Suppr超能文献

锤头鲨:将柔性配体快速、全自动对接至蛋白质结合位点。

Hammerhead: fast, fully automated docking of flexible ligands to protein binding sites.

作者信息

Welch W, Ruppert J, Jain A N

机构信息

Arris Pharmaceutical Corporation, 385 Oyster Point Boulevard, South San Francisco, CA 94080, USA.

出版信息

Chem Biol. 1996 Jun;3(6):449-62. doi: 10.1016/s1074-5521(96)90093-9.

Abstract

BACKGROUND

Molecular docking seeks to predict the geometry and affinity of the binding of a small molecule to a given protein of known structure. Rigid docking has long been used to screen databases of small molecules, because docking techniques that account for ligand flexibility have either been too slow or have required significant human intervention. Here we describe a docking algorithm, Hammerhead, which is a fast, automated tool to screen for the binding of flexible molecules to protein binding sites.

RESULTS

We used Hammerhead to successfully dock a variety of positive control ligands into their cognate proteins. The empirically tuned scoring function of the algorithm predicted binding affinities within 1.3 log units of the known affinities for these ligands. Conformations and alignments close to those determined crystallographically received the highest scores. We screened 80 000 compounds for binding to streptavidin, and biotin was predicted as the top-scoring ligand, with other known ligands included among the highest-scoring dockings. The screen ran in a few days on commonly available hardware.

CONCLUSIONS

Hammerhead is suitable for screening large databases of flexible molecules for binding to a protein of known structure. It correctly docks a variety of known flexible ligands, and it spends an average of only a few seconds on each compound during a screen. The approach is completely automated, from the elucidation of protein binding sites, through the docking of molecules, to the final selection of compounds for assay.

摘要

背景

分子对接旨在预测小分子与已知结构的特定蛋白质结合的几何结构和亲和力。刚性对接长期以来一直用于小分子数据库的筛选,因为考虑配体灵活性的对接技术要么速度太慢,要么需要大量人工干预。在此,我们描述一种对接算法——锤头算法(Hammerhead),它是一种快速、自动化的工具,用于筛选柔性分子与蛋白质结合位点的结合情况。

结果

我们使用锤头算法成功地将多种阳性对照配体对接至其同源蛋白质。该算法经经验调整的评分函数预测的结合亲和力与这些配体已知亲和力相差在1.3个对数单位以内。与晶体学确定的构象和比对相近的构象和比对得分最高。我们筛选了80000种化合物与链霉亲和素的结合情况,预测生物素是得分最高的配体,其他已知配体也在得分最高的对接结果之中。该筛选在几天内利用常用硬件完成。

结论

锤头算法适用于筛选大量柔性分子数据库,以寻找与已知结构蛋白质的结合情况。它能正确对接多种已知的柔性配体,在筛选过程中对每个化合物平均仅耗时几秒。该方法完全自动化,从蛋白质结合位点的阐明,到分子对接,再到用于检测的化合物的最终选择。

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