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Follow-up: Prospective compound design using the ‘SAR Matrix’ method and matrix-derived conditional probabilities of activity

In a previous Method Article, we have presented the ‘Structure-Activity Relationship (SAR) Matrix’ (SARM) approach. The SARM methodology is designed to systematically extract structurally related compound series from screening or chemical optimization data and organize these series and associated SA...

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Autores principales: Gupta-Ostermann, Disha, Hirose, Yoichiro, Odagami, Takenao, Kouji, Hiroyuki, Bajorath, Jürgen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000Research 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4406192/
https://www.ncbi.nlm.nih.gov/pubmed/25949808
http://dx.doi.org/10.12688/f1000research.6271.2
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author Gupta-Ostermann, Disha
Hirose, Yoichiro
Odagami, Takenao
Kouji, Hiroyuki
Bajorath, Jürgen
author_facet Gupta-Ostermann, Disha
Hirose, Yoichiro
Odagami, Takenao
Kouji, Hiroyuki
Bajorath, Jürgen
author_sort Gupta-Ostermann, Disha
collection PubMed
description In a previous Method Article, we have presented the ‘Structure-Activity Relationship (SAR) Matrix’ (SARM) approach. The SARM methodology is designed to systematically extract structurally related compound series from screening or chemical optimization data and organize these series and associated SAR information in matrices reminiscent of R-group tables. SARM calculations also yield many virtual candidate compounds that form a “chemical space envelope” around related series. To further extend the SARM approach, different methods are developed to predict the activity of virtual compounds. In this follow-up contribution, we describe an activity prediction method that derives conditional probabilities of activity from SARMs and report representative results of first prospective applications of this approach.
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spelling pubmed-44061922015-05-05 Follow-up: Prospective compound design using the ‘SAR Matrix’ method and matrix-derived conditional probabilities of activity Gupta-Ostermann, Disha Hirose, Yoichiro Odagami, Takenao Kouji, Hiroyuki Bajorath, Jürgen F1000Res Method Article In a previous Method Article, we have presented the ‘Structure-Activity Relationship (SAR) Matrix’ (SARM) approach. The SARM methodology is designed to systematically extract structurally related compound series from screening or chemical optimization data and organize these series and associated SAR information in matrices reminiscent of R-group tables. SARM calculations also yield many virtual candidate compounds that form a “chemical space envelope” around related series. To further extend the SARM approach, different methods are developed to predict the activity of virtual compounds. In this follow-up contribution, we describe an activity prediction method that derives conditional probabilities of activity from SARMs and report representative results of first prospective applications of this approach. F1000Research 2015-04-15 /pmc/articles/PMC4406192/ /pubmed/25949808 http://dx.doi.org/10.12688/f1000research.6271.2 Text en Copyright: © 2015 Gupta-Ostermann D et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. http://creativecommons.org/publicdomain/zero/1.0/ Data associated with the article are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication).
spellingShingle Method Article
Gupta-Ostermann, Disha
Hirose, Yoichiro
Odagami, Takenao
Kouji, Hiroyuki
Bajorath, Jürgen
Follow-up: Prospective compound design using the ‘SAR Matrix’ method and matrix-derived conditional probabilities of activity
title Follow-up: Prospective compound design using the ‘SAR Matrix’ method and matrix-derived conditional probabilities of activity
title_full Follow-up: Prospective compound design using the ‘SAR Matrix’ method and matrix-derived conditional probabilities of activity
title_fullStr Follow-up: Prospective compound design using the ‘SAR Matrix’ method and matrix-derived conditional probabilities of activity
title_full_unstemmed Follow-up: Prospective compound design using the ‘SAR Matrix’ method and matrix-derived conditional probabilities of activity
title_short Follow-up: Prospective compound design using the ‘SAR Matrix’ method and matrix-derived conditional probabilities of activity
title_sort follow-up: prospective compound design using the ‘sar matrix’ method and matrix-derived conditional probabilities of activity
topic Method Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4406192/
https://www.ncbi.nlm.nih.gov/pubmed/25949808
http://dx.doi.org/10.12688/f1000research.6271.2
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