Drug repurposing for COVID-19 using machine learning and mechanistic models of signal transduction circuits related to SARS-CoV-2 infection
| العنوان: | Drug repurposing for COVID-19 using machine learning and mechanistic models of signal transduction circuits related to SARS-CoV-2 infection |
|---|---|
| المؤلفون: | Marina Esteban-Medina, Carlos Loucera, Matias M. Falco, Joaquín Dopazo, Maria Peña-Chilet, Kinza Rian |
| المساهمون: | [Loucera,C, Esteban-Medina,M, Rian,K, Falco,MM, Dopazo,J, Peña-Chilet,M] Clinical Bioinformatics Area. Fundación Progreso y Salud (FPS). CDCA, Hospital Virgen del Rocio, Sevilla, Spain. [Loucera,C, Peña-Chilet,M] 2Computational Systems Medicine, Institute of Biomedicine of Seville (IBIS), Hospital Virgen del Rocio, Sevilla, Spain. [Falco,MM, Peña-Chilet,M] 3Bioinformatics in Rare Diseases (BiER). Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), FPS, Hospital Virgen del Rocío, Sevilla, Spain. [Dopazo,J]4Clinical Bioinformatics Area. Fundación Progreso y Salud (FPS). CDCA, Hospital Virgen del Rocio, Sevilla, Spain., This work is supported by grants SAF2017-88908-R from the Spanish Ministry of Economy and Competitiveness, PT17/0009/0006, ACCI2018/29 from CIBER-ISCIII and COV20/00788 from the ISCIII, co-funded with European Regional Development Funds (ERDF), the grant 'Large-scale drug repurposing in rare diseases by genomic Big Data analysis with machine learning methods' from the Fundación BBVA (G999088Q), as well as H2020 Programme of the European Union grants Marie Curie Innovative Training Network 'Machine Learning Frontiers in Precision Medicine' (MLFPM) (GA 813533)., Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), Instituto de Salud Carlos III, European Commission, Fundación BBVA |
| المصدر: | Signal Transduction and Targeted Therapy Signal Transduction and Targeted Therapy, Vol 5, Iss 1, Pp 1-3 (2020) Digital.CSIC. Repositorio Institucional del CSIC instname |
| سنة النشر: | 2020 |
| مصطلحات موضوعية: | Information Science::Information Science::Computing Methodologies::Computer Simulation::Molecular Docking Simulation [Medical Subject Headings], Cancer Research, Letter, Coronavirus disease 2019 (COVID-19), Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Química computacional, Big data, Predictive medicine, lcsh:Medicine, Reposicionamiento de medicamentos, Analytical, Diagnostic and Therapeutic Techniques and Equipment::Therapeutics::Drug Therapy::Molecular Targeted Therapy [Medical Subject Headings], Machine learning, computer.software_genre, Marie curie, Organisms::Eukaryota::Animals::Chordata::Vertebrates::Mammals::Primates::Haplorhini::Catarrhini::Hominidae::Humans [Medical Subject Headings], Machine Learning, Computational Chemistry, Simulación del acoplamiento molecular, Target identification, Genetics, media_common.cataloged_instance, Humans, Molecular Targeted Therapy, European union, lcsh:QH301-705.5, media_common, business.industry, SARS-CoV-2, lcsh:R, Drug Repositioning, Phenomena and Processes::Chemical Phenomena::Biochemical Phenomena::Biochemical Processes::Signal Transduction [Medical Subject Headings], COVID-19, Proteins, Chemicals and Drugs::Amino Acids, Peptides, and Proteins::Proteins [Medical Subject Headings], Precision medicine, Terapia molecular dirigida, Aprendizaje automático, Diseases::Virus Diseases::RNA Virus Infections::Nidovirales Infections::Coronaviridae Infections::Coronavirus Infections [Medical Subject Headings], COVID-19 Drug Treatment, Molecular Docking Simulation, Drug repositioning, lcsh:Biology (General), Infectious diseases, Christian ministry, Artificial intelligence, business, computer, Analytical, Diagnostic and Therapeutic Techniques and Equipment::Investigative Techniques::Drug Discovery::Drug Repositioning [Medical Subject Headings], Signal Transduction |
| الوصف: | Drug repurposing is a convenient alternative when the need for new drugs in an unexpected medical scenario is urgent, as is the case of emerging pathogens. In recent years, approaches based on network biology have demonstrated to be superior to genecentric ones.1 Here, we use an innovative methodology that combines mechanistic modeling of the signal transduction circuits related to SARS-CoV-2 infection (the COVID-19 disease map) with a machine-learning algorithm that learns potential causal interactions between proteins, already targets of drugs, and specific signaling circuits in the COVID-19 disease map, to suggest potentially repurposable drugs. This work is supported by grants SAF2017-88908-R from the Spanish Ministry of Economy and Competitiveness, PT17/0009/0006, ACCI2018/29 from CIBER-ISCIII and COV20/00788 from the ISCIII, co-funded with European Regional Development Funds (ERDF), the grant “Large-scale drug repurposing in rare diseases by genomic Big Data analysis with machine learning methods” from the Fundación BBVA (G999088Q), as well as H2020 Programme of the European Union grants Marie Curie Innovative Training Network “Machine Learning Frontiers in Precision Medicine” (MLFPM) (GA 813533). |
| وصف الملف: | application/pdf |
| اللغة: | English |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0ad6c62253a3ade149f0cc873a8bf936 https://www.nature.com/articles/s41392-020-00417-y.pdf |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....0ad6c62253a3ade149f0cc873a8bf936 |
| قاعدة البيانات: | OpenAIRE |
| الوصف غير متاح. |