BCUT

Z eb index, Wiener index. Balaban J index, connectivity indices chi (x), kappa (k) shape indices, molecular walk counts, BCUT descriptors, 2D autocorrelation vector... 

Before the comparative molecular field analysis (CoMFA), BCUT descriptors, 4D-QSAR, and HYBOT descriptors arc discussed in more detail, some further descriptors are listed briefly. 

The BCUT descriptors (Buiden-CAS-University of Texas eigenvalues) [52], are commonly used, are eigenvalue-based, and include 3D information also. 

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]. 

Linear representations are by far the most frequently used descriptor type. Apart from the already mentioned structural keys and hashed fingerprints, other types of information are stored. For example, the topological distance between pharmacophoric points can be stored [179, 180], auto- and cross-correlation vectors over 2-D or 3-D information can be created [185, 186], or so-called BCUT [187] values can be extracted from an eigenvalue analysis of the molecular adjacency matrix. 

Mason, J.S. and Beno, B.R. Library design using BCUT chemistry-space descriptors and multiple four-point pharmacophore fingerprints simultaneous optimization and structure-based diversity. /. Mol. 

A significant percentage of any compound library will inevitably fall into small clusters unsuitable to rigorous statistical evaluation. These must be considered separately - in our case, using diversity analysis with BCUT descriptors [39] to supplement the list derived from clustering. Throughout this process, we use visualization to assess data quality, identify potential problems such as edge effects, and check trends and patterns. 

The 5 k actives with percent inhibition of 25 to 40% and that feU into clusters of less than five compounds were treated separately using BCUT diversity analysis, as described in Section 6.2.5. A cell-based selection biased by primary activity from six bins per each of six axes yielded 1258 compounds. The combined selection from filtering, clustering, and diversity totaled 6986 compounds representing 3337 ring scaffolds and was submitted for confirmation assays. Note that the full set of 16 k filtered actives contained 9254 ring hashcodes, so the selected set covers 36.1% of the represented scaffolds. Because of the presence of duplicate samples in the corporate screening collection, 7275 samples were pulled and assayed. 

Fig. 7.1 3 -D plot of a very large library in BCUT space. As was typically found in very large...

In the technique of post hoc design, a set of descriptors are built up by examination of a set of compounds active at a particular receptor family or sub-class. Normally, the set of drugs would be from a commercial database such as MDDR or the Merck Index, etc. and the descriptors would usually be substructural fragment or key based. One example would be the GPCR-PA+ sub-class referred to above, where BCUT descriptors have been used to aid the design of a focused library of aroimd 2000 compoimds based on 8 scaffolds. Libraries have also been constructed based on peptidomimetic principles as well as on the concepts of privileged structures. ... 

Vectors whose components have continuous values correspond to the more traditional types of vectors found in the physical sciences. They are of identical form to the discrete-valued vectors (see Eq. 2.16) except that the components, vA(xk), are continuous valued. In chemoinformatics, however, the nature of the components is considerably different from those typically found in physics. For example, physiochemical properties, such as logP, solubility, melting point, molecular volume, Hammett ap parameters, and surface charge, as well as other descriptors derived explicitly for the purpose, such as BCUTs... 

Although it is ubiquitous in chemoinformatics applications, the term vector should be used with caution as vectors are properly the objects of vector spaces and must satisfy the axioms of vector spaces. For example, vectors in BCUT chemistry spaces do not form a vector space because the sum of two BCUT vectors may not lie in the space (29). However, as long as this rather fine distinction is borne in mind, significant problems should not arise, and the term vector, taken in its broadest sense, will be used here. 

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