Predicting the molecular structure relationship and the biological activity of DPP-4 inhibitor using deep neural network with catboost method as feature selection

Haris Hamzah, Alhadi Bustamam, Arry Yanuar, Devvi Sarwinda

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Dipeptidyl peptidase 4 (DPP-4) are drug targets for type-2 diabetes mellitus (T2DM). The enzyme dipeptidyl peptidase 4 (DPP-4) can catalyze the decrease in the hormone incretin peptide, especially peptide-1, such as glucagon-like peptide-1 (GLP-1) and the hormone gastric inhibitory peptide (GIP), which results in decreased insulin synthesis. Inhibitors of DPP-4 are promising drug targets for T2DM because they are able to block the work of the DPP-4 enzyme by inhibiting the action of the hormones GLP-1 and GIP. Unfortunately, DPP-4 inhibitors have some adverse effects, such as nausea, headache, nasopharyngitis, and skin reactions. So, the medical field are still expecting new DPP-4 inhibitors with minimal effects. In this study, there are 1773 structures of DPP-4 inhibitors with 1185 active compounds and 588 inactive compounds extracted using topological fingerprints as descriptors. As there is a class imbalance in the dataset, there needs to be an oversampling technique applied, we have decided to use the SMOTE technique. The deep neural network (DNN) method is proposed as a method of classifying DPP-4 inhibitors and is optimized using Adam's optimizer and dropout regularization technique. In addition, we introduce CatBoost as a feature selection method. As a result, the DNN method combined with ECFP-6 and using feature selection with the proportion of the importance value of the feature at 90% produces the highest MCC value that is 0.810, and the sensitivity, specificity, and accuracy values being 0.927, 0.881, and 0.906, respectively.

Original languageEnglish
Title of host publication2020 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages101-108
Number of pages8
ISBN (Electronic)9781728192796
DOIs
Publication statusPublished - 17 Oct 2020
Event12th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2020 - Virtual, Depok, Indonesia
Duration: 17 Oct 202018 Oct 2020

Publication series

Name2020 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2020

Conference

Conference12th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2020
Country/TerritoryIndonesia
CityVirtual, Depok
Period17/10/2018/10/20

Keywords

  • Adam
  • CatBoost
  • Circular fingerprints
  • Deep neural network
  • Dipeptidyl peptidase-IV

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