Title:
METHOD, DEVICE, AND COMPUTER PROGRAM FOR PREDICTING INTERACTION BETWEEN COMPOUND AND PROTEIN
Document Type and Number:
WIPO Patent Application WO/2022/124725
Kind Code:
A1
Abstract:
A method, a device, and a computer program for predicting the interaction between a compound and a protein are provided. A method for predicting the interaction between a compound and a protein, according to some embodiments of the present disclosure, may comprise the steps of: acquiring compound data for training, protein data for training, and training data including interaction scores; constructing a deep-learning model by using the acquired training data; and predicting the interaction between the given compound and protein by using the constructed deep-learning model. The interaction between the given compound and protein in the in vivo environment can be accurately predicted by training the deep-learning model, while excludeing, from an amino acid sequence of the protein for training, amino acid sequences associated with a protein domain having a negative influence on the interaction.
Inventors:
CHOI JIN WOO (KR)
KIM YI RANG (KR)
KIM YI RANG (KR)
Application Number:
PCT/KR2021/018331
Publication Date:
June 16, 2022
Filing Date:
December 06, 2021
Export Citation:
Assignee:
ONCOCROSS CO LTD (KR)
International Classes:
G16C20/70; G06N3/08; G06N20/00; G16B30/10; G16B40/00; G16C20/30
Foreign References:
| KR102299220B1 | 2021-09-07 |
Other References:
SANGMIN SEO, JAEGYOON AHN: "Prediction of Compound-Protein Interactions Using Deep Learning", JOURNAL OF KIISE, vol. 46, no. 10, 1 October 2019 (2019-10-01), KR , pages 1054 - 1060, XP009528856, ISSN: 2383-630X, DOI: 10.5626/JOK.2019.46.10.1054
HAKIME ÖZTÜRK; ELIF OZKIRIMLI; ARZUCAN ÖZGÜR: "WideDTA: prediction of drug-target binding affinity", ARXIV.ORG, 4 February 2019 (2019-02-04), 201 Olin Library Cornell University Ithaca, NY 14853 , pages 1 - 11, XP081027957
CHEN LIFAN, TAN XIAOQIN, WANG DINGYAN, ZHONG FEISHENG, LIU XIAOHONG, YANG TIANBIAO, LUO XIAOMIN, CHEN KAIXIAN, JIANG HUALIANG, ZHE: "TransformerCPI: improving compound–protein interaction prediction by sequence-based deep learning with self-attention mechanism and label reversal experiments", BIOINFORMATICS, vol. 36, no. 16, 15 August 2020 (2020-08-15), GB , pages 4406 - 4414, XP055941575, ISSN: 1367-4803, DOI: 10.1093/bioinformatics/btaa524
TSUBAKI MASASHI, TOMII KENTARO, SESE JUN: "Compound-protein interaction prediction with end-to-end learning of neural networks for graphs and sequences", BIOINFORMATICS, OXFORD UNIVERSITY PRESS , SURREY, GB, vol. 35, no. 2, 15 January 2019 (2019-01-15), GB , pages 309 - 318, XP055826403, ISSN: 1367-4803, DOI: 10.1093/bioinformatics/bty535
ZHENG SHUANGJIA, LI YONGJIAN, CHEN SHENG, XU JUN, YANG YUEDONG: "Predicting drug protein interaction using quasi-visual question answering system", BIORXIV, 25 March 2019 (2019-03-25), pages 1 - 7, XP055826404, DOI: 10.1101/588178
HAKIME ÖZTÜRK; ELIF OZKIRIMLI; ARZUCAN ÖZGÜR: "WideDTA: prediction of drug-target binding affinity", ARXIV.ORG, 4 February 2019 (2019-02-04), 201 Olin Library Cornell University Ithaca, NY 14853 , pages 1 - 11, XP081027957
CHEN LIFAN, TAN XIAOQIN, WANG DINGYAN, ZHONG FEISHENG, LIU XIAOHONG, YANG TIANBIAO, LUO XIAOMIN, CHEN KAIXIAN, JIANG HUALIANG, ZHE: "TransformerCPI: improving compound–protein interaction prediction by sequence-based deep learning with self-attention mechanism and label reversal experiments", BIOINFORMATICS, vol. 36, no. 16, 15 August 2020 (2020-08-15), GB , pages 4406 - 4414, XP055941575, ISSN: 1367-4803, DOI: 10.1093/bioinformatics/btaa524
TSUBAKI MASASHI, TOMII KENTARO, SESE JUN: "Compound-protein interaction prediction with end-to-end learning of neural networks for graphs and sequences", BIOINFORMATICS, OXFORD UNIVERSITY PRESS , SURREY, GB, vol. 35, no. 2, 15 January 2019 (2019-01-15), GB , pages 309 - 318, XP055826403, ISSN: 1367-4803, DOI: 10.1093/bioinformatics/bty535
ZHENG SHUANGJIA, LI YONGJIAN, CHEN SHENG, XU JUN, YANG YUEDONG: "Predicting drug protein interaction using quasi-visual question answering system", BIORXIV, 25 March 2019 (2019-03-25), pages 1 - 7, XP055826404, DOI: 10.1101/588178
Attorney, Agent or Firm:
LIM, Hyung Chul et al. (KR)
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