug design to overcome drug resistance:challenges and opportunities[J]. Curr Pharm Des, 2014, 20(5):687-693.
[33]
Ahamad S, Rahman S, Khan F I, et al. QSAR based therapeutic management of M-tuberculosis[J]. Arch Pharm Res, 2017, 40(6):676-694.
Ahamad S, Rahman S, Khan F I, et al. QSAR based therapeutic management of M-tuberculosis[J]. Arch Pharm Res, 2017, 40(6):676-694.
计算机辅助药物设计在新药研发中的应用,计算机辅助药物设计在抗耐药菌药物研发中的应用进展...相关推荐
- 计算机辅助药物设计在新药研发中的应用,计算机辅助药物设计在新药研发中的应用 | 每日生物评论...
随着分子生物学.X射线晶体学的发展,大量与疾病相关的生物大分子的三维结构被确定:计算机科学的迅速崛起使得数据挖掘.机器学习等技术快速发展.在这两方面的推动下,计算机辅助药物设计(CADD)应运而生,并 ...
- 计算机辅助药物设计在药物合成中的应用,计算机辅助药物设计在药物合成中的应用_郑彦.pdf...
计算机辅助药物设计在药物合成中的应用_郑彦,计算机辅助药物设计,药物设计,药物设计学,基于结构的药物设计,合理药物设计,药物设计学pdf,药物设计软件,第一性原理药物设计,双靶点药物设计 ·6 14 ...
- 药物从研发到上市需要经历哪些流程?||新药研发
研发一种新药从idea开始到药品上市是一个漫长的过程,花费的时间可能需要一二十年之久,在经历上数百万道工序过后,才有可能会研发出一颗救万众于水火的药丸. 无疑新药从研发到上市的背后是一个极其复杂的过程 ...
- 为世界第一大癌症高效研发首创新药,AI大模型助力药物研发叩开未来之门
近日,三位高中生引爆了医药圈,他们使用人工智能(AI)引擎进行靶点发现,确定了多形性胶质母细胞瘤(GBM)的新治疗靶点,多形性胶质母细胞瘤(GBM)是最具侵袭性和最常见的恶性脑肿瘤类型,占所有原发性脑 ...
- 计算机辅助药物设计的一般原理,朱瑞新着--_计算机辅助药物设计(Ⅰ)--基本方法原理概要与实践详解.pdf...
文档介绍: 计算机辅助药物设计 ------ 基本方法原理概要与实践详解作者朱瑞新 2011 年 1 月目录序前言第一章"计算机辅助药物设计"与 M OE 概貌一.导言二.&quo ...
- 中铁上海工程局华东研发中心展厅,cave沉浸空间设计,三折幕片源制作
中铁上海工程局华东研发中心展厅沉浸式三折幕cave空间项目:历时30余天精心打造完成,通过艺术创作的表现手法,围绕中铁上海工程局第一工程有限公司(华东研发中心)内容涵盖企业发展历程.核心业务介绍(海外 ...
- 计算机技术在中医药中的应用,计算机药物虚拟筛选技术在中医药领域中的应用前景...
计算机药物虚拟筛选技术在中医药领域中的应用前景 中国中西医结合杂志 年 月第 卷第 期 , , 学术探讨 计算机药物虚拟筛选技术在中医药领域中的应用前景 朱 摘要 . 伟 ', 陈可冀 徐筱杰 计算机 ...
- 机械中计算机的应用研究,机械设计制造自动化中计算机技术的应用
摘要:现阶段,随着我国科技水平的不断提升,在很大程度上计算机技术的发展与应用.当前计算机技术在各个领域中的应用越来越广泛,将先进的信息技术应用于机械设计制造行业当中,极大的促进了机械行业的发展进步.本 ...
- 语文教学中如何运用计算机辅助教学,计算机辅助教学在语文教学过程中的运用...
信息技术,即信息处理技术,指运用计算机有效地收集.传送和处理信息的技术. 当今世界已跨入二十一世纪, 进入了信息时代,信息技术飞速发展,被广泛应用于各行各业. 计算机辅助教学(CAI)就是计算机在教育 ...
- 中望cad能编写lisp吗_宁水集团:中望CAD解决方案增强设计创新力,加速转型促发展...
业,精于一而至善!宁波水表(集团)股份有限公司(简称"宁水集团")秉承"一业为主,做精做强"的经营理念,深耕供水计量与测量领域60余年,用工匠精神制造和打磨每一 ...
最新文章
- 用Latex做介绍自己和团队科研的网页
- Smarty变量调节器的使用
- 【个人成长学习讨论小组】练习2:角色
- golang go mod包管理
- OpenGL创建一个GLFW窗口的实例
- 一些基于Java的AI框架:Encog,JavaML,Weka
- 那些容易遗忘的web前端问题
- cpp知识汇总(1) 指针vs引用、static、const
- Java并发编程实战~ThreadLocal
- Typecho网站隐藏内容公众号验证码查看涨粉丝插件(美化版)
- 排序算法:选择排序、插入排序、希尔排序
- 思科研究称80%的指纹认证机制均可遭绕过
- a标签download属性无效_使用这些 CSS 属性选择器来提高前端开发效率
- R_差值_拟合_回归_样条
- python在股票中的应用_python在股票市场中的应用,量化大师自编选股公式
- Chrome浏览器谷歌翻译 失效/用不了的解决方法idea-翻译插件失败(TKK: 更新 TKK 失败,请检查网络连接)
- uniapp 微信小程序 map获取接口数据后地图标注marker不会渲染显示
- python数值互换_python值交换
- 关于gitlab Web IDE功能使用
- (每日一练c++)统计某一单科成绩各分数段的分布人数
热门文章
- qq在线咨询功能网页实现(两种方式)实测有效
- 论文阅读笔记:《Hyperspectral image classification via a random patches network》(ISPRSjprs2018)
- 关于供应链,一文教你全面了解什么是供应链
- Java字符串拼接写法 joiner.on
- 读《美国纽约摄影学院摄影教材》上册
- 新手区题目六:坚持60s
- 笔记本电脑升降台市场现状及未来发展趋势分析
- 线性规划求解的python函数 : optimize.linprog
- c语言数组旋转90度,输入n*n的字符矩阵,把它旋转90度后输出??用c语言写,拜托了,急啊!!...
- 《J2SE 回炉再造14》-------溺水狗