Cheminformatics research

Weifan Zheng, Cheminformatics Research Resources, Division of Medicinal Chemistry, School of Pharmacy, University of North Carolina at Chapel Hill, NC 27599-7360, USA. (weifan zheng unc.edu). 

Chemoinformatics (or cheminformatics) deals with the storage, retrieval, and analysis of chemical and biological data. Specifically, it involves the development and application of software systems for the management of combinatorial chemical projects, rational design of chemical libraries, and analysis of the obtained chemical and biological data. The major research topics of chemoinformatics involve QSAR and diversity analysis. The researchers should address several important issues. First, chemical structures should be characterized by calculable molecular descriptors that provide quantitative representation of chemical structures. Second, special measures should be developed on the basis of these descriptors in order to quantify structural similarities between pairs of molecules. Finally, adequate computational methods should be established for the efficient sampling of the huge combinatorial structural space of chemical libraries. 

The NIH has set up a consortium called the Molecular Libraries Screening Center Network (MLSCN), which performs HTS on assays provided by the research community. It currently has more than 100,000 chemically diverse compounds. This is an initiative of the Molecular Libraries Roadmap, which also has another two components Cheminformatics and Technology Development. The aim is to generate a comprehensive database of chemical compounds and their bioactivities to enhance the capability for the development of new drug entities. 

Cheminformatics, Johnson Johnson, Pharmaceutical Research Development, L.L.C., San Diego, California, USA Brett R. Beno Computer Aided Drug Design, Pharmaceutical Research Institute, Bristol-Myers Squibb Company, Princeton, New Jersey, USA Curt Breneman Department of Chemistry, Rensselaer Polytechnic Institute, Troy, New York, USA... 

David Cummins is Principal Research Scientist at Eli Lilly and Company. His interests are in nonparametric regression, exploratory data analysis, simulation, predictive inference, machine learning, model selection, cheminformatics, genomics, proteomics, and metabonomics. 

The studies described in this chapter were supported in parts by the National Institutes of Health s Cheminformatics Center planning grant P20-RR20751 and the research grant R01GM066940. 

Cheminformatics is a research area dealing with computational processing and management of chemical information, particularly information acquisition, chemical descriptors, and computerized analysis of chemistry data. 

Expert systems have now been in nse for more than 40 years and have spread into nearly all imaginable areas of application. Evolving from the research area of artih-cial intelligence (Al), they can be fonnd today in commercial applications throughout the entire scientihc and technical areas. We have seen that this technology is not just stand-alone software but is supported by many technologies from mathematics, cheminformatics, bioinformatics, Al, and related areas. 

In particnlar, cheminformatics has gained increasing awareness in a wide scientific commnnity in recent decades. One of the fnndamental research tasks in this area is the development and investigation of molecnlar descriptors, which represent a molecule and its properties as a mathematical vector. These vectors can be processed and analyzed with mathematical methods, allowing extensive amounts of molecular information to be processed in compnter software. 

Nuclear receptor targeted screening libraries and chemogenomics approaches are a relatively recent field of research enabled by progress in cheminformatics as well as structural biology and combinatorial chemistry. J. Mestres summarizes the current knowledge and applications in this field of nuclear receptor research efforts. 

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