Chemical space visualization

Key Words Biological activity chemical features chemical space cluster analysis compound databases dimension reduction molecular descriptors molecule classification partitioning algorithms partitioning in low-dimensional spaces principal component analysis visualization. 

An alternative to dimension reduction is the use of composite and uncorrelated descriptors that are suitable for the design of information-rich yet low-dimensional chemical spaces. An elegant example is presented by the popular BCUT (Burden-CAS-University of Texas) descriptors (Pearlman and Smith 1998). BCUTs are a set of uncorrelated descriptors that combine information about molecular connectivity, inter-molecular distances, and other molecular properties. BCUT spaces used for many applications are typically only six-dimensional and can frequently be further reduced to 3D representations for visualization purposes by identifying those BCUT axes around which most compounds map. 

D Data Mining module utilizing the novel concept of Chemically Relevant Principal Components to visualize and analyze chemical space of results from ADMET Predictor. 

A more profound visual difference of the chemical space covered by natural products and synthetic drugs was presented by Derek Tan, in which he applied a similar PCA analysis of 20 synthetic drugs (including ten best sellers of 2004) and 20 natural products.7 For this analysis, Tan used nine molecular descriptors—molecular weight, clog P, H-bond donors, H-bond acceptors, rotatable bonds, polar surface area (PSA), chiral centres, N and O atoms—and then applied PCA to reduce nine-dimensional vectors to two-dimensional vectors before re-plotting the data. 

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... 

Fig. 8.4 The visualized distribution of the potentially enriched hits as well as the known FXa inhibitors in the chemical space by using the first three principle components from PCA...

Self-organizing Kohonen maps are a preferred method for visualization of these redundancies. Product-based library selection is a powerful tool to select fractions of a virtual library in order to complete a homogeneous covering of the chemical space. 

Fig. 15.1-3 Schematic visualization of the various concepts to address chemical and biological space (shaded areas) in drug discovery. Medicinal chemistry focused on compound series (red dots) that had shown activity in pharmacological assays and compound optimization was driven by a tight feedback from biological experiments, leading to a focused nonarrayed addressing of chemical space. The combinatorial promise was to systemically explore the chemical space with diverse arrays of compounds (blue dots) to find the suitable starting points. Analysis of combinatorial chemistry libraries showed their limited...

Fig. 32.6. Example of the visualization of the chemical space of hits and similar but inactive structures from a target assay light grey inactive grey to black decreasing IC50.

Southall, N.T. and Ajay (2006) Kinase patent space visualization using chemical replacements. Journal of Medicinal Chemistry, 49, 2103-2109. 

The integration of structural similarity and activity within a single visualization approach provides a consistent framework for the elucidation of SAR trends, continuity regions, and activity cliffs in a dataset. Again dimensionality reduction approaches are essential for mapping the chemical space onto a 2D-plot. The first... 

Dimensionality reduction and data visualization Kernel Principal Component Analysis (KPCA) [6], Kernel Feature Analysis (KFA) [77] Drawing maps of chemical space... 

Figure 17.11 Application of multidimensional scaling (MDS) to visualize the diversity of chemical space from the exemplified compounds of nine different NaV1.7 patent applications (represented in different colors) [30-33], Standard chemical fingerprints are used and the projections are made in three dimensions. While this method allows chemists to readily detect broad differences in...

While the chemical universe of molecitles potentially relevant in food science is considerably smaller, it nonetheless is large enough to benefit from many of the chemical informatic concepts that have proved useful in medicinal chemistry and related fields of chemistry. Two of these concepts, molecttlar similarity and chemical space (CS), are dealt with in this chapter. Of the two, molecular similarity is more fundamental since it plays a cmcial role in the definition of CS itself. Though important, activity or property landscapes, which provide the third leg of a triad of activities that play important roles in much of chemical informatics, will not be discussed here. Numerous recent publications describing the visual and statistical aspects of activity landscapes as well as the basic features of these landscapes should be consrrlted for details [4-8],... 

Visualizing the Chemical Space of Flavours 2.3.1 The Chemical Space... 

To gain an overview of the chemical space of flavours, we have performed a PCA visualization of the merged database containing FragranceDB and TasteDB, totalling 2517 compounds. These databases are represented in their (PCI, PC2)-plane which can be considered as a general 2-D map of their chemical space. 

Medina-Franco JL, Martinez-Mayorga K, Giulianotti MA, Houghten RA, Pinilla C (2008) Visualization of the chemical space in drug discovery. Curr Comput-Aided Drug Des 4(4) 322-333. doi 10.2174/157340908786786010... 

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