Suppr超能文献

Analysis of the in vitro antitumor activity of novel purine-6-sulfenamide, -sulfinamide, and -sulfonamide nucleosides and certain related compounds using a computer-aided receptor modeling procedure.

作者信息

Viswanadhan V N, Ghose A K, Hanna N B, Matsumoto S S, Avery T L, Revankar G R, Robins R K

机构信息

ICN Nucleic Acid Research Institute, Costa Mesa, California 92626.

出版信息

J Med Chem. 1991 Feb;34(2):526-32. doi: 10.1021/jm00106a007.

Abstract

The comparative antileukemic activities of 21 novel nucleosides were determined in vitro by using cultured L1210 cells and analyzed for structure-related efficacy by a computer-aided receptor modeling method (REMOTEDISC) as recently described (Ghose, A. K.; et al. J. Med. Chem. 1989, 32, 746). The algorithm can be classified as a 3D-QSAR method and consists of the following steps: selection of a reference structure from the low-energy conformations of the active compounds; an automated superposition of the low-energy conformations of the other compounds so that there is maximum matching (or overlapping) of the atom-based physicochemical properties; construction of the binding-site cavity from the location of the atoms of the superimposed molecules; and determinations of the relative importance of the various physicochemical properties at different regions of the site cavity using reverse stepwise regression analysis. The model was based on the minimum energy conformation of (R,S)-2-amino-9-beta-D-ribofuranosylpurine-6-sulfinamide (sulfinosine, 5), an effective antileukemic agent in vivo, in the data set. The model fit the biological data with a standard deviation of 0.363, a correlation coefficient of 0.933 and a explained variance of 0.815. The method targeted a syn conformation as the probable active form and the 2'-OH, 5'-OH as well as C2-NH2 group of the purine ring as favoring the stability of the syn conformation, thereby establishing the major contributions of these three molecular entities to overall antitumor activity.

摘要

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