Experimental compound database

To further strengthen decision-making, it is helpful to use statistical clustering to place each experimental compound in the context of a database created from the pharmaceutical profiling of compounds with well-characterized human PK. In the absence of... 

Tan L, Batista J, Bajorath J (2010) Computational methodologies for compound database searching that utilize experimental protein-ligand interaction information. Chem Biol Drug Des 76(3)491-200... 

The advent of experimental techniques such as combinatorial and parallel chemical synthesis, and high-throughput screening has enabled the production of massive amounts of data. These compound databases have played a key role in drug design (Miller, 2002) and other research areas such as Agrochemistry and Food Chemistry. Current computational... 

Preparing and Filtering Compound Databases for Virtual and Experimental Screening... 

Both tools additionally suffer from the small number of reliable biodegradation studies in which transformation pathways were elucidated in enough detail to serve as training data for rule development and prioritization. Especially when confronted with compounds such as current-use pesticides and pharmaceuticals, both tools are lacking some of the rules necessary to break down these more complex molecular structures. Hopefully this situation will improve in the future since with the implementation of REACH, which requests identification of relevant transformation products for all compounds produced in amounts exceeding 100 t/year, the experimental biodegradation database is expected to grow considerably. 

The database approaches are heavily dependent on the size and quality of the database, particularly on the availability of entries that are related to the query structure. Such an approach is relatively fast it is possible to predict the H NMR spectrum of a molecule with 50-100 atoms in a few seconds. The predicted values can be explained on the basis of the structures that were used for the predictions. Additionally, users can augment the database with their own structures and experimental data, allowing improved predictions for compounds bearing similarities to those added. 

The identification of chemical compounds by IR spectroscopy is usually done by comparing an experimental spectrum of the compound with a reference spectrum. However, the number of known chemical structures (ca. 17 000 000) greatly exceeds the number of IR spectra the largest database of spectra, Specinfo [76], contains 600 000 spectra. 

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