Literature DB >> 20838964

Molecular similarity measures.

Gerald M Maggiora1, Veerabahu Shanmugasundaram.   

Abstract

Molecular similarity is a pervasive concept in chemistry. It is essential to many aspects of chemical reasoning and analysis and is perhaps the fundamental assumption underlying medicinal chemistry. Dissimilarity, the complement of similarity, also plays a major role in a growing number of applications of molecular diversity in combinatorial chemistry, high-throughput screening, and related fields. How molecular information is represented, called the representation problem, is important to the type of molecular similarity analysis (MSA) that can be carried out in any given situation. In this work, four types of mathematical structure are used to represent molecular information: sets, graphs, vectors, and functions. Molecular similarity is a pairwise relationship that induces structure into sets of molecules, giving rise to the concept of chemical space. Although all three concepts - molecular similarity, molecular representation, and chemical space - are treated in this chapter, the emphasis is on molecular similarity measures. Similarity measures, also called similarity coefficients or indices, are functions that map pairs of compatible molecular representations that are of the same mathematical form into real numbers usually, but not always, lying on the unit interval. This chapter presents a somewhat pedagogical discussion of many types of molecular similarity measures, their strengths and limitations, and their relationship to one another. An expanded account of the material on chemical spaces presented in the first edition of this book is also provided. It includes a discussion of the topography of activity landscapes and the role that activity cliffs in these landscapes play in structure-activity studies.

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Year:  2011        PMID: 20838964     DOI: 10.1007/978-1-60761-839-3_2

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  18 in total

1.  Design, Synthesis, and Evaluation of Novel 3-Carboranyl-1,8-Naphthalimide Derivatives as Potential Anticancer Agents.

Authors:  Sebastian Rykowski; Dorota Gurda-Woźna; Marta Orlicka-Płocka; Agnieszka Fedoruk-Wyszomirska; Małgorzata Giel-Pietraszuk; Eliza Wyszko; Aleksandra Kowalczyk; Paweł Stączek; Andrzej Bak; Agnieszka Kiliszek; Wojciech Rypniewski; Agnieszka B Olejniczak
Journal:  Int J Mol Sci       Date:  2021-03-09       Impact factor: 5.923

2.  BioSM: metabolomics tool for identifying endogenous mammalian biochemical structures in chemical structure space.

Authors:  Mai A Hamdalla; Ion I Mandoiu; Dennis W Hill; Sanguthevar Rajasekaran; David F Grant
Journal:  J Chem Inf Model       Date:  2013-02-27       Impact factor: 4.956

3.  Multiple search methods for similarity-based virtual screening: analysis of search overlap and precision.

Authors:  John D Holliday; Evangelos Kanoulas; Nurul Malim; Peter Willett
Journal:  J Cheminform       Date:  2011-08-08       Impact factor: 5.514

Review 4.  Chemical structure identification in metabolomics: computational modeling of experimental features.

Authors:  Lochana C Menikarachchi; Mai A Hamdalla; Dennis W Hill; David F Grant
Journal:  Comput Struct Biotechnol J       Date:  2013-03-01       Impact factor: 7.271

5.  XTMS: pathway design in an eXTended metabolic space.

Authors:  Pablo Carbonell; Pierre Parutto; Joan Herisson; Shashi Bhushan Pandit; Jean-Loup Faulon
Journal:  Nucleic Acids Res       Date:  2014-05-03       Impact factor: 16.971

6.  MetMaxStruct: A Tversky-Similarity-Based Strategy for Analysing the (Sub)Structural Similarities of Drugs and Endogenous Metabolites.

Authors:  Steve O'Hagan; Douglas B Kell
Journal:  Front Pharmacol       Date:  2016-08-22       Impact factor: 5.810

Review 7.  Two Decades of 4D-QSAR: A Dying Art or Staging a Comeback?

Authors:  Andrzej Bak
Journal:  Int J Mol Sci       Date:  2021-05-14       Impact factor: 5.923

8.  Enhanced ranking of PknB Inhibitors using data fusion methods.

Authors:  Abhik Seal; Perumal Yogeeswari; Dharmaranjan Sriram; David J Wild
Journal:  J Cheminform       Date:  2013-01-14       Impact factor: 5.514

9.  Web-based 3D-visualization of the DrugBank chemical space.

Authors:  Mahendra Awale; Jean-Louis Reymond
Journal:  J Cheminform       Date:  2016-05-04       Impact factor: 5.514

10.  ITPI: Initial Transcription Process-Based Identification Method of Bioactive Components in Traditional Chinese Medicine Formula.

Authors:  Baixia Zhang; Yanwen Li; Yanling Zhang; Zhiyong Li; Tian Bi; Yusu He; Kuokui Song; Yun Wang
Journal:  Evid Based Complement Alternat Med       Date:  2016-02-29       Impact factor: 2.629

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