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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Machine learning and deep learning in data-driven decision making of drug discovery and challenges in high-quality data acquisition in the pharmaceutical industry
TL;DR: In this paper , the authors discuss the recent updates in AI tools as cheminformatics application in medicinal chemistry for the data-driven decision-making of drug discovery and challenges in high-quality data acquisition in the pharmaceutical industry while improving small-molecule bioactivities and properties.
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Nano-metal-organic-frameworks for treating H2O2-Secreting bacteria alleviate pulmonary injury and prevent systemic sepsis.
Yi Wu,Wei Jiang,Shaohu Huo,Shuya Li,Youcui Xu,Shenggang Ding,Jing Zhou,Hang Liu,Wei-Fu Lv,Yucai Wang +9 more
TL;DR: In this article, the use of H2O2-reactive metal-organic framework nanosystems (MOFs) for treating pneumococcus pneumoniae (S. pneumoniae) was demonstrated.
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Host-acting antibacterial compounds combat cytosolic bacteria.
TL;DR: In this article , the authors focus mainly on the interactions between host cells and facultative intracellular bacteria to explore potential targets for the discovery and development of HACs, and summarize the targets of recently described HAC and their modes of action and pharmacological activities against diverse pathogenic bacteria-associated infections.
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Development and validation of a deep neural network-based model to predict acute kidney injury following intravenous administration of iodinated contrast media in hospitalized patients with chronic kidney disease: a multicohort analysis.
TL;DR: A DNN model using routinely available variables can accurately discriminate the risk of PC-AKI of hospitalized CKD patients following intravenous administration of ICM and shows promising discrimination in subgroup analyses.
Proceedings ArticleDOI
Harms from Increasingly Agentic Algorithmic Systems
Alan Chan,Rebecca Salganik,Alva Markelius,Chris Pang,Nitarshan Rajkumar,Dmitrii Krasheninnikov,L. Langosco,Zhonghao He,Yawen Duan,Micah Carroll,Michelle Lin,Alex Mayhew,Katherine Grant Collins,Maryam Molamohammadi,John Burden,Wanru Zhao,Shalaleh Rismani,Konstantinos Voudouris,Umang Bhatt,Adrian Weller,David Krueger,Tegan Maharaj +21 more
TL;DR: In this article , the authors identify four key characteristics which tend to increase the agency of a given algorithmic system: underspecification, directness of impact, goal-directedness, and long-term planning.
References
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TL;DR: A description of their implementation has not previously been presented in the literature, and ECFPs can be very rapidly calculated and can represent an essentially infinite number of different molecular features.