GRID descriptor

Besides the aforementioned descriptors, grid-based methods are frequently used in the field of QSAR quantitative structure-activity relationships) [50]. A molecule is placed in a box and for an orthogonal grid of points the interaction energy values between this molecule and another small molecule, such as water, are calculated. The grid map thus obtained characterizes the molecular shape, charge distribution, and hydrophobicity. 

For the calculation of grid-based descriptors it is necessary to align the ligands in the first step. If the molecules have the same skeleton, the alignment step is not critical. Otherwise, the ahgnment may be biased by the user. 

Once the molecules are aligned, a molecular field is computed on a grid of points in space around the molecule. This field must provide a description of how each molecule will tend to bind in the active site. Field descriptors typically consist of a sum of one or more spatial properties, such as steric factors, van der Waals parameters, or the electrostatic potential. The choice of grid points will also affect the quality of the final results. 

Cluster sampling methods, which first identify a set of compound clusters, followed by the selection of several compounds from each cluster [73]. Grid-based sampling, which places all the compounds into a low-dimensional descriptor space divided into many cells and then chooses a few compounds from each cell [74]. 

Pastor, M., Cruciani, G., McLay, L, Pickett, S., Glementi, S. GRid-INdependent descriptors (GRIND) a novel class of alignment-independent three-dimensional molecular descriptors. /. Med. Chem. 2000, 43, 3233-3243. 

Another set of useful 3D-based descriptors for predicting intestinal absorption is through the use of the GRID program. Applications of these descriptors are discussed in Chapter 4. 

In the following section, the calculation of the VolSurf parameters from GRID interaction energies will be explained and the physico-chemical relevance of these novel descriptors demonstrated by correlation with measured absorption/ distribution/metabolism/elimination (ADME) properties. The applications will be shown by correlating 3D molecular structures with Caco-2 cell permeabilities, thermodynamic solubilities and metabolic stabilities. Special emphasis will be placed on interpretation of the models by multivariate statistics, because a rational design to improve molecular properties is critically dependent on an understanding of how molecular features influence physico-chemical and ADME properties. 

Once the protein interaction pattern is translated from Cartesian coordinates into distances from the reactive center of the enzyme and the structure of the ligand has been described with similar fingerprints, both sets of descriptors can be compared [25]. The hydrophobic complementarity, the complementarity of charges and H-bonds for the protein and the substrates are all computed using Carbo similarity indices [26]. The prediction of the site of metabolism (either in CYP or in UGT) is based on the hypothesis that the distance between the reactive center on the protein (iron atom in the heme group or the phosphorous atom in UDP) and the interaction points in the protein cavity (GRID-MIF) should correlate to the distance between the reactive center of the molecule (i.e. positions of hydrogen atoms and heteroatoms) and the position of the different atom types in the molecule [27]. 

The fields that are derived on a grid can be encoded into lengthy binary [167] or real-valued descriptors [147]. Also, an abstract description as the so-called field graphs has been attempted [197]. Another approach to convert fields back into linear descriptors is to extract the characteristic features [198]. 

Fig. 14.5 Computation of VolSurf descriptors [155, 156] derived from GRID molecular interaction fields. Interactions of the example molecule with a water and dry probe at different contour levels are used to compute a vector of 72 volume-, size- and surface-based descriptors.

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