Computer-assisted examination of compounds for common three-dimensional substructures

Crandell, Christopher W.; Smith, Dennis H.

doi:10.1021/ci00040a009

Cited by 66 publications

(34 citation statements)

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“…In some cases, this is because they are by now very old, such as the seminal -and I use the word advisedly -contributions by Ray and Kirsch [32] and by Vleduts [33] to the searching of molecules and of reactions, respectively. In other cases, the original work was over-shadowed by subsequent publications: for example, the 1981 paper by Lynch et al [34] was merely the first in a sequence of over twenty publications on the representation and searching of generic structures; and the 1983 graph-matching paper by Crandell and Smith [35] resulted a decade later in the first successful commercial system for pharmacophore mapping [36] (vide infra). In still other cases, the importance of the work was simply not fully recognised at the time, e.g., the paper by Adamson and Bush [37] on comparing fragment bit-strings to compute molecular similarity preceded the first descriptions of similarity searching systems by over a decade [38,39]; indeed, it was this 1973 paper that was one of the principal drivers for work in Sheffield on fingerprint-based searching and clustering that commenced in the Eighties [40] and that continues to the present day [41].…”

Section: Selection Of Key Papersmentioning

confidence: 99%

“…This limitation was first overcome in a study by Crandell and Smith [35], who described the use of an MCS algorithm to find 3D patterns common to sets of molecules. The work was carried out as an aid to structure elucidation (see below) but is also clearly applicable to the problem of pharmacophore mapping.…”

Section: Quantitative Structure-activity Relationships and Molecular mentioning

confidence: 99%

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From chemical documentation to chemoinformatics: 50 years of chemical information science

Willett

2008

Journal of Information Science

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This paper summarises the historical development of the discipline that is now called 'chemoinformatics'. It shows how this has evolved, principally as a result of technological developments in chemistry and biology during the past decade, from long-established techniques for the modelling and searching of chemical molecules. A total of 30 papers, the earliest dating back to 1957, are briefly summarised to highlight some of the key publications and to show the development of the discipline.Keywords: Chemical documentation; Chemical structures; Chemoinformatics; Drug discovery; History; Informatics; Molecules; Pharmaceutical research IntroductionChemistry is, and has been for many years, one of the most information-rich academic disciplines. The very first journal devoted to chemistry was Chemisches Journal, which was published 1778-1784 and then, under the name of Chemische Annalen, till 1803 [1]. The growth in the chemical literature during the 19 th century led to a recognition of the need for comprehensive abstracting and indexing services for the chemical sciences. The principal such service is Chemical Abstracts Service (CAS), which was established in 1907 and which acts as the central repository for the world's published chemical (and, increasingly, life-sciences) information. The size of this repository is impressive: at the end of its first year of operations, the CAS database contained ca. 12K abstracts; by the end of 2006, this had grown to ca. 25M abstracts with ca. 1M being added each year. Most chemical publications will refer to one or more chemical substances. The structures of these substances form a vitally important part of the chemical literature, and one that distinguishes chemistry from many other disciplines. The CAS Registry System was started in 1965 to provide access to substance information, initially registering just small organic and inorganic molecules but now also registering biological sequences [2]. At the end of 1965 there 1 Correspondence to: Prof. Peter Willett, Department of Information Studies, University of Sheffield, 211 Portobello Street, Sheffield S1 4DP, UK; p.willett@sheffield.ac.uk. Journal of Information Science, XX (X) 2007, pp. 1-24 © CILIP, DOI: 10.1177/0165551506nnnnnn 1 Peter Willettwere ca. 222K substances in the System; by the end of 2006 this had grown to ca. 89M substances, of which ca. one-third were small molecules and the remainder biological sequences, with ca. 1.5M being added each year. There are also many additional molecular structures in public databases such as the Beilstein Database [3], and corporate files, in particular those of the major pharmaceutical, agrochemical and biotechnology companies.The presence of chemical structures requires very different computational techniques from those used for processing conventional textual information. These specialised techniques -now referred to by the name of chemoinformatics as discussed further below -have developed steadily over the fifty years that have passed since the founding of the I...

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Section: Selection Of Key Papersmentioning

confidence: 99%

Section: Quantitative Structure-activity Relationships and Molecular mentioning

confidence: 99%

From chemical documentation to chemoinformatics: 50 years of chemical information science

Willett

2008

Journal of Information Science

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“…Examples for such methods include the CrandellSmith method [13], RAPID [14] and HipHop [15][16][17]. In other methods information about inactive ligands is also used.…”

Section: Inputmentioning

confidence: 99%

Predicting Molecular Interactions in silico: I. A Guide to Pharmacophore Identification and its Applications to Drug Design

Dror

Shulman‐Peleg²,

Nussinov³

et al. 2004

CMC

145

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A major goal in contemporary drug design is to develop new ligands with high affinity of binding toward a given protein receptor. Pharmacophore, which is the three-dimensional arrangement of essential features that enable a molecule to exert a particular biological effect, is a very useful model for achieving this goal. If the three-dimensional structure of the receptor is known, pharmacophore is a complementary tool to standard techniques, such as docking. However, frequently the structure of the receptor protein is unknown and only a set of ligands together with their measured binding affinities towards the receptor is available. In such a case, a pharmacophore-based strategy is one of the few applicable tools.Here we present a broad, yet concise guide to pharmacophore identification and review a sample of applications for drug design. In particular, we present the framework of the algorithms, classify their modules and point out their advantages and challenges.

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“…The Barakat-Dean algorithm is an example of an algorithm that was originally proposed in a 3D formulation, and so is the algorithm described by Crandell and Smith [78], although even this owes much to the algorithm of Varkony et al [66], in that it attempts to "grow" a 3D MCIS iteratively. The Crandell-Smith algorithm was studied in detail by Brint and Willett [42], who found that a clique-based method using the Bron-Kerbosch algorithm was generally to be preferred for the identification of the 3D…”

Section: D-specific Algorithmsmentioning

confidence: 99%

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Raymond

Willett

2002

Journal of Computer-Aided Molecular Design

340

118

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The maximum common subgraph (MCS) problem has become increasingly important in those aspects of chemoinformatics that involve the matching of 2D or 3D chemical structures. This paper provides a classification and a review of the many MCS algorithms, both exact and approximate, that have been described in the literature, and makes recommendations regarding their applicability to typical chemoinformatics tasks.

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Computer-assisted examination of compounds for common three-dimensional substructures

Cited by 66 publications

References 10 publications

From chemical documentation to chemoinformatics: 50 years of chemical information science

From chemical documentation to chemoinformatics: 50 years of chemical information science

Predicting Molecular Interactions in silico: I. A Guide to Pharmacophore Identification and its Applications to Drug Design

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