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
Reads0
Chats0
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
Citations
More filters
Journal ArticleDOI
Deep Learning Driven Drug Discovery: Tackling Severe Acute Respiratory Syndrome Coronavirus 2.
TL;DR: In this article, a mini-review discusses recent advances and future perspectives of deep learning-based SARS-CoV-2 drug discovery, as well as future perspectives on deep learning for SARS and CoV2.
Journal ArticleDOI
Deep learning model for virtual screening of novel 3C-like protease enzyme inhibitors against SARS coronavirus diseases.
Madhulata Kumari,Naidu Subbarao +1 more
TL;DR: In this article, a convolutional neural network (CNN) was used to predict inhibitory activity of 3CLpro in severe acute respiratory syndrome coronavirus (SARS-CoV) for unknown compounds during the virtual screening process.
Journal ArticleDOI
The future of antibiotics begins with discovering new combinations.
TL;DR: In this article, the authors focus on the discovery of new and efficacious combinations needed to revitalize the antibacterial drug pipeline and discuss how combination therapy can impact the treatment of bacterial infections.
Journal ArticleDOI
Artificial intelligence-enhanced drug design and development: Toward a computational precision medicine.
TL;DR: Artificial Intelligence (AI) relies upon a convergence of technologies with further synergies with life science technologies to capture the value of massive multi-modal data in the form of predictive models supporting decision-making as mentioned in this paper.
Journal ArticleDOI
Everything is connected: Graph neural networks
TL;DR: Graph representation learning has been studied extensively in the literature as mentioned in this paper , where the main aim is to assimilate the key concepts in the area, and position graph representation learning in a proper context with related fields.
References
More filters
Journal ArticleDOI
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
TL;DR: This work presents DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates, which enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression.
Journal ArticleDOI
Fast and accurate short read alignment with Burrows–Wheeler transform
Heng Li,Richard Durbin +1 more
TL;DR: Burrows-Wheeler Alignment tool (BWA) is implemented, a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps.
Journal ArticleDOI
edgeR: a Bioconductor package for differential expression analysis of digital gene expression data.
TL;DR: EdgeR as mentioned in this paper is a Bioconductor software package for examining differential expression of replicated count data, which uses an overdispersed Poisson model to account for both biological and technical variability and empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference.
Journal ArticleDOI
One-step inactivation of chromosomal genes in Escherichia coli K-12 using PCR products
TL;DR: A simple and highly efficient method to disrupt chromosomal genes in Escherichia coli in which PCR primers provide the homology to the targeted gene(s), which should be widely useful, especially in genome analysis of E. coli and other bacteria.
Journal ArticleDOI
Extended-Connectivity Fingerprints
David Rogers,Mathew Hahn +1 more
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.