EFindSite: Enhanced Fingerprint‐Based Virtual Screening Against Predicted Ligand Binding Sites in Protein Models. Issue 2 (12th February 2014)

• Record Type: Journal Article
• Authors: Feinstein, Wei P.; Brylinski, Michal
• Is Part Of: Molecular informatics. Volume 33:Issue 2(2014:Feb.)
• Page Start: 135
• Page End: 150
• Publication Date: 2014-02-12
• Subjects: Cheminformatics -- Periodicals; QSAR (Biochemistry) -- Periodicals; Structure-activity relationships (Biochemistry) -- Periodicals; Drugs -- Structure-activity relationships -- Periodicals; 615.19
• DOI: 10.1002/minf.201300143
• Languages: English
• ISSNs: 1868-1743

Abstract

<abstract abstract-type="main" xml:lang="en"> <title>Abstract</title> <p>A standard practice for lead identification in drug discovery is ligand virtual screening, which utilizes computing technologies to detect small compounds that likely bind to target proteins prior to experimental screens. A high accuracy is often achieved when the target protein has a resolved crystal structure; however, using protein models still renders significant challenges. Towards this goal, we recently developed <italic>e</italic>FindSite that predicts ligand binding sites using a collection of effective algorithms, including meta‐threading, machine learning and reliable confidence estimation systems. Here, we incorporate fingerprint‐based virtual screening capabilities in <italic>e</italic>FindSite in addition to its flagship role as a ligand binding pocket predictor. Virtual screening benchmarks using the enhanced Directory of Useful Decoys demonstrate that <italic>e</italic>FindSite significantly outperforms AutoDock Vina as assessed by several evaluation metrics. Importantly, this holds true regardless of the quality of target protein structures. As a first genome‐wide application of <italic>e</italic>FindSite, we conduct large‐scale virtual screening of the entire proteome of <italic>Escherichia coli</italic> with encouraging results. In the new approach to fingerprint‐based virtual screening using remote protein homology, <italic>e</italic>FindSite demonstrates its compelling proficiency offering a high ranking accuracy and low susceptibility to target structure deformations. The enhanced version of <italic>e</italic>FindSite is freely available to the academic community at http://www.brylinski.org/efindsite.</p> </abstract>