TY - JOUR
T1 - Predicting drug resistance related to ABC transporters using unsupervised Consensus Self-Organizing Maps
AU - Estrada-Tejedor, Roger
AU - Ecker, Gerhard F.
N1 - Funding Information:
RET thankfully acknowledge the financial support of l’Obra Social “La Caixa”. GFE is grateful to the Austrian Science Fund for financial support provided under the framework of SFB35 (#F03502).
Publisher Copyright:
© 2018 The Author(s).
PY - 2018/12/1
Y1 - 2018/12/1
N2 - ATP binding cassette (ABC) transporters play a pivotal role in drug elimination, particularly on several types of cancer in which these proteins are overexpressed. Due to their promiscuous ligand recognition, building computational models for substrate classification is quite challenging. This study evaluates the use of modified Self-Organizing Maps (SOM) for predicting drug resistance associated with P-gp, MPR1 and BCRP activity. Herein, we present a novel multi-labelled unsupervised classification model which combines a new clustering algorithm with SOM. It significantly improves the accuracy of substrates classification, catching up with traditional supervised machine learning algorithms. Results can be applied to predict the pharmacological profile of new drug candidates during the drug development process.
AB - ATP binding cassette (ABC) transporters play a pivotal role in drug elimination, particularly on several types of cancer in which these proteins are overexpressed. Due to their promiscuous ligand recognition, building computational models for substrate classification is quite challenging. This study evaluates the use of modified Self-Organizing Maps (SOM) for predicting drug resistance associated with P-gp, MPR1 and BCRP activity. Herein, we present a novel multi-labelled unsupervised classification model which combines a new clustering algorithm with SOM. It significantly improves the accuracy of substrates classification, catching up with traditional supervised machine learning algorithms. Results can be applied to predict the pharmacological profile of new drug candidates during the drug development process.
KW - Multidrug-resistance
KW - Cancer
UR - http://www.scopus.com/inward/record.url?scp=85046374645&partnerID=8YFLogxK
UR - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=pure_univeritat_ramon_llull&SrcAuth=WosAPI&KeyUT=WOS:000431113100001&DestLinkType=FullRecord&DestApp=WOS_CPL
U2 - 10.1038/s41598-018-25235-9
DO - 10.1038/s41598-018-25235-9
M3 - Article
C2 - 29717183
AN - SCOPUS:85046374645
SN - 2045-2322
VL - 8
JO - Scientific Reports
JF - Scientific Reports
IS - 1
M1 - 6803
ER -
