دورية أكاديمية
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Evidence for the druggability of aldosterone targets in heart failure: A bioinformatics and data science-driven decision-making approach.

التفاصيل البيبلوغرافية
العنوان: Evidence for the druggability of aldosterone targets in heart failure: A bioinformatics and data science-driven decision-making approach.
المؤلفون: Salgado Rezende de Mendonça L; Center of Innovation, Technology, and Education (CITE) at Anhembi Morumbi University, Anima Institute, Sao Jose dos Campos Technology Park, Sao Jose dos Campos, Brazil., Senar S; DrTarget, 28806 Madrid, Spain(1)., Moreira LL; Center of Innovation, Technology, and Education (CITE) at Anhembi Morumbi University, Anima Institute, Sao Jose dos Campos Technology Park, Sao Jose dos Campos, Brazil., Silva Júnior JA; Universidade Nove de Julho (UNINOVE), Sao Paulo, Brazil., Nader M; College of Medicine & Health Sciences, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates., Campos LA; Center of Innovation, Technology, and Education (CITE) at Anhembi Morumbi University, Anima Institute, Sao Jose dos Campos Technology Park, Sao Jose dos Campos, Brazil. Electronic address: camposbaltatu@gmail.com., Baltatu OC; Center of Innovation, Technology, and Education (CITE) at Anhembi Morumbi University, Anima Institute, Sao Jose dos Campos Technology Park, Sao Jose dos Campos, Brazil. Electronic address: ocbaltatu@gmail.com.
المصدر: Computers in biology and medicine [Comput Biol Med] 2024 Mar; Vol. 171, pp. 108124. Date of Electronic Publication: 2024 Feb 13.
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: Elsevier Country of Publication: United States NLM ID: 1250250 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-0534 (Electronic) Linking ISSN: 00104825 NLM ISO Abbreviation: Comput Biol Med Subsets: MEDLINE
أسماء مطبوعة: Publication: New York : Elsevier
Original Publication: New York, Pergamon Press.
مواضيع طبية MeSH: Aldosterone* , Heart Failure*/drug therapy, Humans ; Data Science ; Heart ; Enzyme Inhibitors ; Cardiotonic Agents ; Computational Biology
مستخلص: Background: Aldosterone plays a key role in the neurohormonal drive of heart failure. Systematic prioritization of drug targets using bioinformatics and database-driven decision-making can provide a competitive advantage in therapeutic R&D. This study investigated the evidence on the druggability of these aldosterone targets in heart failure.
Methods: The target disease predictability of mineralocorticoid receptors (MR) and aldosterone synthase (AS) in cardiac failure was evaluated using Open Targets target-disease association scores. The Open Targets database collections were downloaded to MongoDB and queried according to the desired aggregation level, and the results were retrieved from the Europe PMC (data type: text mining), ChEMBL (data type: drugs), Open Targets Genetics Portal (data type: genetic associations), and IMPC (data type: genetic associations) databases. The target tractability of MR and AS in the cardiovascular system was investigated by computing activity scores in a curated ChEMBL database using supervised machine learning.
Results: The medians of the association scores of the MR and AS groups were similar, indicating a comparable predictability of the target disease. The median of the MR activity scores group was significantly lower than that of AS, indicating that AS has higher target tractability than MR [Hodges-Lehmann difference 0.62 (95%CI 0.53-0.70, p < 0.0001]. The cumulative distributions of the overall multiplatform association scores of cardiac diseases with MR were considerably higher than with AS, indicating more advanced investigations on a wider range of disorders evaluated for MR (Kolmogorov-Smirnov D = 0.36, p = 0.0009). In curated ChEMBL, MR had a higher cumulative distribution of activity scores in experimental cardiovascular assays than AS (Kolmogorov-Smirnov D = 0.23, p < 0.0001). Documented clinical trials for MR in heart failures surfaced in database searches, none for AS.
Conclusions: Although its clinical development has lagged behind that of MR, our findings indicate that AS is a promising therapeutic target for the treatment of cardiac failure. The multiplatform-integrated identification used in this study allowed us to comprehensively explore the available scientific evidence on MR and AS for heart failure therapy.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024 Elsevier Ltd. All rights reserved.)
فهرسة مساهمة: Keywords: Aldosterone; CYP11B2; Databases; Heart failure; Machine learning; NR3C2; Open access platforms
المشرفين على المادة: 4964P6T9RB (Aldosterone)
0 (Enzyme Inhibitors)
0 (Cardiotonic Agents)
تواريخ الأحداث: Date Created: 20240227 Date Completed: 20240321 Latest Revision: 20240321
رمز التحديث: 20240321
DOI: 10.1016/j.compbiomed.2024.108124
PMID: 38412691
قاعدة البيانات: MEDLINE
الوصف
تدمد:1879-0534
DOI:10.1016/j.compbiomed.2024.108124