Analysis and comparison of 2D fingerprints: Insights into database screening performance using eight fingerprint methods

Duan, Jian‐Xin; Dixon, Steven L.; Lowrie, Jeffrey F.; Sherman, Woody

doi:10.1016/j.jmgm.2010.05.008

Cited by 422 publications

(293 citation statements)

References 59 publications

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“…The W values (all statistically significant at p <= 0.01) and resulting mean ranks for the MDDR and WOMBAT searches are listed in Table 5 where, as before, the best performance is bold-faced and italicised. Two recent comparisons of 2D fingerprints have shown the general effectiveness of circular substructures for similarity applications [21,22], and the results in the table show that this is also the case here for the ECFP4 and FCFP4 substructures [26] when used with the MDDR and WOMBAT datasets. The MUV searches have been excluded from Table 5 as the W value of 0.03 was not statistically significant at the 0.01 level, i.e., there was no degree of consistency in the ranking of the different fingerprints.…”

Section: Resultssupporting

confidence: 63%

“…The BCI and MDL fingerprints are dictionary-based, the Daylight and Pipeline Pilot fingerprints are molecule-based, and the Unity fingerprints employ both types of generation method. The use of these and other types of fingerprints for similaritybased virtual screening are described by Hert et al [12], Sastry et al [21] and Duan et al [22].…”

Section: Methodsmentioning

confidence: 99%

“…For example, Holliday et al have discussed the use of 22 different similarity coefficients for the matching of chemical fingerprints [23]; however, despite the many alternatives and despite the known limitations of the Tanimoto coefficient [3], it is this coefficient that continues to be the most widely used. As another example, Duan et al note that fingerprints can often be implemented in multiple ways, with their extensive comparison of similarity methods for virtual screening involving 11 different parameterisations of the atoms involved in each substructural fragment encoded in a fingerprint [22]; the comparison here has used two popular representations (ECFP4 and FCFP4) in the Pipeline Pilot software to exemplify the use of alternative approaches to atom-typing. Other factors that may affect the effectiveness of fingerprint implementations include: the length of the fingerprint that is used, especially if hashing techniques are employed that can result in substantial numbers of collisions [21]; and whether incidence or occurrence data is used, i.e., whether the fingerprint encodes merely the presence of a fragment, its frequency of occurrence, or some standardised form of the latter [24].…”

Section: Methodsmentioning

confidence: 99%

“…Increases in retrieval effectiveness could certainly be obtained by appropriate choice of method and/or parameterisation for specific activity classes and/or reference structures [4,22]; however, the training data necessary for such tuning is often unavailable in the early stages of a discovery project when similarity methods are most commonly employed.…”

Section: Methodsmentioning

confidence: 99%

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Effectiveness of 2D Fingerprints for Scaffold Hopping

et al. 2011

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Universities of LeedsMethods. This paper reports a detailed evaluation of the effectiveness of six common types of 2D fingerprint when they are used for scaffold hopping similarity searches of MDDR, WOMBAT and MUV data.Results. The results demonstrate that 2D fingerprints can be used for scaffold hopping, with novel scaffolds being identified in nearly every search that was carried out. The degree of enrichment depends on the structural diversity of the actives that are being sought, with the greatest enrichments often being obtained using ECFP4 fingerprints. Conclusions. 2D fingerprints provide a simple, and computationally efficient, way of identifying novel chemotypes in lead-discovery programmes.

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Section: Resultssupporting

confidence: 63%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Effectiveness of 2D Fingerprints for Scaffold Hopping

et al. 2011

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“…The features should be able to describe the differences between actives and inactives in the training set and allow extrapolating to other, yet untested compounds. Although several molecular fingerprints, such as extended-connectivity, substructure-based or path-based fingerprints are standards in the chemoinformatics field and have been successfully applied to prediction tasks, the results are dependent on the data and none of the methods is able to clearly outperform the others (Duan et al, 2010). To avoid the choice of the wrong descriptor, the combination of (independent) fingerprints has been suggested (Duan et al, 2010) and several studies have successfully applied combinations of path-and substructure-based fingerprints (Drwal et al, 2014;Banerjee et al, 2015).…”

Section: Combination Of Features and Algorithmsmentioning

confidence: 99%

Molecular similarity-based predictions of the Tox21 screening outcome

Drwal

Siramshetty

Banerjee

et al. 2015

Front. Environ. Sci.

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Citation:Drwal MN, Siramshetty VB, Banerjee P, Goede A, Preissner R and Dunkel M (2015) To assess the toxicity of new chemicals and drugs, regulatory agencies require in vivo testing for many toxic endpoints, resulting in millions of animal experiments conducted each year. However, following the Replace, Reduce, Refine (3R) principle, the development and optimization of alternative methods, in particular in silico methods, has been put into focus in the recent years. It is generally acknowledged that the more complex a toxic endpoint, the more difficult it is to model. Therefore, computational toxicology is shifting from modeling general and complex endpoints to the investigation and modeling of pathways of toxicity and the underlying molecular effects. The U.S. Toxicology in the twenty-first century (Tox21) initiative has screened a large library of compounds, including approximately 10K environmental chemicals and drugs, for different mechanisms responsible for eliciting toxic effects, and made the results publicly available. Through the Tox21 Data Challenge, the consortium has established a platform for computational toxicologists to develop and validate their predictive models. Here, we present a fast and successful method for the prediction of different outcomes of the nuclear receptor and stress response pathway screening from the Tox21 Data Challenge 2014. The method is based on the combination of molecular similarity calculations and a naïve Bayes machine learning algorithm and has been implemented as a KNIME pipeline. Molecules are represented as binary vectors consisting of a concatenation of common two-dimensional molecular fingerprint types with topological compound properties. The prediction method has been optimized individually for each modeled target and evaluated in a cross-validation as well as with the independent Tox21 validation set. Our results show that the method can achieve good prediction accuracies and rank among the top algorithms submitted to the prediction challenge, indicating its broad applicability in toxicity prediction.

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Selecting, Acquiring, and Using Small Molecule Libraries for High‐Throughput Screening

Dandapani

Rossé

Southall

et al. 2012

CP Chemical Biology

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The selection, acquisition, and use of high‐quality small molecule libraries for screening is an essential aspect of drug discovery and chemical biology programs. Screening libraries continue to evolve as researchers gain a greater appreciation of the suitability of small molecules for specific biological targets, processes, and environments. The decision surrounding the makeup of any given small molecule library is informed by a multitude of variables, and opinions vary on best practices. The fitness of any collection relies upon upfront filtering to avoid problematic compounds, assess appropriate physicochemical properties, install the ideal level of structural uniqueness, and determine the desired extent of molecular complexity. These criteria are under constant evaluation and revision as academic and industrial organizations seek out collections that yield ever‐improving results from their screening portfolios. Practical questions including cost, compound management, screening sophistication, and assay objective also play a significant role in the choice of library composition. This overview attempts to offer advice to all organizations engaged in small molecule screening based upon current best practices and theoretical considerations in library selection and acquisition. Curr. Protoc. Chem. Biol. 4:177‐191 © 2012 by John Wiley & Sons, Inc.

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Analysis and comparison of 2D fingerprints: Insights into database screening performance using eight fingerprint methods

Cited by 422 publications

References 59 publications

Effectiveness of 2D Fingerprints for Scaffold Hopping

Effectiveness of 2D Fingerprints for Scaffold Hopping

Molecular similarity-based predictions of the Tox21 screening outcome

Selecting, Acquiring, and Using Small Molecule Libraries for High‐Throughput Screening

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