Compound selection

In dissimilarity-based compound selection the required subset of molecules is identified directly, using an appropriate measure of dissimilarity (often taken to be the complement of the similarity). This contrasts with the two-stage procedure in cluster analysis, where it is first necessary to group together the molecules and then decide which to select. Most methods for dissimilarity-based selection fall into one of two categories maximum dissimilarity algorithms and sphere exclusion algorithms [Snarey et al. 1997]. 

The maximum dissimilarity algorithm works in an iterative manner at each step one compormd is selected from the database and added to the subset [Kennard and Stone 1969]. The compound selected is chosen to be the one most dissimilar to the current subset. There are many variants on this basic algorithm which differ in the way in which the first compound is chosen and how the dissimilarity is measured. Three possible choices for fhe initial compormd are (a) select it at random, (b) choose the molecule which is most representative (e.g. has the largest sum of similarities to the other molecules) or (c) choose the molecule which is most dissimilar (e.g. has the smallest sum of similarities to the other molecules). 

Brown R D and Y C Martin 1996. Use of Structure-Activity Data to Compare Structure-Base Clustering Methods and Descriptors for Use in Compound Selection. Journal of Chemia Information and Computer Science 36 572-583. 

Snarey M, N K Terrett, P Willett and D J Wilton 1997. Comparison of Algorithms for Dissimilaritj based Compound Selection. Journal of Molecular Graphics and Modelling 15 372-385. 

Table VIII. The compounds selected are as typical as possible, but it must be remembered that there are many environmental factors that produce changes in the location of the absorption bands. These displacements are usually of the order of a few mp., but in some cases they are so great as to move the absorption band into a completely different region of the spectrum.

Sulfur Compounds. Various gas streams are treated by molecular sieves to remove sulfur contaminants. In the desulfurization of wellhead natural gas, the unit is designed to remove sulfur compounds selectively, but not carbon dioxide, which would occur in Hquid scmbbing processes. Molecular sieve treatment offers advantages over Hquid scmbbing processes in reduced equipment size because the acid gas load is smaller in production economics because there is no gas shrinkage (leaving CO2 in the residue gas) and in the fact that the gas is also fliUy dehydrated, alleviating the need for downstream dehydration. 

New areas in adsorption technology include carbonaceous and polymeric resins (3). Based on synthetic organic polymer materials, these resins may find special uses where compound selectivity is important, low effluent concentrations are required, carbon regeneration is impractical, or the waste to be treated contains high levels of inorganic dissolved soHds. 

Tritium is the subject of various reviews (6—8), and a book (9) provides a comprehensive survey of the preparation, properties, and uses of tritium compounds. Selected physical properties for molecular tritium, are given in Table 1. 

Flammability Timits. Some 1358 compounds selected from the DIPPR Compilation Pile (Peimsylvania State University, 1991 Ref. 4) have been fit for upper and lower flammabiHty limits (227). Average errors reported were 0.266% (volume) and 0.06% (volume) for upper and lower flammabiHty limits, respectively. A detailed analysis by functional group classification is included that identifies classifications with high error for several methods. 

MONOPROTECTION OF DICARBONYL COMPOUNDS Selective Protection of a- and /3-Diketones... 

Bromination of 3 -hydroxy-B-homo-5a-cholestan-7-one acetate (54b) in the presence of hydrobromic acid gives a single thermodynamically stable monobromo ketone. To determine the position of the bromine atom, the sequence of reactions was repeated with compounds selectively deuterated in the 5a-position. 

The primary function of this section is to organize data to faalitate NMR structure elucidation of organofluonne compounds Selectively fluonnated aliphatics are emphasized, whereas fluonnated aromatics are covered m less detail Inorganic nitrogen, phosphorus, silicon, and sulfur fluondes are not included, although compounds containing these and other heteroatoms attached to CF3 are the focus of multmuclear data presented later (see Table 16)... 

In contrast to aromatic halonitro compounds, selective removal of halogen in aliphatic halonitro compounds presents little problem. The reaction can be done by hydrogenation over palladium-on-carbon in the presence of a hydrohalide acceptor 46,73). 

The present work involves the study of methyl glycosides and O-isopropylidene ketals of various isomeric deoxy sugars by mass spectrometry. Several of the compounds selected for the present study have free hydroxyl groups, and interpretation of their mass spectra shows the scope of the study of these and related deoxy sugar derivatives by mass spectrometry without prior substitution of all hydroxyl groups. Some of the candidates (compounds 4, 7, 8 and 10) are structurally related to biologically-derived deoxy sugars. 

The standard method for the preparation of 3//-1.5-benzodiazepines 2 is the condensation of benzene-1,2-diamine with 1,3-dicarbonyl compounds. Selected examples are given.255... 

Material Property Table 7-18(b) Glass-reinforced TP compound selection sheet... 

Pharmacogenetics as a Compound Selection Tool in Drug Development... 

A detailed study of the radiochemical reactions of phenylarsenic compounds has been published by Grossmann. Once again unable to effect isolation of all compounds, he was able, however, to get evidently reliable values for the sums of all compounds with one, two and three phenyl-arsenic bonds, respectively, as well as ionic arsenic and a further organic-soluble fraction which appeared to be a group of polymeric phenylarsenic compounds. Selected data from this work are given in Table 6. 

The previous sections have summarized the basic techniques available for searching chemical databases for specific types of query. Another important database application is compound selection, the ability to select a subset of a database for submission to a biological testing program. The selection procedure can be applied to in-house databases, to externally available compound collections, or to virtual libraries, that is, sets of compounds that could potentially be synthesized. 

Compound selection methods usually involve selecting a relatively small set of a few tens or hundreds of compounds from a large database that could consist of hundreds of thousands or even millions of compounds. Identifying the n most dissimilar compounds in a database containing N compounds, when typically n N, is computationally infeasible because it requires consideration of all possible n-member subsets of the database, and therefore approximate methods have been developed as described below. 

Dissimilarity-based compound selection (DECS) methods involve selecting a subset of compounds directly based on pairwise dissimilarities [37]. The first compound is selected, either at random or as the one that is most dissimilar to all others in the database, and is placed in the subset. The subset is then built up stepwise by selecting one compound at a time until it is of the required size. In each iteration, the next compound to be selected is the one that is most dissimilar to those already in the subset, with the dissimilarity normally being computed by the MaxMin approach [38]. Here, each database compound is compared with each compound in the subset and its nearest neighbor is identified the database compound that is selected is the one that has the maximum dissimilarity to its nearest neighbor in the subset. 

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