Chemical Similarity and Substructure Searches

Nils Morten Kriege; Thomas Seidel; Lina Humbeck; Uta Lessel

doi:10.1016/B978-0-323-95502-7.00048-8

Chemical Similarity and Substructure Searches

Nils Morten Kriege, Thomas Seidel, Lina Humbeck, Uta Lessel

Publications: Contribution to book › Chapter › Peer Reviewed

Abstract

Chemical similarity is a fundamental concept in cheminformatics and is used in various tasks, such as predicting biological activities or analyzing molecular datasets. A natural approach to quantifying the similarity of chemical compounds is based on the substructures they share. This chapter focuses on graph-based methods for comparing molecules, particularly algorithms for identifying the maximum common subgraph of two molecular graphs. We discuss the basic graph-theoretical formalizations and summarize the related computational problems, their theoretical complexity and the prevailing algorithmic techniques for their solution as well as corresponding applications.

Original language	English
Title of host publication	Encyclopedia of Bioinformatics and Computational Biology (Second Edition)
Publisher	Elsevier
Volume	3
Edition	2
ISBN (Print)	978-0-323-95503-4
DOIs	https://doi.org/10.1016/B978-0-323-95502-7.00048-8
Publication status	Published - 2025

Austrian Fields of Science 2012

102004 Bioinformatics

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10.1016/B978-0-323-95502-7.00048-8

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title = "Chemical Similarity and Substructure Searches",

abstract = "Chemical similarity is a fundamental concept in cheminformatics and is used in various tasks, such as predicting biological activities or analyzing molecular datasets. A natural approach to quantifying the similarity of chemical compounds is based on the substructures they share. This chapter focuses on graph-based methods for comparing molecules, particularly algorithms for identifying the maximum common subgraph of two molecular graphs. We discuss the basic graph-theoretical formalizations and summarize the related computational problems, their theoretical complexity and the prevailing algorithmic techniques for their solution as well as corresponding applications.",

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AU - Kriege, Nils Morten

AU - Seidel, Thomas

AU - Humbeck, Lina

AU - Lessel, Uta

PY - 2025

Y1 - 2025

N2 - Chemical similarity is a fundamental concept in cheminformatics and is used in various tasks, such as predicting biological activities or analyzing molecular datasets. A natural approach to quantifying the similarity of chemical compounds is based on the substructures they share. This chapter focuses on graph-based methods for comparing molecules, particularly algorithms for identifying the maximum common subgraph of two molecular graphs. We discuss the basic graph-theoretical formalizations and summarize the related computational problems, their theoretical complexity and the prevailing algorithmic techniques for their solution as well as corresponding applications.

AB - Chemical similarity is a fundamental concept in cheminformatics and is used in various tasks, such as predicting biological activities or analyzing molecular datasets. A natural approach to quantifying the similarity of chemical compounds is based on the substructures they share. This chapter focuses on graph-based methods for comparing molecules, particularly algorithms for identifying the maximum common subgraph of two molecular graphs. We discuss the basic graph-theoretical formalizations and summarize the related computational problems, their theoretical complexity and the prevailing algorithmic techniques for their solution as well as corresponding applications.

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DO - 10.1016/B978-0-323-95502-7.00048-8

M3 - Chapter

SN - 978-0-323-95503-4

VL - 3

BT - Encyclopedia of Bioinformatics and Computational Biology (Second Edition)

PB - Elsevier

ER -

Chemical Similarity and Substructure Searches

Abstract

Austrian Fields of Science 2012

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