Results 1 to 10 of about 119,327 (256)

Statistical Tools for Virtual Screening

Journal of Medicinal Chemistry, 2005
In large-scale virtual screening (VS) campaigns, data are often computed for millions of compounds to identify leads, but there remains the task of prioritizing VS "hits" for experimental assays and the dilemma of assessing true/false positives. We present two statistical methods for mining large databases: (1) a general scoring metric based on the VS ...
Jennifer R, Krumrine, Andrew T, Maynard, Charles L, Lerman   +2 more
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The Future of Virtual Compound Screening

Chemical Biology & Drug Design, 2012
We provide a future perspective of the virtual screening field. A number of challenges will be highlighted that virtual screening will likely face when compound data will further grow at or beyond current rates and when much more target information will become available.
Kathrin, Heikamp, Jürgen, Bajorath
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Virtual Screening for Kinase Targets

Current Medicinal Chemistry, 2004
Kinases have become a major area of drug discovery and structure-based design. Hundreds of 3D structures for more than thirty different kinases are available to the public. High structural and sequence homology within the kinase gene family makes the remaining kinases ideal targets for homology modeling and virtual screening.
Ingo, Muegge, Istvan J, Enyedy
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Virtual Screening: Are We There Yet?

Mini-Reviews in Medicinal Chemistry, 2006
The cost of pharmaceutical development has increased dramatically in recent years, and many assorted approaches have been developed to decrease both the time and costs associated with bringing a drug to the market. Among these methods is the use of in silico screening of compound databases for potential new lead compounds, commonly referred to as ...
Mehran, Jalaie, Veerabahu, Shanmugasundaram   +1 more
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An Empirical Investigation of Virtual Screening

2013 IEEE International Conference on Systems, Man, and Cybernetics, 2013
Drug discovery relies much on data processing. Virtual screening (VS) is a typical method of drug discovery that exploits chemical structures (molecules) to identify those that are likely to bind to a particular drug target. VS can be turned into either a matching or a classification problem where the quality of the data matters very much.
Amir Ali Rafati-Afshar, Abdelhamid Bouchachia   +1 more
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Approaches to Virtual Screening and Screening Library Selection

Current Pharmaceutical Design, 2013
The ease of access to virtual screening (VS) software in recent years has resulted in a large increase in literature reports. Over 300 publications in the last year report the use of virtual screening techniques to identify new chemical matter or present the development of new virtual screening techniques.
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Virtual Screening Against Obesity

Current Medicinal Chemistry, 2011
The development of novel drugs against obesity is one of the top priorities of worldwide drug research. In recent years, it has been facilitated by the application of virtual screening methods. In this review, we give a short introduction into obesity-related protein targets and computer-aided drug design techniques.
P, Markt, S, Herdlinger, D, Schuster
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Synergies of Virtual Screening Approaches

Mini-Reviews in Medicinal Chemistry, 2008
Virtual screening is a knowledge driven approach. Therefore, synergies between different virtual screening methods using information about the drug target as well as about known ligands in combination promise the best results. Finding novel active scaffolds is often a more important success criterion than hit rates of virtual screens.
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Structure-Based Virtual Screening

2017
Structure-based virtual screening (SBVS) is a computational approach used in the early-stage drug discovery campaign to search a chemical compound library for novel bioactive molecules against a certain drug target. It utilizes the three-dimensional (3D) structure of the biological target, obtained from X-ray, NMR, or computational modeling, to dock a ...
Qingliang, Li, Salim, Shah
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Machine Learning in Virtual Screening

Combinatorial Chemistry & High Throughput Screening, 2009
In this review, we highlight recent applications of machine learning to virtual screening, focusing on the use of supervised techniques to train statistical learning algorithms to prioritize databases of molecules as active against a particular protein target.
James L, Melville, Edmund K, Burke, Jonathan D, Hirst   +2 more
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