Progressive Docking: a Hybrid Qsar/Docking Approach for Accelerating in Silico High Throughput Screening.
From: Division of Infectious Diseases, University of British Columbia, Vancouver, British Columbia V5Z 3J5. artc@interchange.ubc.ca
Journal of medicinal chemistry
- Publish Date: Dec 2006
- ISSN: 0022-2623
- Volume: 49
- Issue: 25
- Pages: 7466-78
- Medium: Print
- Language: English
- Citation (JAMA): Cherkasov Artem, Ban Fuqiang, Li Yvonne, et al. Progressive Docking: a Hybrid Qsar/Docking Approach for Accelerating in Silico High Throughput Screening.. J. Med. Chem. Dec 2006;49:7466-78
Abstract
A combination of protein-ligand docking and ligand-based QSAR approaches has been elaborated, aiming to speed-up the process of virtual screening. In particular, this approach utilizes docking scores generated for already processed compounds to build predictive QSAR models that, in turn, assess hypothetical target binding affinities for yet undocked entries. The “progressive docking” has been tested on drug-like substances from the NCI database that have been docked into several unrelated targets, including human sex hormone binding globulin (SHBG), carbonic anhydrase, corticosteroid-binding globulin, SARS 3C-like protease, and HIV1 reverse transcriptase. We demonstrate that progressive docking can reduce the amount of computations 1.2- to 2.6-fold (when compared to traditional docking), while maintaining 80-99% hit recovery rates. This progressive-docking procedure, therefore, substantially accelerates high throughput screening, especially when using high accuracy (slower) docking approaches and large-sized datasets, and has allowed us to identify several novel potent nonsteroidal SHBG ligands.
Mesh Headings (Keywords): Binding Sites, Carbonic Anhydrases, Cysteine Endopeptidases, Databases, Factual, HIV Reverse Transcriptase, Humans, Ligands, Models, Molecular, Molecular Structure, Protein Binding, Proteins, Quantitative Structure-Activity Relationship, Sex Hormone-Binding Globulin, Transcortin, Viral Proteins
Check for Full Text / PubMed Unique Identifier (PMID): 17149875
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