About: Targeting SARS-CoV-2 with AI- and HPC-enabled Lead Generation: A First Data Release

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About: Targeting SARS-CoV-2 with AI- and HPC-enabled Lead Generation: A First Data Release Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Targeting SARS-CoV-2 with AI- and HPC-enabled Lead Generation: A First Data Release
Creator	Liu, Xuefeng Hong, Zhi Ramanathan, Arvind Stevens, Rick Babuji, Yadu Blaiszik, Ben Brettin, Tom Chard, Kyle Chard, Ryan Clyde, Austin Foster, Ian Jha, Shantenu Li, Zhuozhao Ren, Yi Saint, Nicholaus Schwarting, Marcus Van Dam, Hubertus Wagner, Rick
Source	ArXiv
abstract	Researchers across the globe are seeking to rapidly repurpose existing drugs or discover new drugs to counter the the novel coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). One promising approach is to train machine learning (ML) and artificial intelligence (AI) tools to screen large numbers of small molecules. As a contribution to that effort, we are aggregating numerous small molecules from a variety of sources, using high-performance computing (HPC) to computer diverse properties of those molecules, using the computed properties to train ML/AI models, and then using the resulting models for screening. In this first data release, we make available 23 datasets collected from community sources representing over 4.2 B molecules enriched with pre-computed: 1) molecular fingerprints to aid similarity searches, 2) 2D images of molecules to enable exploration and application of image-based deep learning methods, and 3) 2D and 3D molecular descriptors to speed development of machine learning models. This data release encompasses structural information on the 4.2 B molecules and 60 TB of pre-computed data. Future releases will expand the data to include more detailed molecular simulations, computed models, and other products.
has issue date	2020-05-28(xsd:dateTime)
has license	arxiv
sha1sum (hex)	0ba5aaea1db8233464d6dfddea4e06e19953ca4d
resource representing a document's title	Targeting SARS-CoV-2 with AI- and HPC-enabled Lead Generation: A First Data Release
resource representing a document's body	covid:0ba5aaea1db8233464d6dfddea4e06e19953ca4d#body_text
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