MACC-2 method

CATS3D was not only successful in scaffold hopping on the basis of the definition above (Meqi). We also observed a substructure hopping , which might be seen as an equivalent to more traditional bioisosteric replacement strategies. It seems that the CATS descriptor family represents molecules in a way that allows a combination of scaffold hopping and substructure hopping at once. This can result in a selection of molecules which would not be considered similar by other methods such as the MACCS keys. 

Unlike the classical —> autocorrelation descriptors, only the highest product of interaction energies per distance bin is stored as GRIND descriptor (MACC-2 transform). This difference is responsible for the reversibility of GRIND descriptors. Unlike most of the grid-based methods, GRIND descriptors are also independent of the molecule alignment. 

The fingerprint methods can be divided into dictionary-based and hashed-based methods. In the dictionary-based methods, such as the MDL MACCS keys [12] and BCI fingerprints [13], a binary fingerprint is defined in which each bit represents a particular substructural fragment contained in a fragment dictionary. The fingerprint... 

The number of features combined in a vector-type representation is indicative of the dimensionality of the problem space. Low-dimensional representations, on the one hand, allow easy visualization but are most often not very discriminative. Highdimensional representations, on the other hand, such as those encoded in Daylight fingerprints [23], MACCS keys [24], or UNITY fingerprints [25], provide more detailed accounts on structural or chemical variations. However, this is achieved at the cost of visualization. Part of these high-dimensional representations describe specific local features of molecules, and because not all molecules in the data contain these features, gaps or zeros are introduced in the data representation. For certain data mining methods, this could be problematic. In many cases, dimensionality reduction procedures are applied to reduce the complexity of the representation. The reduction of the dimensionality is accomplished by means of 1) variable selection procedures, 2)... 

The MACCS-II link has its advantages and disadvantages at the moment. To use it, you must always be in MACCS. This problem occurs because you cannot get information from a MACCS database from outside MACCS by any direct method. ORACLE does not have this problem. For example, it is possible to retrieve ORACLE database information into a FORTRAN procedural language program for further manipulation and display. What MACCS-II does provide is a strong link to the outside. This overcomes most of the problems associated with this missing link to MACCS. 

We currently use the link in two different ways. In one case the link takes place totally using the MACCS programming interface. The other uses the ability to suspend and exit MACCS, enter an outside apphcation and then return to MACCS. Both of these methods have their advantages and disadvantages. 

A few of the doses were calculated with an older version of the code (MACCS Version 1.5.11.1) and dose conversion factor library using the same input parameters. Both versions of the code and dose conversion factor library gave almost identical results for these inputs. Further details on the calculation method and inputs can be found in the MACCS2 user manual (Chanin and Young 1997) and in the airborne dose versus distance database documentation (Naegeli 1999). 

An exhaustive analysis of 2995 molecule pairs extracted from the 98.1 version of Bioster database indicated that similarity measures based on 2D molecular fingerprints or electrostatic field descriptors were complementary although 2D methods could be adequate for similarity analyses [55]. To evaluate a range of similarity measures among synthetic substances and natural products, the Willett group also used 5024 compounds from Bioster database as well as sets of selected bioactive compounds from the more populous Chemical Abstract Service, ID-Alert, MACCS Drug Data Report, and NCI AIDS databases [56]. 

Method MACCS 166 LINGO Path Tree Circular... 

How does this example apply to the use of multiple similarity methods Each of the similarity methods can be considered to be equivalent to an independent judge, since none of the values produced by the other methods have an explicit impact on the value produced by a given method. This may not always be the case, for example, if two methods use MACCS key fingerprints, but one uses the Tanimoto (Jacard) and the other a closely related similarity function (see Table 15.3). As shown by Gower [76], some molecular similarity functions are monotonically related. Thus, comparisons of these functions based on the same molecular representation will produced linear correlations of the values computed by the two functionally similarity functions. Hence, only one of the functions should be used. 

Clustering by 2D fingerprints is a very common procedure, and yet there are still many unanswered questions, principally aroimd the choice of descriptor, and the selection of a statistically appropriate number of clusters. Wild and Blankley have looked at these issues and have come to some interesting conclusions MACCS-like keys are best for general diverse sets (e.g. corporate databases), whereas Daylight-like keys are the best for similar sets (e.g. combinatorial libraries) the best method for eluster-level selection is dataset-dependent. However, the Kelley method seems to have the best worst-case performance across the different datasets and deseriptors. Xue et al. have developed a method for using consensus... 

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