A Deep Learning Approach to Antibiotic Discovery
Jonathan M. Stokes,Kevin Yang,Kyle Swanson,Wengong Jin,Andres Cubillos-Ruiz,Nina M. Donghia,Craig R. MacNair,Shawn French,Lindsey A. Carfrae,Zohar Bloom-Ackermann,Victoria M. Tran,Anush Chiappino-Pepe,Ahmed H. Badran,Ian W. Andrews,Ian W. Andrews,Ian W. Andrews,Emma J. Chory,George M. Church,Eric D. Brown,Tommi S. Jaakkola,Regina Barzilay,James J. Collins +21 more
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TLDR
A deep neural network capable of predicting molecules with antibacterial activity is trained and a molecule from the Drug Repurposing Hub-halicin- is discovered that is structurally divergent from conventional antibiotics and displays bactericidal activity against a wide phylogenetic spectrum of pathogens.About:
This article is published in Cell.The article was published on 2020-02-20 and is currently open access. It has received 1002 citations till now.read more
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Mechanosensitive Channels Mediate Hypoionic Shock-Induced Aminoglycoside Potentiation against Bacterial Persisters by Enhancing Antibiotic Uptake
TL;DR: The mechanosensitive (MS) channels, a ubiquitous protein family sensing mechanical forces of cell membrane, mediate such hypoionic shock-induced aminoglycoside potentiation as mentioned in this paper .
Book ChapterDOI
Data, Analytics and Interoperability Between Systems (IoT) is Incongruous with the Economics of Technology
Shoumen Datta,Shoumen Datta,Shoumen Datta,Tausifa Jan Saleem,Molood Barati,María Victoria López López,Marie-Laure Furgala,D. C. Vanegas,Gérald Santucci,Pramod P. Khargonekar,Eric S. McLamore +10 more
Journal ArticleDOI
A Significant Question in Cancer Risk and Therapy: Are Antibiotics Positive or Negative Effectors? Current Answers and Possible Alternatives.
TL;DR: The preponderant evidence derived from information reported over the last 10 years confirms that antibiotic exposure tends to increase cancer risk and, unfortunately, that it reduces the efficacy of various forms of cancer therapy (e.g., chemo-, radio-, and immunotherapy alone or in combination).
Proceedings ArticleDOI
Graph Neural Networks for COVID-19 Drug Discovery
Mark Cheung,Jose M. F. Moura +1 more
TL;DR: In this article, the authors presented an overview of the drug discovery framework, drug-target interaction framework, and GNNs for predicting desirable molecular properties for drugs that can inhibit SARS-CoV-2.
Posted ContentDOI
PharmaNet: Pharmaceutical discovery with deep recurrent neural networks
Paola Ruiz Puentes,Natalia Valderrama,Cristina González,Laura Alexandra Daza,Carolina Muñoz-Camargo,Juan C. Cruz,Juan C. Cruz,Pablo Arbeláez +7 more
TL;DR: A machine learning-based algorithm is introduced as an alternative for a more accurate search of new pharmacological candidates, which takes advantage of Recurrent Neural Networks for active molecule prediction within large databases, and achieves a perfect performance for human farnesyl pyrophosphate synthase (FPPS), which is a potential target for antimicrobial and anticancer treatments.
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