Suppr超能文献

蛋白质和配体三维结构的对接前过滤器。

Pre-docking filter for protein and ligand 3D structures.

作者信息

Wilantho Alisa, Tongsima Sissades, Jenwitheesuk Ekachai

机构信息

National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, 113 Thailand Science Park, Phahonyothin Road, Klong 1, Klongluang, Pathumtani 12120, Thailand.

出版信息

Bioinformation. 2008;3(5):189-93. doi: 10.6026/97320630003189. Epub 2008 Dec 31.

Abstract

Virtual drug screening using protein-ligand docking techniques is a time-consuming process, which requires high computational power for binding affinity calculation. There are millions of chemical compounds available for docking. Eliminating compounds that are unlikely to exhibit high binding affinity from the screening set should speed-up the virtual drug screening procedure. We performed docking of 6353 ligands against twenty-one protein X-ray crystal structures. The docked ligands were ranked according to their calculated binding affinities, from which the top five hundred and the bottom five hundred were selected. We found that the volume and number of rotatable bonds of the top five hundred docked ligands are similar to those found in the crystal structures and corresponded with the volume of the binding sites. In contrast, the bottom five hundred set contains ligands that are either too large to enter the binding site, or too small to bind with high specificity and affinity to the binding site. A pre-docking filter that takes into account shapes and volumes of the binding sites as well as ligand volumes and flexibilities can filter out low binding affinity ligands from the screening sets. Thus, the virtual drug screening procedure speed is increased.

摘要

使用蛋白质-配体对接技术进行虚拟药物筛选是一个耗时的过程,它需要高计算能力来进行结合亲和力计算。有数以百万计的化合物可用于对接。从筛选集中剔除那些不太可能表现出高结合亲和力的化合物应该能加快虚拟药物筛选过程。我们针对21种蛋白质X射线晶体结构对6353种配体进行了对接。对接后的配体根据其计算出的结合亲和力进行排序,从中选出了前500个和后500个。我们发现,对接的前500个配体的体积和可旋转键的数量与晶体结构中的相似,并且与结合位点的体积相对应。相比之下,后500个配体集中包含的配体要么太大而无法进入结合位点,要么太小而无法以高特异性和亲和力与结合位点结合。一个考虑结合位点的形状和体积以及配体体积和灵活性的对接前过滤器可以从筛选集中滤除低结合亲和力的配体。因此,虚拟药物筛选过程的速度得以提高。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df79/2646187/923e0e5e2d7a/97320630003189F1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验