Multi-label classification using deep belief networks for virtual screening of multi-target drug

Aries Fitriawan, Ito Wasito, Arida Ferti Syafiandini, Mukhlis Amien, Arry Yanuar

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

1 Citation (Scopus)

Abstract

Nowadays, the trend of drugs leads to multi-target drug. A drug compound may have one or more protein targets. Drugs that have multi-target protein considered to be more potential in the future. Virtual screening (VS) is a computational technique used in drug discovery to find the protein target of drugs. Virtual screening is usually based on compound similarity or database docking. Thus, the identification for multi-target drug compounds based on structure classification still remain as a challenging task The identification problem of multi-target protein from drug compounds can be categorized into multi-label classification problem. The purpose of this research is to find a new approach for multi-target drug virtual screening using machine learning technique. In this paper, the classification has been done by using combination of Deep Belief Networks (DBN) and Binary Relevance data transformation method. This research used two subset of protein target classes from DUD-E docking website. Feature were obtained from molecular fingerprint descriptor. The experiments result show that DBN can be used as virtual screening method for multi-target drug and outperform the DUD-E benchmarking.

Original languageEnglish
Title of host publicationProceeding - 2016 International Conference on Computer, Control, Informatics and its Applications
Subtitle of host publicationRecent Progress in Computer, Control, and Informatics for Data Science, IC3INA 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages102-107
Number of pages6
ISBN (Electronic)9781509023233
DOIs
Publication statusPublished - 23 Feb 2017
Event2016 International Conference on Computer, Control, Informatics and its Applications, IC3INA 2016 - Tangerang, Indonesia
Duration: 3 Oct 20165 Oct 2016

Publication series

NameProceeding - 2016 International Conference on Computer, Control, Informatics and its Applications: Recent Progress in Computer, Control, and Informatics for Data Science, IC3INA 2016

Conference

Conference2016 International Conference on Computer, Control, Informatics and its Applications, IC3INA 2016
CountryIndonesia
CityTangerang
Period3/10/165/10/16

Keywords

  • Deep Belief Networks
  • deep learning
  • drug design
  • multilabel classification
  • virtual screening

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