How Similar Are Similarity Searching Methods? A Principal Component Analysis of Molecular Descriptor Space

Bender, Andreas; Jenkins, Jeremy L.; Scheiber, Josef; Sukuru, Sai Chetan K.; Glick, Meir; Davies, John W.

doi:10.1021/ci800249s

Cited by 264 publications

(244 citation statements)

References 46 publications

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“…It is noteworthy that it is superior to both TAN, COS and TAN-B, all of which have been used in previous studies of similarity searching. We note also that TAN-B is superior to TAN, despite the fact that several previous studies have suggested that weighted-searching is superior to binary searching [10; 36; 37]; however, our results here are in accord with recent work by Bender et al [38].…”

Section: Additional Comparison Of Distance Coefficientssupporting

confidence: 89%

Clustering files of chemical structures using the Székely–Rizzo generalization of Ward's method

Varin

Bureau

Mueller

et al. 2009

Journal of Molecular Graphics and Modelling

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Ward's method is extensively used for clustering chemical structures represented by 2D fingerprints. This paper compares Ward clusterings of 14 datasets (containing between 278 and 4332 molecules) with those obtained using the Székely-Rizzo clustering method, a generalization of Ward's method. The clusters resulting from these two methods were evaluated by the extent to which the various classifications were able to group active molecules together, using a novel criterion of clustering effectiveness. Analysis of a total of 1400 classifications (Ward and Székely-Rizzo clustering methods, fourteen different datasets, five different fingerprints and ten different distance coefficients) demonstrated the general superiority of the Székely-Rizzo method. The distance coefficient first described by Soergel performed extremely well in these experiments, and this was also the case when it was used in simulated virtual screening experiments.

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Section: Additional Comparison Of Distance Coefficientssupporting

confidence: 89%

Clustering files of chemical structures using the Székely–Rizzo generalization of Ward's method

Varin

Bureau

Mueller

et al. 2009

Journal of Molecular Graphics and Modelling

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“…Significant progress has been made quantifying and visualizing properties of compound sets (26), including methods that relate structure to intuitive notions of shape (27)(28)(29), and similarity fusion methods (30)(31)(32)(33) that describe relationships between sets. Moreover, chemical similarity and diversity analyses continue to progress (34)(35)(36)(37), including studies using Shannon entropy (38) as a measure of structure information among compounds (39)(40)(41), addressing reagent selection (42), database similarity searches (43), and scaffold diversity (44). Entropy-based methods have also been used on assay data to distinguish single-target compounds from those with multitarget effects (45), and to quantify relationships between targets based on K i profiles among sets of common inhibitors (46).…”

mentioning

confidence: 99%

Quantifying structure and performance diversity for sets of small molecules comprising small-molecule screening collections

Clemons

Wilson

Dančík

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

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Using a diverse collection of small molecules we recently found that compound sets from different sources (commercial; academic; natural) have different protein-binding behaviors, and these behaviors correlate with trends in stereochemical complexity for these compound sets. These results lend insight into structural features that synthetic chemists might target when synthesizing screening collections for biological discovery. We report extensive characterization of structural properties and diversity of biological performance for these compounds and expand comparative analyses to include physicochemical properties and three-dimensional shapes of predicted conformers. The results highlight additional similarities and differences between the sets, but also the dependence of such comparisons on the choice of molecular descriptors. Using a protein-binding dataset, we introduce an information-theoretic measure to assess diversity of performance with a constraint on specificity. Rather than relying on finding individual active compounds, this measure allows rational judgment of compound subsets as groups. We also apply this measure to publicly available data from ChemBank for the same compound sets across a diverse group of functional assays. We find that performance diversity of compound sets is relatively stable across a range of property values as judged by this measure, both in protein-binding studies and functional assays. Because building screening collections with improved performance depends on efficient use of synthetic organic chemistry resources, these studies illustrate an important quantitative framework to help prioritize choices made in building such collections.A central theme in applying cheminformatics to discovery chemistry is to relate synthetic decisions to consequences on both chemical structure and biological assay performance. Historically, such efforts focused on small sets of similar compounds, and single performance measurements (1-3), providing guidance to chemists in compound optimization against singletarget proteins or processes (4). However, additional methods are needed to judge large sets of compounds, such as those used in small-molecule screening. Progress toward more valuable screening collections (5) requires unbiased methods to evaluate diversity of assay performance for compound sets rather than performance of individual members.A widely used method to judge compounds for drug discovery is the "rule of 5" (RO5) (6), which predicts poor absorption or permeation for compounds that deviate from property-value constraints: H-bond donors (Hd) and acceptors (Ha), molecular weight (MW), and calculated partition coefficients (cLogP). Recent studies have attempted to refine such rules (7-9) and extend them to other goals (10-13), such as making leads or probes. Such property filters have been debated and reviewed (14-16), and their long-term impact on pharmaceutical research is starting to be analyzed (17, 18). Importantly, exceptions to these rules, including natural products (19-21), ...

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“…In this article, we describe how we have used diversity-based library subsets to complement this "screen-all" approach, as our subsets have largely been used to supplement full library screens rather than to replace them. Numerous methods have been described for assessing molecular similarity (e.g., see Bender et al 28 and references therein). Reduced topological representations (Murcko assemblies), ECFPs, and atomic property descriptors (BCUT) have all shown promise in the selection of diverse subsets that retain high levels of hit identification.…”

Section: Discussionmentioning

confidence: 99%

Small-Molecule Library Subset Screening as an Aid for Accelerating Lead Identification

Beresini¹,

Liu²,

Dawes³

et al. 2014

SLAS Discovery

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Several small-compound library subsets (14,000 to 56,000) have been established to complement screening of a larger Genentech corporate library (~1,300,000). Two validation sets (~1% of the total library) containing compounds representative of the main library were chosen by selection of plates or individual compounds. Use of these subsets guided selection of assay configuration, validated assay reproducibility, and provided estimates of hit rates expected from our full library. A larger diversity subset representing the scaffold diversity of the full library (3.4% of the total) was designed for screening more challenging targets with limited reagent availability or low-throughput assays. Retrospective analysis of this subset showed hit rates similar to those of the main library while recovering a higher proportion of hit scaffolds. Finally, a property-restricted diversity set called the "in-between library" was established to identify ligand-efficient compounds of molecular size between those typically found in fragment and high-throughput screening libraries. It was screened at fivefold higher concentrations than the main library to facilitate identification of less potent yet ligand-efficient compounds. Taken together, this work underscores the value of generating multiple purpose-focused, diversity-based library subsets that are designed using computational approaches coupled with internal screening data analyses to accelerate the lead discovery process.

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How Similar Are Similarity Searching Methods? A Principal Component Analysis of Molecular Descriptor Space

Cited by 264 publications

References 46 publications

Clustering files of chemical structures using the Székely–Rizzo generalization of Ward's method

Clustering files of chemical structures using the Székely–Rizzo generalization of Ward's method

Quantifying structure and performance diversity for sets of small molecules comprising small-molecule screening collections

Small-Molecule Library Subset Screening as an Aid for Accelerating Lead Identification

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