Drug3D-DTI: Improved drug-target interaction prediction by incorporating spatial information of small molecules

Zhirui Liao, Xiaodi Huang, Hiroshi Mamitsuka, Shanfeng Zhu

Research output: Book chapter/Published conference paperConference paperpeer-review

1 Citation (Scopus)

Abstract

A number of machine learning (ML) approaches for drug discovery have been available that rely only on sequential (1D) and planar (2D) information without effectively using the 3D information for generating features of drugs. However, 3D information of small molecules can reflect relative position of atoms more directly, which affects molecular properties. In this work, we present a new deep learning model called Drug3D-DTI for drug-target interaction prediction. Drug3D-DTI takes advantage of molecular spatial information, i.e., atom proximity in three-dimensional (3D) structures. We comprehensively evaluated the performance of Drug3D-DTI on two datasets with two tasks of regression and classification. In particular, we compared Drug3D-DTI with several existing methods including the two cutting-edge methods for compound-protein interaction prediction. From the experimental results, Drug3D-DTI clearly outperformed other methods under all settings. Further, this performance improvement was validated by ablation experiments and a case study. The implementation of Drug3D-DTI is available at (https://github.com/zhiruiliao/Drug3D-DTI).
Original languageEnglish
Title of host publicationProceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021
EditorsYufei Huang, Lukasz Kurgan, Feng Luo, Xiaohua Tony Hu, Yidong Chen, Edward Dougherty, Andrzej Kloczkowski, Yaohang Li
PublisherIEEE
Pages340-347
Number of pages8
ISBN (Electronic)9781665401265
ISBN (Print)9781665429825
DOIs
Publication statusPublished - 14 Jan 2022
EventIEEE International Conference on Bioinformatics and Biomedicine 2021: IEEE BIBM 2021 - Online
Duration: 09 Dec 202112 Dec 2021
https://ieeebibm.org/BIBM2021/
https://ieeebibm.org/BIBM2021/BIBM%202021%20Program%20-%20Dec%209.pdf (Program)
https://ieeexplore.ieee.org/xpl/conhome/9669261/proceeding (Proceedings)

Publication series

NameProceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021

Conference

ConferenceIEEE International Conference on Bioinformatics and Biomedicine 2021
Period09/12/2112/12/21
OtherThe IEEE International Conference on Bioinformatics and Biomedicine (BIBM) has established itself as the premier research conference in bioinformatics and biomedicine. IEEE BIBM 2021 provides a leading forum for disseminating the latest research in bioinformatics and health informatics. It brings together academic and industrial scientists from computer science, biology, chemistry, medicine, mathematics and statistics. We solicit high-quality original research papers (including significant work-in-progress) in any aspect of bioinformatics, genomics, and biomedicine. New computational techniques and methods and their application in life science and medical domains are especially encouraged.
Internet address

Fingerprint

Dive into the research topics of 'Drug3D-DTI: Improved drug-target interaction prediction by incorporating spatial information of small molecules'. Together they form a unique fingerprint.

Cite this