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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CADD, AI and ML in Drug Discovery: A Comprehensive Review.
TL;DR: In this article , the authors discuss how CADD, AI, ML, and DL approaches help identify drug candidates and various other steps of the drug discovery process and provide a detailed overview of the different in silico tools used and how these approaches interact.
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Antibiotic uptake through porins located in the outer membrane of Gram-negative bacteria.
TL;DR: A larger dataset of single channel permeabilities under various condition will be a powerful tool for understanding and improving the activity of antibiotics.
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Applying Artificial Intelligence to Gynecologic Oncology: A Review.
David Mysona,Daniel S. Kapp,Atharva Rohatgi,Danny Lee,Amandeep Mann,Paul Minh Huy Tran,Lynn Kim Hoang Tran,Jin-Xiong She,John K. Chan +8 more
TL;DR: A review of the role of artificial intelligence in gynecologic oncology can be found in this paper, where the authors provided a summary of AI, its applicability, and its limitations in the field of gynecology.
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Drug repurposing in silico screening platforms.
TL;DR: This review outlines some of the exciting advances in the specific applications of in silico approaches to the challenge of drug repurposing and focuses particularly on where these efforts have resulted in the development of generic platform technologies of broad value to researchers involved in programmatic drugRepurposing work.
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NICEdrug.ch, a workflow for rational drug design and systems-level analysis of drug metabolism.
Homa MohammadiPeyhani,Anush Chiappino-Pepe,Kiandokht Haddadi,Jasmin Hafner,Noushin Hadadi,Vassily Hatzimanikatis +5 more
TL;DR: The NICEdrug.ch database as mentioned in this paper includes a unique fingerprint that identifies reactive similarities between drug-drug and drug-metabolite pairs, which can be used for lead discovery and drug repurposing.
References
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Extended-Connectivity Fingerprints
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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.