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化学信息学中的分子相似性与多样性:从理论到应用

Molecular similarity and diversity in chemoinformatics: from theory to applications.

作者信息

Maldonado Ana G, Doucet J P, Petitjean Michel, Fan Bo-Tao

机构信息

ITODYS, Université Paris 7--Denis Diderot, CNRS UMR-7086, 1 rue Guy de la Brosse, 75005, Paris, France.

出版信息

Mol Divers. 2006 Feb;10(1):39-79. doi: 10.1007/s11030-006-8697-1.

DOI:10.1007/s11030-006-8697-1
PMID:16404528
Abstract

This review is dedicated to a survey on molecular similarity and diversity. Key findings reported in recent investigations are selectively highlighted and summarized. Even if this overview is mainly centered in chemoinformatics, applications in other areas (pharmaceutical and medical chemistry, combinatorial chemistry, chemical databases management, etc.) are also introduced. The approaches used to define and describe the concepts of molecular similarity and diversity in the context of chemoinformatics are discussed in the first part of this review. We introduce, in the second and third parts, the descriptions and analyses of different methods and techniques. Finally, current applications and problems are enumerated and discussed in the last part.

摘要

本综述致力于对分子相似性和多样性进行调查。近期研究报告中的关键发现被有选择地突出并总结。即使本概述主要集中在化学信息学领域,但也介绍了在其他领域(药物化学和医学化学、组合化学、化学数据库管理等)的应用。本综述的第一部分讨论了在化学信息学背景下用于定义和描述分子相似性和多样性概念的方法。在第二和第三部分中,我们介绍了不同方法和技术的描述与分析。最后,在最后一部分列举并讨论了当前的应用和问题。

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本文引用的文献

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Self-similarity and protein chains.自相似性与蛋白质链
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Hit-directed nearest-neighbor searching.命中导向的最近邻搜索。
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Molecular similarity in chemical informatics and predictive toxicity modeling: from quantitative read-across (q-RA) to quantitative read-across structure-activity relationship (q-RASAR) with the application of machine learning.化学信息学和预测性毒理学建模中的分子相似性:从定量文献外推 (q-RA) 到基于机器学习的定量文献外推结构-活性关系 (q-RASAR)。
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Drug Repurposing: Insights into Current Advances and Future Applications.药物再利用:当前进展与未来应用洞察
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Network Science and Group Fusion Similarity-Based Searching to Explore the Chemical Space of Antiparasitic Peptides.基于网络科学和群组融合相似性的搜索以探索抗寄生虫肽的化学空间
ACS Omega. 2022 Dec 6;7(50):46012-46036. doi: 10.1021/acsomega.2c03398. eCollection 2022 Dec 20.
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Selecting molecules with diverse structures and properties by maximizing submodular functions of descriptors learned with graph neural networks.通过最大化基于图神经网络学习的描述符的子模函数来选择具有多样结构和性质的分子。
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Protegrin structure-activity relationships: using homology models of synthetic sequences to determine structural characteristics important for activity.防御素的结构-活性关系:利用合成序列的同源模型确定对活性重要的结构特征。
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Biological spectra analysis: Linking biological activity profiles to molecular structure.生物光谱分析:将生物活性谱与分子结构联系起来。
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"Lead hopping". Validation of topomer similarity as a superior predictor of similar biological activities.“先导跳跃”。验证拓扑异构体相似性作为相似生物活性的优越预测指标。
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A 3D similarity method for scaffold hopping from known drugs or natural ligands to new chemotypes.一种用于从已知药物或天然配体跳跃到新化学类型的支架的三维相似性方法。
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SitePrint: three-dimensional pharmacophore descriptors derived from protein binding sites for family based active site analysis, classification, and drug design.位点印记:从蛋白质结合位点衍生的三维药效团描述符,用于基于家族的活性位点分析、分类和药物设计。
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