Protein structure prediction in structure based drug design.
Protein structure prediction in structure based drug design.
复制标题
DOI：
10.2174/0929867043455837
复制
发表时间：
2004-02
影响因子：
4.1
通讯作者：
Mayuko Takeda-Shitaka;D. Takaya;C. Chiba;Hirokazu Tanaka;H. Umeyama
中科院分区：
文献类型：
--
作者：
Mayuko Takeda-Shitaka;D. Takaya;C. Chiba;Hirokazu Tanaka;H. Umeyama
人类基因组和其他基因组测序计划已经产生了大量的蛋白质序列信息。最近，一个结构基因组学计划，旨在确定至少一个代表性的三维结构，从每个蛋白质家族的实验已经开始。同源建模将在基于结构的药物设计中发挥重要作用，例如计算机筛选;因为基于这些代表性结构，可以通过同源建模预测各种基因组中编码的剩余蛋白质的三维结构。最近一次蛋白质结构预测技术的关键评估（CASP 5）的结果表明，同源建模预测的质量已经提高;达到了生物学家现在可以自信地使用同源建模的可靠性水平。随着建模软件的改进和已知蛋白质结构数量的增加，同源建模正成为一种越来越强大和可靠的工具。本文讨论了同源模建在基于结构的药物设计中的特点和作用，并以CHIMERA和FAMS为例介绍了同源模建系统。对于一个示例应用，严重急性呼吸综合征（SARS）冠状病毒的非结构蛋白的同源建模进行了讨论。许多生物学功能涉及蛋白质-蛋白质复合物的形成;其中蛋白质分子在结合过程中动态地表现。因此，了解蛋白质-蛋白质相互作用对于基于结构的药物设计是非常重要的。为此，简正模态分析是有用的。本文讨论了用简正模分析预测蛋白质相互作用，并给出了应用实例。
The human genome and other genome sequencing projects have generated huge amounts of protein sequence information. Recently, a structural genomics project that aims to determine at least one representative three-dimensional structure from every protein family experimentally has been started. Homology modeling will play an essential role in structure based drug design such as in silico screening; because based on these representative structures the three-dimensional structures of the remaining proteins encoded in the various genomes can be predicted by homology modeling. The results of the last Critical Assessment of Techniques for Protein Structure Prediction (CASP5) demonstrated that the quality of homology modeling prediction has improved; reaching a level of reliability that biologists can now confidently use homology modeling. With improvements in modeling software and the growing number of known protein structures, homology modeling is becoming a more and more powerful and reliable tool. The present paper discusses the features and roles of homology modeling in structure based drug design, and describes the CHIMERA and FAMS modeling systems as examples. For a sample application, homology modeling of non-structural proteins of the severe acute respiratory syndrome (SARS) coronavirus is discussed. Many biological functions involve formation of protein-protein complexes; in which the protein molecules behave dynamically in the course of binding. Therefore, an understanding of protein-protein interaction will be very important for structure based drug design. To this end, normal mode analysis is useful. The present paper discusses the prediction of protein-protein interaction using normal mode analysis and examples of applications are given.