A generalizable definition of chemical similarity for read-across

Background Methods that provide a measure of chemical similarity are strongly relevant in several fields of chemoinformatics as they allow to predict the molecular behavior and fate of structurally close compounds. One common application of chemical similarity measurements, based on the principle th...
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Autor*in:	Floris, Matteo [verfasserIn] Manganaro, Alberto Nicolotti, Orazio Medda, Ricardo Mangiatordi, Giuseppe Felice Benfenati, Emilio

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2014

Schlagwörter:	Chemical similarity Read-across Applicability domain QSAR

Anmerkung:	© Floris et al.; licensee Springer. 2014. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (

Übergeordnetes Werk:	Enthalten in: Journal of cheminformatics - London : BioMed Central, 2009, 6(2014), 1 vom: 18. Okt.
Übergeordnetes Werk:	volume:6 ; year:2014 ; number:1 ; day:18 ; month:10

Links:	Volltext

DOI / URN:	10.1186/s13321-014-0039-1

Katalog-ID:	SPR031341055

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spelling	10.1186/s13321-014-0039-1 doi (DE-627)SPR031341055 (SPR)s13321-014-0039-1-e DE-627 ger DE-627 rakwb eng Floris, Matteo verfasserin aut A generalizable definition of chemical similarity for read-across 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Floris et al.; licensee Springer. 2014. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( Background Methods that provide a measure of chemical similarity are strongly relevant in several fields of chemoinformatics as they allow to predict the molecular behavior and fate of structurally close compounds. One common application of chemical similarity measurements, based on the principle that similar molecules have similar properties, is the read-across approach, where an estimation of a specific endpoint for a chemical is provided using experimental data available from highly similar compounds. Results This paper reports the comparison of multiple combinations of binary fingerprints and similarity metrics for computing the chemical similarity in the context of two different applications of the read-across technique. Conclusions Our analysis demonstrates that the classical similarity measurements can be improved with a generalizable model of similarity. The proposed approach has already been used to build similarity indices in two open-source software tools (CAESAR and VEGA) that make several QSAR models available. In these tools, the similarity index plays a key role for the assessment of the applicability domain. Chemical similarity (dpeaa)DE-He213 Read-across (dpeaa)DE-He213 Applicability domain (dpeaa)DE-He213 QSAR (dpeaa)DE-He213 Manganaro, Alberto aut Nicolotti, Orazio aut Medda, Ricardo aut Mangiatordi, Giuseppe Felice aut Benfenati, Emilio aut Enthalten in Journal of cheminformatics London : BioMed Central, 2009 6(2014), 1 vom: 18. Okt. (DE-627)594779219 (DE-600)2486539-4 1758-2946 nnns volume:6 year:2014 number:1 day:18 month:10 https://dx.doi.org/10.1186/s13321-014-0039-1 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2014 1 18 10
allfields_unstemmed	10.1186/s13321-014-0039-1 doi (DE-627)SPR031341055 (SPR)s13321-014-0039-1-e DE-627 ger DE-627 rakwb eng Floris, Matteo verfasserin aut A generalizable definition of chemical similarity for read-across 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Floris et al.; licensee Springer. 2014. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( Background Methods that provide a measure of chemical similarity are strongly relevant in several fields of chemoinformatics as they allow to predict the molecular behavior and fate of structurally close compounds. One common application of chemical similarity measurements, based on the principle that similar molecules have similar properties, is the read-across approach, where an estimation of a specific endpoint for a chemical is provided using experimental data available from highly similar compounds. Results This paper reports the comparison of multiple combinations of binary fingerprints and similarity metrics for computing the chemical similarity in the context of two different applications of the read-across technique. Conclusions Our analysis demonstrates that the classical similarity measurements can be improved with a generalizable model of similarity. The proposed approach has already been used to build similarity indices in two open-source software tools (CAESAR and VEGA) that make several QSAR models available. In these tools, the similarity index plays a key role for the assessment of the applicability domain. Chemical similarity (dpeaa)DE-He213 Read-across (dpeaa)DE-He213 Applicability domain (dpeaa)DE-He213 QSAR (dpeaa)DE-He213 Manganaro, Alberto aut Nicolotti, Orazio aut Medda, Ricardo aut Mangiatordi, Giuseppe Felice aut Benfenati, Emilio aut Enthalten in Journal of cheminformatics London : BioMed Central, 2009 6(2014), 1 vom: 18. Okt. (DE-627)594779219 (DE-600)2486539-4 1758-2946 nnns volume:6 year:2014 number:1 day:18 month:10 https://dx.doi.org/10.1186/s13321-014-0039-1 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2014 1 18 10
allfieldsGer	10.1186/s13321-014-0039-1 doi (DE-627)SPR031341055 (SPR)s13321-014-0039-1-e DE-627 ger DE-627 rakwb eng Floris, Matteo verfasserin aut A generalizable definition of chemical similarity for read-across 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Floris et al.; licensee Springer. 2014. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( Background Methods that provide a measure of chemical similarity are strongly relevant in several fields of chemoinformatics as they allow to predict the molecular behavior and fate of structurally close compounds. One common application of chemical similarity measurements, based on the principle that similar molecules have similar properties, is the read-across approach, where an estimation of a specific endpoint for a chemical is provided using experimental data available from highly similar compounds. Results This paper reports the comparison of multiple combinations of binary fingerprints and similarity metrics for computing the chemical similarity in the context of two different applications of the read-across technique. Conclusions Our analysis demonstrates that the classical similarity measurements can be improved with a generalizable model of similarity. The proposed approach has already been used to build similarity indices in two open-source software tools (CAESAR and VEGA) that make several QSAR models available. In these tools, the similarity index plays a key role for the assessment of the applicability domain. Chemical similarity (dpeaa)DE-He213 Read-across (dpeaa)DE-He213 Applicability domain (dpeaa)DE-He213 QSAR (dpeaa)DE-He213 Manganaro, Alberto aut Nicolotti, Orazio aut Medda, Ricardo aut Mangiatordi, Giuseppe Felice aut Benfenati, Emilio aut Enthalten in Journal of cheminformatics London : BioMed Central, 2009 6(2014), 1 vom: 18. Okt. (DE-627)594779219 (DE-600)2486539-4 1758-2946 nnns volume:6 year:2014 number:1 day:18 month:10 https://dx.doi.org/10.1186/s13321-014-0039-1 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2014 1 18 10
