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Article

Discovery through Machine Learning and Preclinical Validation of Novel Anti-Diabetic Peptides

Nuritas Ltd., Joshua Dawson House, D02 RY95 Dublin, Ireland
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Academic Editor: Jean A. Boutin
Biomedicines 2021, 9(3), 276; https://doi.org/10.3390/biomedicines9030276
Received: 4 February 2021 / Revised: 5 March 2021 / Accepted: 7 March 2021 / Published: 9 March 2021
(This article belongs to the Special Issue Recent Advances in the Discovery of Novel Drugs on Natural Molecules)
While there have been significant advances in drug discovery for diabetes mellitus over the past couple of decades, there is an opportunity and need for improved therapies. While type 2 diabetic patients better manage their illness, many of the therapeutics in this area are peptide hormones with lengthy sequences and a molecular structure that makes them challenging and expensive to produce. Using machine learning, we present novel anti-diabetic peptides which are less than 16 amino acids in length, distinct from human signalling peptides. We validate the capacity of these peptides to stimulate glucose uptake and Glucose transporter type 4 (GLUT4) translocation in vitro. In obese insulin-resistant mice, predicted peptides significantly lower plasma glucose, reduce glycated haemoglobin and even improve hepatic steatosis when compared to treatments currently in use in a clinical setting. These unoptimised, linear peptides represent promising candidates for blood glucose regulation which require further evaluation. Further, this indicates that perhaps we have overlooked the class of natural short linear peptides, which usually come with an excellent safety profile, as therapeutic modalities. View Full-Text
Keywords: drug discovery; peptide; type 2 diabetes; machine learning drug discovery; peptide; type 2 diabetes; machine learning
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MDPI and ACS Style

Casey, R.; Adelfio, A.; Connolly, M.; Wall, A.; Holyer, I.; Khaldi, N. Discovery through Machine Learning and Preclinical Validation of Novel Anti-Diabetic Peptides. Biomedicines 2021, 9, 276. https://doi.org/10.3390/biomedicines9030276

AMA Style

Casey R, Adelfio A, Connolly M, Wall A, Holyer I, Khaldi N. Discovery through Machine Learning and Preclinical Validation of Novel Anti-Diabetic Peptides. Biomedicines. 2021; 9(3):276. https://doi.org/10.3390/biomedicines9030276

Chicago/Turabian Style

Casey, Rory, Alessandro Adelfio, Martin Connolly, Audrey Wall, Ian Holyer, and Nora Khaldi. 2021. "Discovery through Machine Learning and Preclinical Validation of Novel Anti-Diabetic Peptides" Biomedicines 9, no. 3: 276. https://doi.org/10.3390/biomedicines9030276

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