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GRID probe

GRID probe Catalyst feature GRID IEa) CiTest weight... [Pg.157]

A careful pretreatment is necessary to focus on the relevant variables. Often variables with low absolute values (<0.01 kcal moT ) and those with low standard deviations (<0.02-0.03kcal mol" ) are removed in order to eliminate noise. Autoscaling is not recommended, since all the data comes from the same source (GRID probe-target interaction energies) and all the data are expressed in the same units (kcalmof ). Thus, autoscaling might introduce noise in the model. [Pg.50]

The first study to investigate selectivity profiles using MIFs in connection with a chemometric analysis was published about 10 years ago [5]. There, the behavior of all 64 possible DNA triplets with respect to 31 GRID probes was studied with GRID/PCA. [Pg.60]

Figure 3.9. x-Variable distribution for the 10 grid probes in the P pocket after BUW. Blue dots indicate energies in thrombin, red dots in trypsin, and green dots in factor Xa. [Pg.65]

Figure 4.7. The complementaiy site points used for pharmacophore fingerprint calculations (lower right), together with the energetically favorable contours from 5 GRID probes on a FactorXa binding site. Figure 4.7. The complementaiy site points used for pharmacophore fingerprint calculations (lower right), together with the energetically favorable contours from 5 GRID probes on a FactorXa binding site.
The descriptors developed to characterize the substrate chemotypes are obtained from a mixture of molecular orbital calculations and GRID probe-pharmacophore recognition. Molecular orbital calculations to compute the substrate s electron density distribution are the first to be performed. All atom charges are determined using the AMI Hamiltonian. Then the computed charges are used to derive a 3D pharmacophore based on the molecular electrostatic potential (MEP) around the substrate molecules. [Pg.281]

Figure 12.5. All the substrate atoms are classified into GRID probe categories depending on their hydrophobic, hydrogen-bond donor or acceptor capabilities. Starting from a randomly chosen atom their distances in the space are then binned and transformed into clustered distances. One set of descriptors is computed for each atom type category hydrophobic, hydrogen-bond acceptor and... Figure 12.5. All the substrate atoms are classified into GRID probe categories depending on their hydrophobic, hydrogen-bond donor or acceptor capabilities. Starting from a randomly chosen atom their distances in the space are then binned and transformed into clustered distances. One set of descriptors is computed for each atom type category hydrophobic, hydrogen-bond acceptor and...

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See also in sourсe #XX -- [ Pg.48 ]

See also in sourсe #XX -- [ Pg.383 ]




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Descriptor GRID water probe

GRID probe interaction)

GRID probe-molecule interaction potential

GRID water probe

Pharmacophore GRID probe

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