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Rationalizing the Formation of Activity Cliffs in Different Compound Data Sets
[Image: see text] Activity cliffs are formed by structurally analogous compounds with large potency variations and are highly relevant for the exploration of discontinuous structure–activity relationships and compound optimization. So far, activity cliffs have mostly been studied on a case-by-case b...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2018
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6644420/ https://www.ncbi.nlm.nih.gov/pubmed/31458921 http://dx.doi.org/10.1021/acsomega.8b01188 |
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author | Hu, Huabin Stumpfe, Dagmar Bajorath, Jürgen |
author_facet | Hu, Huabin Stumpfe, Dagmar Bajorath, Jürgen |
author_sort | Hu, Huabin |
collection | PubMed |
description | [Image: see text] Activity cliffs are formed by structurally analogous compounds with large potency variations and are highly relevant for the exploration of discontinuous structure–activity relationships and compound optimization. So far, activity cliffs have mostly been studied on a case-by-case basis or assessed by global statistical analysis. Different from previous investigations, we report a large-scale analysis of activity cliff formation with a strong focus on individual compound activity classes (target sets). Compound potency distributions were systematically analyzed and categorized, and structural relationships were dissected and visualized on a per-set basis. Our study uncovered target set-dependent interplay of potency distributions and structural relationships and revealed the presence of activity cliffs and origins of cliff formation in different structure–activity relationship environments. |
format | Online Article Text |
id | pubmed-6644420 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-66444202019-08-27 Rationalizing the Formation of Activity Cliffs in Different Compound Data Sets Hu, Huabin Stumpfe, Dagmar Bajorath, Jürgen ACS Omega [Image: see text] Activity cliffs are formed by structurally analogous compounds with large potency variations and are highly relevant for the exploration of discontinuous structure–activity relationships and compound optimization. So far, activity cliffs have mostly been studied on a case-by-case basis or assessed by global statistical analysis. Different from previous investigations, we report a large-scale analysis of activity cliff formation with a strong focus on individual compound activity classes (target sets). Compound potency distributions were systematically analyzed and categorized, and structural relationships were dissected and visualized on a per-set basis. Our study uncovered target set-dependent interplay of potency distributions and structural relationships and revealed the presence of activity cliffs and origins of cliff formation in different structure–activity relationship environments. American Chemical Society 2018-07-11 /pmc/articles/PMC6644420/ /pubmed/31458921 http://dx.doi.org/10.1021/acsomega.8b01188 Text en Copyright © 2018 American Chemical Society This is an open access article published under an ACS AuthorChoice License (http://pubs.acs.org/page/policy/authorchoice_termsofuse.html) , which permits copying and redistribution of the article or any adaptations for non-commercial purposes. |
spellingShingle | Hu, Huabin Stumpfe, Dagmar Bajorath, Jürgen Rationalizing the Formation of Activity Cliffs in Different Compound Data Sets |
title | Rationalizing the Formation of Activity Cliffs in
Different Compound Data Sets |
title_full | Rationalizing the Formation of Activity Cliffs in
Different Compound Data Sets |
title_fullStr | Rationalizing the Formation of Activity Cliffs in
Different Compound Data Sets |
title_full_unstemmed | Rationalizing the Formation of Activity Cliffs in
Different Compound Data Sets |
title_short | Rationalizing the Formation of Activity Cliffs in
Different Compound Data Sets |
title_sort | rationalizing the formation of activity cliffs in
different compound data sets |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6644420/ https://www.ncbi.nlm.nih.gov/pubmed/31458921 http://dx.doi.org/10.1021/acsomega.8b01188 |
work_keys_str_mv | AT huhuabin rationalizingtheformationofactivitycliffsindifferentcompounddatasets AT stumpfedagmar rationalizingtheformationofactivitycliffsindifferentcompounddatasets AT bajorathjurgen rationalizingtheformationofactivitycliffsindifferentcompounddatasets |