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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Computer-aided drug design in seeking viral capsid modulators
TL;DR: In this article , the authors summarize the application of CADD in the discovery, optimization, and mechanism prediction of capsid-targeting small molecules, providing new insights into antiviral drug discovery modalities.
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Target-driven machine learning-enabled virtual screening (TAME-VS) platform for early-stage hit identification
TL;DR: Good et al. as discussed by the authors proposed a target-driven machine learning-enabled virtual screening (TAME-VS) platform, which leverages existing chemical databases of bioactive molecules to modularly facilitate hit finding.
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Antimicrobial resistance genes of fermented red pepper (FRP) related food in a large-scale environment: distribution pattern and risk assessment
TL;DR: In this article , a combination of read-and assembly-based whole genome sequencing methods as well as amplicon sequences analysis was used to investigate and reveal the ARGs dissemination patterns and risk assessment in fermented red pepper (FRP) related foods on a large-scale metagenomic data.
Domain-aware representation of small molecules for explainable property predic- tion models
TL;DR: In this paper , a domain-aware fragment-based graph input representation based on a molecular fragmentation approach termed pBRICS was developed to fragment small molecules into their functional groups, which can be used to predict various properties including ADMET properties.
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Structure-based virtual screening
TL;DR: In this article , the authors discuss how structure-based virtual screening (SBVS) is used to find compounds that could be considered bioactive hits in the campaigns of lead discovery, which include homology modeling, molecular docking, molecular dynamics simulation, databases, and virtual screening approaches.
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