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相关概念视频

Drug Discovery: Overview01:26

Drug Discovery: Overview

Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...
Structure-Activity Relationships and Drug Design01:28

Structure-Activity Relationships and Drug Design

Drug design is a dynamic field that involves discovering and developing new medications based on specific biological targets. This process heavily relies on structure-activity relationships (SAR) and quantitative structure-activity relationships (QSAR) to guide the design and optimization of efficient drugs.
SAR studies the intricate relationship between a drug's chemical structure and biological activity. It focuses on understanding how modifications to a drug's structure can influence its...

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相关实验视频

Updated: Jun 20, 2026

Workflow and Tools for Crystallographic Fragment Screening at the Helmholtz-Zentrum Berlin
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SpaceHASTEN:一个基于结构的虚拟选工具,用于未编号的虚拟化学库.

Tuomo Kalliokoski1, Ainoleena Turku1, Heikki Käsnänen1

  • 1Orion Pharma, Orionintie 1A, 02101 Espoo, Finland.

Journal of chemical information and modeling
|December 23, 2024
PubMed
概括

为了药物发现,探索广的化学空间是具有挑战性的. 一个名为SpaceHASTEN的新工具,可以对非编号化学空间进行高效的基于结构的虚拟选,从而识别出新药候选物.

科学领域:

  • 计算化学是一种计算化学.
  • 药物发现 药物发现
  • 化学信息学 化学信息学

背景情况:

  • 为了药物发现,完全列举化学图书馆在计算上是不可行的,因为化学空间庞大.
  • 非编号的虚拟化学空间提供了一个切实可行的替代方案,将化合物作为由规则连接的构建块.
  • 现有的搜索这些空间的工具主要使用基于连接体的方法,缺乏基于蛋白质结构的选能力.

研究的目的:

  • 为了开发一种新的混合联体/基于结构的虚拟选工具,SpaceHASTEN.
  • 以蛋白质结构作为输入来实现非编号化学空间的高效基于结构的虚拟选.
  • 用蛋白质结构查询来选非编号化学空间的软件的缺口.

主要方法:

  • 开发SpaceHASTEN,将SpaceLight,FTrees,LigPrep和Glide集成在一起.
  • 使用混合方法,结合基于连接体和基于结构的虚拟选方法.
  • 使用DUD-E数据集中的三个公共目标进行验证.

主要成果:

  • SpaceHASTEN成功地在非编号化学空间上进行了基于结构的虚拟选.
  • 该工具确定了大量多样化和新的高分数组合物 (虚拟命中).
  • 选数百万种化合物允许从化学空间中的数十亿个分子中检索出命中.

更多相关视频

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相关实验视频

Last Updated: Jun 20, 2026

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Published on: March 3, 2021

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Achieving Efficient Fragment Screening at XChem Facility at Diamond Light Source
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结论:

  • SpaceHASTEN提供了一种高效的解决方案,用于基于结构的虚拟选大型,未编号的化学空间.
  • 开发的工具通过利用蛋白质结构信息来促进新药候选者的发现.
  • 免费可用的软件为计算药物发现工作提供了宝贵的资源.