The Craig plot

The Craig plot is nothing but an actual plot between the 71 factor taken along the X-axis and the O factor taken along the Y-axis, thereby having a clear and vivid idea with regard to the relative properties of different fimctional moieties (substituents). 

The various advantageous salient features of a Craig plot are enumerated as 

Interestingly, in the same vein, the various fimctional moieties that are located on the horizontal line , for instance methyl, ethyl tert-butyl on one hand whereas, carboxy, chloro, bromo, and iodo moieties on the other can be regarded and identified as being isoelectric in nature or possessing identical a values. 

In case, the Hansch equation rightfully demands that +ve 0 and -n values are an absolute necessity, additional relevant substituents must be picked up from the top-left quadrant. 

The Topliss scheme is nothing but an organized flow diagram which categorically permits such a procedure to be adopted with a commendable success rate. 

In this example, a series of substituents would have to be chosen where tt and MR are not related. The substituents H, Me, OMe, NHCOCH2, I, and CN would be more suitable. 

Although tables of tt and a factors are readily available for a large range of substituents, it is often easier to visualize the relative properties of different substituents by considering a plot where they axis is the value of the or factor and the x axis is the value of the tt factor. Such a plot is known as a Craig plot. The example shown in Fig. 

16 is the Craig plot for the a and 7r factors of para-aromatic substituents. There are 

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The Craig plot is useful in planning which substituents should be used in a QSAR study. In order to derive the most accurate equation involving tt and a, analogues should be synthesized with substituents from each quadrant. For example, halide substituents are useful representatives of substituents with increased hydrophobicity... 

The right substituent choice minimahzes the number of test compounds that have to be synthesized to insnre a significant space volume. This point represents a 3D extension of the Craig plot discnssed by Craig" and by Anstel. In this context, the decision tree proposed by Topliss allows a fast identification of the snbstitnents associated with the highest potency. Application examples of the Topliss scheme are discussed by Martin and Dnnn. ... 

Fig. 2.7 illustrates the Craig plot of various para aromatic substituents for the a and n factors respectively. 

Fig. 2.7 The Craig Plot for the G and K Factors ofpara-Aromutic Substituents.

The Craig plot in Fig. 2.6 evidently depicts that there is absolutely no clearly defined overall relationship between the two key factors O and it. However, the various functional moieties (i.e., substituents) are strategically positioned around all the four quadrants of the plot based on their inherent physicochemical status and integrity. 

The Craig plot may also be exploited to compare the MR and hydrophobicity. 

Another way to identify correlations is to plot the values of the parameters in graphical form this can help to identify any correlations and the presence of outliers. A Craig plot is a two-dimerrsional scatterplot of one parameter against another ideally, the molecules should sample from all four quadrants of the plot. 

Craig plots are two dimensional plots of one parameter against another (Figure 4.6). The plot is divided into four sections corresponding to the positive and negative values of the parameters. They are used, in conjunction with an already established Flansch equation for a series of related aromatic compounds, to select the aromatic substituents that are likely to produce highly active... 

It is also important to make enough structures to make the results statistically meaningful. As a rule of thumb, five structures should be made for every parameter studied. Typically, the initial QSAR study would involve the two parameters tt and a, and possibly Es. Craig plots could be used in order to choose suitable substituents. 

Various strategies have been advocated in order to cover the physicochemical parameter space of a series of new compounds as well as possible. Familiar strategies go back to proposals by Topliss and Craig. Both are schemes used for substituent variation at a selected site. The Topliss substitution scheme can be used to optimize aromatic and aliphatic substituents using a fixed set of substituents and rules. A Craig plot is a 2D plot of selected descriptors, for example, Hammett electronic properties) and Hansch 7T values (lipophilicity). Substituents can be selected from each quadrant of this plot such that they vary widely in their properties, for example, lipophilic and hydrophilic, electron-donor and electron-acceptor, and to ensure the two properties are not correlated in the selected set which is preferable for the generation of stable QSAR models. 

A further extension would be to consider a 3D Craig plot using three descriptors, for example, reflecting steric, lipophilic and electronic properties of the substituents. In that case, substituents may be chosen from the eight octants. If one wants to consider even more descriptors, this approach becomes impractical. In that case, more advanced experimental design techniques may be applied. One approach taken by Hansch and Leo was to use CA to define sets of aliphatic and aromatic substituents useful in the design of compounds for synthesis, such that various aspects of the substituents are taken into account in a balanced way. ... 

Hansch analysis tries to correlate biological activity with physico-chemical properties by linear and nonlinear regression analysis, finding property-activity relationship models. A Craig plot is a plot of two substituent parameters (e.g., Hansch-Fujita n and Hammett a values). The simplest Hansch analysis is based on the Hansch linear model [Kubinyi, 1988b], defined... 

From the above Craig plot one may obviously identify the substituents that are particularly responsible for +ve n and 0 parameters, -ve n and a parameters, and lastly one +ve and one -ve parameter. 

Figure 1. A Craig plot of r versus a values for all 27 substituents Included in the present investigation. Note that skewing to the + r quadrant resulted as a consequence of our finding that increased llpophilicity enhances affinity, thus leading to the synthesis of a greater number of such derivatives.

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