UNITY fingerprints

In addition to looking for data trends in physical property space using PCA and PLS, trends in chemical structure space can be delineated by viewing nonlinear maps (NLM) of two-dimensional structure descriptors such as Unity Fingerprints or topological atom pairs using tools such as Benchware DataMiner [42]. Two-dimensional NLM plots provide an overview of chemical structure space and biological activity/molecular properties are mapped in a 3rd and/or 4th dimension to look for trends in the dataset. 

In addition to the commonly used MACCS structural fragment keys (MDL Information Systems, Inc., San Leandro CA) and Daylight or UNITY fingerprints (Daylight... 

Fragments selected for optimal diversity using UNITY fingerprints... 

Substructure searching is often used in drug design and needs no further clarification. Similarity searching is also a very well known technique described in more detail elsewhere [52], We usually use M ACCS keys, Unity fingerprints, CATS descriptors, and feature trees for similarity searching [53], Each technique has its own strengths and weaknesses, so we favor parallel application of two or three of them. 

Samiulla et u/. report the design of natural product scaffolds that were then used in a small library of vasicinone derivatives. A key aspect of the design was the incorporation of parameters intended to result in improved ADME properties by including the filters proposed by Lipinski" and Veber et BCUTs were used to optimize the diversity of the scaffolds while Unity fingerprints were used in the diversity optimization of the vasicinone library. The measured solubility, permeability in MDCK cells and CYP inhibition were measured for the scaffolds. The resulting libraries demonstrated favorable distributions of each of the measured ADME properties. 

Applications of UNITY fingerprints discussed in literature are [Brown and Martin, 1996 Matter, 1997 Matter and Potter, 1999 Schuffenhauer, Gillet et al, 2000 Wild and Blankley, 2000 Wintner and Moallemi, 2000 Makara, 2001 Cruciani, Pastor et al, 2002 Keseru and Molnar, 2002 Martin, Kofron et al, 2002 Raymond and Willett, 2002 Abrahamian, Fox et al, 2003 Holliday, Salim et al, 2003 Salim, Holliday et al, 2003 Wilton and Willett, 2003 Schuffenhauer, Floersheim et al, 2003 Bender, Mussa et al, 2004c Bender and Glen, 2005 Schuffenhauer, Brown et al, 2006]. 

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)... 

Schuffenhauer et al. [21] reported a comparative study ofbioisosteric replacements with UNITY 2D fingerprints and FBSS (field-based similarity search) using the Bioster database [22] as a source ofbioisosteric pairs. The authors report that both these 2D and 3D methods provide complementary results that were demonstrated to work synergistically when combined using data fusion. The UNITY fingerprint was reported to be very sensitive to heteroatom replacement. This sensitivity can be overcome somewhat by abstracting the atoms present in a structure into pharmacophoric features. 

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