allfieldsSound	10.1186/s13321-014-0039-1 doi (DE-627)SPR031341055 (SPR)s13321-014-0039-1-e DE-627 ger DE-627 rakwb eng Floris, Matteo verfasserin aut A generalizable definition of chemical similarity for read-across 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Floris et al.; licensee Springer. 2014. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( Background Methods that provide a measure of chemical similarity are strongly relevant in several fields of chemoinformatics as they allow to predict the molecular behavior and fate of structurally close compounds. One common application of chemical similarity measurements, based on the principle that similar molecules have similar properties, is the read-across approach, where an estimation of a specific endpoint for a chemical is provided using experimental data available from highly similar compounds. Results This paper reports the comparison of multiple combinations of binary fingerprints and similarity metrics for computing the chemical similarity in the context of two different applications of the read-across technique. Conclusions Our analysis demonstrates that the classical similarity measurements can be improved with a generalizable model of similarity. The proposed approach has already been used to build similarity indices in two open-source software tools (CAESAR and VEGA) that make several QSAR models available. In these tools, the similarity index plays a key role for the assessment of the applicability domain. Chemical similarity (dpeaa)DE-He213 Read-across (dpeaa)DE-He213 Applicability domain (dpeaa)DE-He213 QSAR (dpeaa)DE-He213 Manganaro, Alberto aut Nicolotti, Orazio aut Medda, Ricardo aut Mangiatordi, Giuseppe Felice aut Benfenati, Emilio aut Enthalten in Journal of cheminformatics London : BioMed Central, 2009 6(2014), 1 vom: 18. Okt. (DE-627)594779219 (DE-600)2486539-4 1758-2946 nnns volume:6 year:2014 number:1 day:18 month:10 https://dx.doi.org/10.1186/s13321-014-0039-1 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2027 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2014 1 18 10
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This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Background Methods that provide a measure of chemical similarity are strongly relevant in several fields of chemoinformatics as they allow to predict the molecular behavior and fate of structurally close compounds. One common application of chemical similarity measurements, based on the principle that similar molecules have similar properties, is the read-across approach, where an estimation of a specific endpoint for a chemical is provided using experimental data available from highly similar compounds. Results This paper reports the comparison of multiple combinations of binary fingerprints and similarity metrics for computing the chemical similarity in the context of two different applications of the read-across technique. 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title_auth	A generalizable definition of chemical similarity for read-across
abstract	Background Methods that provide a measure of chemical similarity are strongly relevant in several fields of chemoinformatics as they allow to predict the molecular behavior and fate of structurally close compounds. One common application of chemical similarity measurements, based on the principle that similar molecules have similar properties, is the read-across approach, where an estimation of a specific endpoint for a chemical is provided using experimental data available from highly similar compounds. Results This paper reports the comparison of multiple combinations of binary fingerprints and similarity metrics for computing the chemical similarity in the context of two different applications of the read-across technique. Conclusions Our analysis demonstrates that the classical similarity measurements can be improved with a generalizable model of similarity. The proposed approach has already been used to build similarity indices in two open-source software tools (CAESAR and VEGA) that make several QSAR models available. In these tools, the similarity index plays a key role for the assessment of the applicability domain. © Floris et al.; licensee Springer. 2014. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (
abstractGer	Background Methods that provide a measure of chemical similarity are strongly relevant in several fields of chemoinformatics as they allow to predict the molecular behavior and fate of structurally close compounds. One common application of chemical similarity measurements, based on the principle that similar molecules have similar properties, is the read-across approach, where an estimation of a specific endpoint for a chemical is provided using experimental data available from highly similar compounds. Results This paper reports the comparison of multiple combinations of binary fingerprints and similarity metrics for computing the chemical similarity in the context of two different applications of the read-across technique. Conclusions Our analysis demonstrates that the classical similarity measurements can be improved with a generalizable model of similarity. The proposed approach has already been used to build similarity indices in two open-source software tools (CAESAR and VEGA) that make several QSAR models available. In these tools, the similarity index plays a key role for the assessment of the applicability domain. © Floris et al.; licensee Springer. 2014. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (
abstract_unstemmed	Background Methods that provide a measure of chemical similarity are strongly relevant in several fields of chemoinformatics as they allow to predict the molecular behavior and fate of structurally close compounds. One common application of chemical similarity measurements, based on the principle that similar molecules have similar properties, is the read-across approach, where an estimation of a specific endpoint for a chemical is provided using experimental data available from highly similar compounds. Results This paper reports the comparison of multiple combinations of binary fingerprints and similarity metrics for computing the chemical similarity in the context of two different applications of the read-across technique. Conclusions Our analysis demonstrates that the classical similarity measurements can be improved with a generalizable model of similarity. The proposed approach has already been used to build similarity indices in two open-source software tools (CAESAR and VEGA) that make several QSAR models available. In these tools, the similarity index plays a key role for the assessment of the applicability domain. © Floris et al.; licensee Springer. 2014. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (
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score	7.3979836

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A generalizable definition of chemical similarity for read-across

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