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STRUCTURE-BASED MODELING AND TARGET-SELECTIVITY PREDICTION

机译:基于结构的建模和目标选择性预测

摘要

The present invention provides, inter alia, methods, models, and systems for selecting an effector having specificity for a target molecule. The methods and systems of the present invention involve several steps, including compiling a database containing structural data for a library of molecules and a population of ligands and activity data, establishing structure-based equivalence of sequence elements in the library of molecules, determining likely spatial orientations of population ligands in library molecules, calculating interaction energies for each ligand-molecule pair, generating statistical models that are predictive of sequence elements likely to contribute to a differential effect of ligands on molecules, selecting an effector that is likely to have a desired specificity for the target molecule, experimentally determining activity data for effector-library molecule pairs, and at least once repeating the steps listed above wherein the effector is a member of the population of ligands.
机译:本发明尤其提供了用于选择对靶分子具有特异性的效应子的方法,模型和系统。本发明的方法和系统涉及几个步骤,包括编译包含分子库和配体群和活性数据的结构数据的数据库,在分子库中建立序列元素的基于结构的等价性,确定可能的空间库分子中群体配体的方向,计算每个配体-分子对的相互作用能,生成可预测可能有助于配体对分子差异作用的序列元件的统计模型,选择可能具有所需特异性的效应子对于靶分子,实验确定效应子-库分子对的活性数据,并至少重复一次以上列出的步骤,其中效应子是配体群体的成员。

著录项

  • 公开/公告号US2016378912A1

    专利类型

  • 公开/公告日2016-12-29

    原文格式PDF

  • 申请/专利权人 EPIGENETX LLC;

    申请/专利号US201414901924

  • 申请日2014-06-30

  • 分类号G06F19/16;G06F19/00;C40B30/02;

  • 国家 US

  • 入库时间 2022-08-21 13:46:45

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