Sampling Scoring

Throughout this chapter, we roughly separate docking approaches by their treatment of protein flexibility. Within the two broad categories (rigid body and flexible docking), the docking problem can be separated into two subproblems  

The sampling problem Given two independent protein structures, generate putative structures of the complex. 

The scoring problem Given a set of putative complexes, rank them by estimating their free energy of binding. 

A plethora of techniques has been employed to address the sampling problem, ranging from complete enumeration of the relative orientations of the rigid binding partners to methods based on effective energy gradients to determine new atomic positions. 

A more detailed approach to scoring is to compute a molecular mechanics (MM) potential energy for the enthalpic part of the binding free energy typically, such a function contains the following terms  

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Method Ligand jfexibiUty sampling Scoring function... 

Fig. 9 Composition of the identified patterns of contamination (loadings) in surface and groundwater of the Ebro River basin and patterns contribution to the analyzed samples (scores) from year 2004 to 2006. Samples ordered for both compartments from first to sixth sampling campaigns and, for each campaign, from NW to SE. Campaigns 1,3, and 5 sampled in summer and 2, 4, and 6 sampled in fall...

P.R.146 also shows good lightfastness in textile printing. 1/1 SD prints equal step 7 on the Blue Scale, while 1/3 SD samples score step 6-7 and are therefore somewhat less lightfast than those of the yellower P.R.7, but superior to the likewise yellower P.R.170. Wheatherfastness in print, however, is much inferior to that of P.R.7 and 170. P.R.146 prints are not entirely stable to dry cleaning and dry heat they match step 4 on the 5 step evaluation scale. 

The production of P. Y. 187 has recently been discontinued. It was a special-purpose pigment for polyamide. Thermostable up to 320°C in this plastic material, the pigment furnishes greenish yellow shades. 1/1 SD samples score only as high as step 4 on the Blue Scale for lightfastness. 

Pattern recognition studies on complex data from capillary gas chromatographic analyses were conducted with a series of microcomputer programs based on principal components (SIMCA-3B). Principal components sample score plots provide a means to assess sample similarity. The behavior of analytes in samples can be evaluated from variable loading plots derived from principal components calculations. A complex data set was derived from isomer specific polychlorinated biphenyl (PCBS) analyses of samples from laboratory and field studies. 

Four levels of pattern recognition have been defined by Albano (2). Levels I and II are most frequently used to determine the similarity of objects, or to characterize clusters of samples and to classify unknown objects. Level III takes advantage of the reduction of data dimensions resulting from SIMCA and seeks to establish a correlation of sample scores with independent variables... 

The sample scores (Theta-1, Theta-2, and Theta-3) in each component were used to represent the samples in a 3-D... 

For the SIMCA analyses, the individual PCB isomer concentrations were normalized to sum 100. We examined the data by using the SIMCA-3B program to calculate principal components and to plot sample scores in a manner identical to that discussed for the Aroclor mixtures. The plot of sample data illustrates that the geographic locations have different residue profiles (Figure 5). 

Figure 1. Analysis of the relationships between (a) compositional and sensory variables and (b) cultivars in terms of these variables, (a) Loadings of the 6 sensory and 14 compositional variables (Table I) on first (horizontal) and second (vertical) principal components, (b) Sample scores of the first (horizontal) and second (vertical) principal components of raspberry cultivars (Table II).

Note This is only a sample scoring scale. Scoring scales differ from exam to exam. 

Figure 4. Partial least squares analysis of twelve glycoside hydrolysates, sensory attribute ratings and volatile compound concentration (normalised) a) component loadings, and b) sample scores. For explanation of codes see Tables II and IV.

Using the test sample scores in a calibration model... 

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