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Open AccessArticle

Development of Multi-Target Chemometric Models for the Inhibition of Class I PI3K Enzyme Isoforms: A Case Study Using QSAR-Co Tool

Department of Chemistry and Biochemistry, University of Porto, 4169-007 Porto, Portugal
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Int. J. Mol. Sci. 2019, 20(17), 4191; https://doi.org/10.3390/ijms20174191
Received: 14 July 2019 / Revised: 23 August 2019 / Accepted: 24 August 2019 / Published: 27 August 2019
(This article belongs to the Special Issue QSAR and Chemoinformatics Tools for Modeling)
The present work aims at establishing multi-target chemometric models using the recently launched quantitative structure–activity relationship (QSAR)-Co tool for predicting the activity of inhibitor compounds against different isoforms of phosphoinositide 3-kinase (PI3K) under various experimental conditions. The inhibitors of class I phosphoinositide 3-kinase (PI3K) isoforms have emerged as potential therapeutic agents for the treatment of various disorders, especially cancer. The cell-based enzyme inhibition assay results of PI3K inhibitors were curated from the CHEMBL database. Factors such as the nature and mutation of cell lines that may significantly alter the assay outcomes were considered as important experimental elements for mt-QSAR model development. The models, in turn, were developed using two machine learning techniques as implemented in QSAR-Co: linear discriminant analysis (LDA) and random forest (RF). Both techniques led to models with high accuracy (ca. 90%). Several molecular fragments were extracted from the current dataset, and their quantitative contributions to the inhibitory activity against all the proteins and experimental conditions under study were calculated. This case study also demonstrates the utility of QSAR-Co tool in solving multi-factorial and complex chemometric problems. Additionally, the combination of different in silico methods employed in this work can serve as a valuable guideline to speed up early discovery of PI3K inhibitors. View Full-Text
Keywords: PI3K inhibitors; cancer; QSAR; multi-target models; linear discriminant analysis; random forest PI3K inhibitors; cancer; QSAR; multi-target models; linear discriminant analysis; random forest
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Halder, A.K.; Cordeiro, M.N.D.S. Development of Multi-Target Chemometric Models for the Inhibition of Class I PI3K Enzyme Isoforms: A Case Study Using QSAR-Co Tool. Int. J. Mol. Sci. 2019, 20, 4191.

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