Exploring QSAR models for activity-cliff prediction

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Bibliographic Details
Main Authors: Markus, Dablander, Thierry, Hanser, Renaud, Lambiotte
Format: Book
Language:English
Published: Springer 2023
Subjects:
ACs
Online Access:https://link.springer.com/article/10.1186/s13321-023-00708-w
https://dlib.phenikaa-uni.edu.vn/handle/PNK/8224
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spelling oai:localhost:PNK-82242023-04-21T08:51:03Z Exploring QSAR models for activity-cliff prediction Markus, Dablander Thierry, Hanser Renaud, Lambiotte ACs QSAR models CC BY Pairs of similar compounds that only differ by a small structural modification but exhibit a large difference in their binding affinity for a given target are known as activity cliffs (ACs). It has been hypothesised that QSAR models struggle to predict ACs and that ACs thus form a major source of prediction error. However, the AC-prediction power of modern QSAR methods and its quantitative relationship to general QSAR-prediction performance is still underexplored. We systematically construct nine distinct QSAR models by combining three molecular representation methods (extended-connectivity fingerprints, physicochemical-descriptor vectors and graph isomorphism networks) with three regression techniques (random forests, k-nearest neighbours and multilayer perceptrons); we then use each resulting model to classify pairs of similar compounds as ACs or non-ACs and to predict the activities of individual molecules in three case studies: dopamine receptor D2, factor Xa, and SARS-CoV-2 main protease. 2023-04-21T08:51:03Z 2023-04-21T08:51:03Z 2023 Book https://link.springer.com/article/10.1186/s13321-023-00708-w https://dlib.phenikaa-uni.edu.vn/handle/PNK/8224 en application/pdf Springer
institution Digital Phenikaa
collection Digital Phenikaa
language English
topic ACs
QSAR models
spellingShingle ACs
QSAR models
Markus, Dablander
Thierry, Hanser
Renaud, Lambiotte
Exploring QSAR models for activity-cliff prediction
description CC BY
format Book
author Markus, Dablander
Thierry, Hanser
Renaud, Lambiotte
author_facet Markus, Dablander
Thierry, Hanser
Renaud, Lambiotte
author_sort Markus, Dablander
title Exploring QSAR models for activity-cliff prediction
title_short Exploring QSAR models for activity-cliff prediction
title_full Exploring QSAR models for activity-cliff prediction
title_fullStr Exploring QSAR models for activity-cliff prediction
title_full_unstemmed Exploring QSAR models for activity-cliff prediction
title_sort exploring qsar models for activity-cliff prediction
publisher Springer
publishDate 2023
url https://link.springer.com/article/10.1186/s13321-023-00708-w
https://dlib.phenikaa-uni.edu.vn/handle/PNK/8224
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score 8.891053