Molecular de-extinction is an innovative science aiming to discover, synthesize, and characterize molecules throughout evolution. Recent work by Ferreira et al. involved mining ancient genomes to search for antimicrobial defensins. They discovered six ancient β-defensins, revealing their evolutionary history and uncovering their structural and biochemical properties, which could feed medical applications.
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Journey to the past: molecular de-extinction enables the discovery of ancient β-defensins and highlights their evolutionary history.
Trends Biochem Sci
December 2024
IPSiM, CNRS, INRAE, Institut Agro, Univ. Montpellier, 2, Place P. Viala, F-34 060 Cedex 2 Montpellier, France. Electronic address:
Molecular de-extinction is an innovative science aiming to discover, synthesize, and characterize molecules throughout evolution. Recent work by Ferreira et al. involved mining ancient genomes to search for antimicrobial defensins.
View Article and Find Full Text PDFThe patentability and bioethics of molecular de-extinction.
Nat Biotechnol
August 2024
Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Catastrophic selection: the other side of the coin.
Ann Med
December 2024
SaBio, Instituto de Investigación en Recursos Cinegéticos (IREC), Consejo Superior de Investigaciones Científicas (CSIC), Universidad de Castilla-La Mancha (UCLM)-Junta de Comunidades de Castilla-La Mancha (JCCM), Ciudad Real, Spain.
Recently, a machine learning molecular de-extinction paleoproteomic approach was used to recover inactivated antimicrobial peptides to overcome the challenges posed by antibiotic-resistant pathogens. The authors showed the possibility of identifying lost molecules with antibacterial capacity, but the other side of the coin associated with catastrophic selection should be considered for the development of new pharmaceuticals.
View Article and Find Full Text PDFDeep-learning-enabled antibiotic discovery through molecular de-extinction.
Nat Biomed Eng
July 2024
Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Molecular de-extinction aims at resurrecting molecules to solve antibiotic resistance and other present-day biological and biomedical problems. Here we show that deep learning can be used to mine the proteomes of all available extinct organisms for the discovery of antibiotic peptides. We trained ensembles of deep-learning models consisting of a peptide-sequence encoder coupled with neural networks for the prediction of antimicrobial activity and used it to mine 10,311,899 peptides.
View Article and Find Full Text PDFMolecular de-extinction of ancient antimicrobial peptides enabled by machine learning.
Cell Host Microbe
August 2023
Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Bioengineering, Department of Chemical and Biomolecular Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA; Penn Institute for Computational Science, University of Pennsylvania, Philadelphia, PA 19104, USA. Electronic address:
Molecular de-extinction could offer avenues for drug discovery by reintroducing bioactive molecules that are no longer encoded by extant organisms. To prospect for antimicrobial peptides encrypted within extinct and extant human proteins, we introduce the panCleave random forest model for proteome-wide cleavage site prediction. Our model outperformed multiple protease-specific cleavage site classifiers for three modern human caspases, despite its pan-protease design.
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