Diversity space

In addition, the large number of experiments and the higher diversity space that can be accessed also greatly improve the quality of the data obtained. Trends are more easily observed as the correlation becomes more reliable with the increasing number of experiments. 

HTE should never be considered as a mindless exercise to identify a catalyst. Rather, the design of a set of experiments requires a good overview of what really determines the diversity space for this particular reaction. For this reason, HTE will always remain linked with areas of more classical research, such as mechanistic studies. 

Dissimilarity and clustering methods only describe the compounds that are in the input set voids in diversity space are not obvious, and if compounds are added then the set must be re-analyzed. Cell-based partitioning methods address these problems by dividing descriptor space into cells, and then populating those cells with compounds [67, 68]. The library is chosen to contain representatives from each cell. The use of a partition-based method with BCUT descriptors [69] to design an NMR screening library has recently been described [70]. 

There is an important interplay between structure-based combinatorial chemistry and diversity. By choosing the most diverse set of compounds within those predicted to bind well, more information becomes available about the structural properties required by compounds to bind, which refines and improves the predictions for the next round of synthesis. In addition, if good hits are found, the information can be fed back to find compounds close in diverse space to the hit. 

The extraterrestrial reference spectral distribution was assembled from a number of recent diverse space based (satellite) measurement sources. The ETR reference spectrum is normalized to a total integrated irradiance of 1366.1 Wm2. 

It could be safely assumed that nowadays diversity-inspired, pure primary libraries are not synthesized any more in fact, although they can produce a large number of compounds their representation of the huge chemical diversity space remains necessarily limited, and the need to focus large libraries on meaningful diversity is more and more urgent. 

Many reports have been published addressing various aspects of diversity analysis in the context of chemical library design and database mining. Methods have also been published to map molecules from a high-dimensional chemical space to 2D/3D space so that direct visualization of chemical similarity and diversity becomes feasible.Fow-dimensional diversity space also... 

Solubility is extremely difficult to calculate. Dozens of methods exist, but none is reliable enough to be used in the entire chemical diversity space populated by infinite drug candidates. Experimental solubility errors are relatively high and frequent. Moreover, solubility can change dramatically with the purity of the compounds, stability, and time. Solubility of liquid substances differs from that of solid phase compounds. Solubility is thermodynamically affected by crystal packing, influencing the process of crystal lattice disruption and hence polymorphism, amorphous solid compounds lead to imprecise experimental measures. Finally, publically available databases of solubility values contain a lot of errors. 

This approach is particularly efficient when combined with the Cosine coefficient (69) and was used by Pickett et al. in combination with pharmacophore descriptors (70). In lower dimensional spaces the maxsum measure tends to force selection from the comers of diversity space (6b, 71) and hence maxmin is the preferred function in these cases. A similar conclusion was drawn from a comparison of algorithms for dissimilarity-based compound selection (72). 

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