Using Extended-Connectivity Fingerprints with Laplacian-Modified Bayesian Analysis in High-Throughput Screening Follow-Up
Year: 2005
Type: article
Abstract: This article describes the use of a combination of extended-connectivity fingerprints (ECFPs) and Laplacian-modified Bayesian analysis in a study of the inhibition of Escherichia coli dihydrofolate reductase. The McMaster High-Throughput Screening Lab at McMaster University proposed a competition to predict the hits in a separate test set of 50,000 compounds. Although the problem seemed best approached with 3D methods, the authors show that 2D methods offer surprisingly competitive results with a low computational cost.
Source: SLAS DISCOVERY
Authors: David Rogers, Robert D. Brown, Mathew Hahn
Language: English
Subfield: Drug Discovery
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $2,070
OpenAlex ID: W2142602210