1
|
Ayuso-Muñoz A, Prieto-Santamaría L, Ugarte-Carro E, Serrano E, Rodríguez-González A. Uncovering hidden therapeutic indications through drug repurposing with graph neural networks and heterogeneous data. Artif Intell Med 2023; 145:102687. [PMID: 37925215 DOI: 10.1016/j.artmed.2023.102687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 10/04/2023] [Accepted: 10/13/2023] [Indexed: 11/06/2023]
Abstract
Drug repurposing has gained the attention of many in the recent years. The practice of repurposing existing drugs for new therapeutic uses helps to simplify the drug discovery process, which in turn reduces the costs and risks that are associated with de novo development. Representing biomedical data in the form of a graph is a simple and effective method to depict the underlying structure of the information. Using deep neural networks in combination with this data represents a promising approach to address drug repurposing. This paper presents BEHOR a more comprehensive version of the REDIRECTION model, which was previously presented. Both versions utilize the DISNET biomedical graph as the primary source of information, providing the model with extensive and intricate data to tackle the drug repurposing challenge. This new version's results for the reported metrics in the RepoDB test are 0.9604 for AUROC and 0.9518 for AUPRC. Additionally, a discussion is provided regarding some of the novel predictions to demonstrate the reliability of the model. The authors believe that BEHOR holds promise for generating drug repurposing hypotheses and could greatly benefit the field.
Collapse
Affiliation(s)
- Adrián Ayuso-Muñoz
- ETS Ingenieros Informáticos, Universidad Politécnica de Madrid, 28660 Boadilla del Monte, Madrid, Spain; Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, 28223 Pozuelo de Alarcón, Madrid, Spain.
| | - Lucía Prieto-Santamaría
- ETS Ingenieros Informáticos, Universidad Politécnica de Madrid, 28660 Boadilla del Monte, Madrid, Spain; Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, 28223 Pozuelo de Alarcón, Madrid, Spain.
| | - Esther Ugarte-Carro
- ETS Ingenieros Informáticos, Universidad Politécnica de Madrid, 28660 Boadilla del Monte, Madrid, Spain; Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, 28223 Pozuelo de Alarcón, Madrid, Spain.
| | - Emilio Serrano
- ETS Ingenieros Informáticos, Universidad Politécnica de Madrid, 28660 Boadilla del Monte, Madrid, Spain.
| | - Alejandro Rodríguez-González
- ETS Ingenieros Informáticos, Universidad Politécnica de Madrid, 28660 Boadilla del Monte, Madrid, Spain; Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, 28223 Pozuelo de Alarcón, Madrid, Spain.
| |
Collapse
|
2
|
Prieto Santamaría L, Ugarte Carro E, Díaz Uzquiano M, Menasalvas Ruiz E, Pérez Gallardo Y, Rodríguez-González A. A data-driven methodology towards evaluating the potential of drug repurposing hypotheses. Comput Struct Biotechnol J 2021; 19:4559-4573. [PMID: 34471499 PMCID: PMC8387760 DOI: 10.1016/j.csbj.2021.08.003] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Revised: 07/08/2021] [Accepted: 08/03/2021] [Indexed: 12/14/2022] Open
Abstract
Drug repurposing has become a widely used strategy to accelerate the process of finding treatments. While classical de novo drug development involves high costs, risks, and time-consuming paths, drug repurposing allows to reuse already-existing and approved drugs for new indications. Numerous research has been carried out in this field, both in vitro and in silico. Computational drug repurposing methods make use of modern heterogeneous biomedical data to identify and prioritize new indications for old drugs. In the current paper, we present a new complete methodology to evaluate new potentially repurposable drugs based on disease-gene and disease-phenotype associations, identifying significant differences between repurposing and non-repurposing data. We have collected a set of known successful drug repurposing case studies from the literature and we have analysed their dissimilarities with other biomedical data not necessarily participating in repurposing processes. The information used has been obtained from the DISNET platform. We have performed three analyses (at the genetical, phenotypical, and categorization levels), to conclude that there is a statistically significant difference between actual repurposing-related information and non-repurposing data. The insights obtained could be relevant when suggesting new potential drug repurposing hypotheses.
Collapse
Key Words
- ACE, Angiotensin I Converting Enzyme
- AHR, Aryl Hydrocarbon Receptor
- ALK, Anaplastic Lymphoma Kinase
- API, Application Programming Interface
- CMap, Connectivity Map
- COX-2, Cyclooxygenase 2
- CUI, Concept Unique Identifier
- DISNET knowledge base
- DR, Drug Repurposing or Drug Repositioning
- DRD3, Dopamine Receptor D3
- Data integration
- Disease understanding
- Drug repositioning
- Drug repurposing
- Drug-disease validation
- ESR1, Estrogen Receptor 1
- ESR2, Estrogen Receptor 2
- FCGR2A, Fc Fragment Of IgG Receptor IIa
- FCGR3A, Fc Fragment Of IgG Receptor IIIa
- FCGR3B, Fc Fragment Of IgG Receptor IIIb
- GDA, Gene Disease Association
- ICD-10-CM, International Classification of Diseases, 10th revision, Clinical Modification
- ID, Identifier
- KDR, Kinase insert Domain Receptor
- LTα, Lymphotoxin alpha
- MeSH-PA, Medical Subject Headings – Pharmacological Action
- ND, New Disease
- NLM, National Library of Medicine
- OD, Original Disease
- PTGS2, Prostaglandin-endoperoxidase synthase 2
- SM, Supplementary Material
- SRD5A1, Steroid 5 Alpha-Reductase 1
- SRD5A2, Steroid 5 Alpha-Reductase 2
- TNFα, Tumour Necrosis Factor alpha
- UMLS, Unified Medical Language System
Collapse
Affiliation(s)
- Lucía Prieto Santamaría
- Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, 28660 Boadilla del Monte, Madrid, Spain.,ETS Ingenieros Informáticos, Universidad Politécnica de Madrid, 28660 Boadilla del Monte, Madrid, Spain.,Ezeris Networks Global Services S.L., 28028 Madrid, Spain
| | - Esther Ugarte Carro
- Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, 28660 Boadilla del Monte, Madrid, Spain
| | - Marina Díaz Uzquiano
- Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, 28660 Boadilla del Monte, Madrid, Spain
| | - Ernestina Menasalvas Ruiz
- Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, 28660 Boadilla del Monte, Madrid, Spain.,ETS Ingenieros Informáticos, Universidad Politécnica de Madrid, 28660 Boadilla del Monte, Madrid, Spain
| | | | - Alejandro Rodríguez-González
- Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, 28660 Boadilla del Monte, Madrid, Spain.,ETS Ingenieros Informáticos, Universidad Politécnica de Madrid, 28660 Boadilla del Monte, Madrid, Spain
| |
Collapse
|