Application of NMR and molecular docking in structure-based drug discovery.
Application of NMR and molecular docking in structure-based drug discovery.
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DOI：
10.1007/128_2011_213
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发表时间：
2012
影响因子：
8.6
通讯作者：
Powers R
中科院分区：
文献类型：
--
作者：
Stark JL;Powers R
药物发现是一项复杂而昂贵的奋进，很少有达到临床测试阶段的药物进入市场。高通量筛选（HTS）是制药行业用于鉴定初始先导化合物的主要方法。不幸的是，HTS的失败率很高，并且在识别可行的药物线索方面不是特别有效。这些缺点鼓励了替代方法的开发，以推动药物发现过程。具体而言，核磁共振（NMR）光谱和分子对接通常被用作药物发现研究的重要组成部分。分子对接提供了一种非常快速的方法，以最小的成本从大型化学库中评估可能的结合剂。NMR配体-亲和筛选可以直接检测蛋白质-配体相互作用，可以测量相应的解离常数，并且可以可靠地鉴定配体结合位点并产生共结构。此外，NMR配体亲和筛选和分子对接是完全互补的技术，两者的结合有可能提高药物发现的效率和成功率。本文将重点介绍NMR配体亲和筛选和分子对接在药物发现中的应用，并描述最近将这两种技术结合起来识别新的有效治疗药物的例子。
Drug discovery is a complex and costly endeavor, where few drugs that reach the clinical testing phase make it to market. High-throughput screening (HTS) is the primary method used by the pharmaceutical industry to identify initial lead compounds. Unfortunately, HTS has a high failure rate and is not particularly efficient at identifying viable drug leads. These shortcomings have encouraged the development of alternative methods to drive the drug discovery process. Specifically, nuclear magnetic resonance (NMR) spectroscopy and molecular docking are routinely being employed as important components of drug discovery research. Molecular docking provides an extremely rapid way to evaluate likely binders from a large chemical library with minimal cost. NMR ligand-affinity screens can directly detect a protein-ligand interaction, can measure a corresponding dissociation constant, and can reliably identify the ligand binding site and generate a co-structure. Furthermore, NMR ligand affinity screens and molecular docking are perfectly complementary techniques, where the combination of the two has the potential to improve the efficiency and success rate of drug discovery. This review will highlight the use of NMR ligand affinity screens and molecular docking in drug discovery and describe recent examples where the two techniques were combined to identify new and effective therapeutic drugs.
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DOI：
10.2174/1386207023329923
发表时间：
2002-12-01
影响因子：
1.8
作者：
Dalvit, C;Flocco, M;Stockman, BJ
通讯作者：
Stockman, BJ
影响因子：
2.9
作者：
Branson, Kim M.;Mertens, Haydyn D. T.;Smith, Brian J.
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Smith, Brian J.
影响因子：
3.1
作者：
Cao, TC;Li, TH
通讯作者：
Li, TH
影响因子：
3.5
作者：
BOHM, HJ
通讯作者：
BOHM, HJ
影响因子：
14.9
作者：
del Val, C;Mehrle, A;Wiemann, S
通讯作者：
Wiemann, S