Descriptor correlation

P-gp substrate 22 substrates and 31 nonsubstrates 115 substrates and 157 nonsubstrates 61% substrates and 81% nonsubstrates correctly predicted. Overall accuracy 72.4% Transport Caco-2 cell line Size, shape (e.g. molecular surface and glo-bularity), hydrophilic and H-bonding related descriptors correlated positively with P-gp activity, log P0/w not significant [54]... 

Fig. 1. Median partitioning and compound selection. In this schematic illustration, a two-dimensional chemical space is shown as an example. The axes represent the medians of two uncorrelated (and, therefore, orthogonal) descriptors and dots represent database compounds. In A, a compound database is divided in into equal subpopulations in two steps and each resulting partition is characterized by a unique binary code (shared by molecules occupying this partition). In B, diversity-based compound selection is illustrated. From the center of each partition, a compound is selected to obtain a representative subset. By contrast, C illustrates activity-based compound selection. Here, a known active molecule (gray dot) is added to the source database prior to MP and compounds that ultimately occur in the same partition as this bait molecule are selected as candidates for testing. Finally, D illustrates the effects of descriptor correlation. In this case, the two applied descriptors are significantly correlated and the dashed line represents a diagonal of correlation that affects the compound distribution. As can be seen, descriptor correlation leads to over- and underpopulated partitions.

A major practical issue affecting MP calculations is caused by use of correlated molecular descriptors. During subsequent MP steps, exact halves of values (and molecules) are only generated if the chosen descriptors are uncorrelated (orthogonal), as shown in Fig. 1A. By contrast, the presence of descriptor correlations (and departure from orthogonal reference space) leads to overpopulated and underpopulated, or even empty, partitions (see also Note 5), as illustrated in Fig. ID. For diversity analysis, compounds should be widely distributed over computed partitions and descriptor correlation effects should therefore be limited as much as possible. However, for other applications, the use of correlated descriptors that produce skewed compound distributions may not be problematic or even favorable (see Note 5). 

Descriptor/Descriptor Correlation is the property of an artificial molecular descriptor to correlate with at least one experimental descriptor. 

Since the mean molecular polarizability is a property that is related to the distance information in a molecule — as is the stabilization of a charge due to polarizability — it is reasonable that RDF descriptors correlate with this property. 

Degeneracy of 735 molecular descriptors as well as their pairwise correlations were estimated on the NGI database for 221,860 compounds and made available on a software module called Molecular Descriptor Correlations (MDC) [MDC - Milano Chemometrics, 2006]. 

MDC — Molecular Descriptor Correlations, Ver. 1.0, Milano Chemometrics QSAR Research Group, Univ. Milano-Bicocca, P.za. della Sdenza 1, Milano, Italy http //michem.disatunimib.it/ chm/download / molecular correlationinfo.htm. 

The same descriptor correlated well also with the acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE) enzyme inhibition activity of organophosphorus compounds. The best one-parameter correlation for the toxicity of organophosphorus compounds was achieved by using the normalized electronic moment (Me) [46]. 

To explore the relationship between molecular structure and enantioselectivity a principal component analysis with partial least squares projection techniques allowed the authors to determine which of 50 physicochemical descriptors correlated with separation factors. A partial list of variables used in their models is given in Table 4. 

The simplest means to obtain such a quantitative relationship is to use multiple linear regression (MLR) available in any statistical software package. In order to avoid statistically insignificant relationships or chance correlations, one should always apply the following rules of thumb (1) the ratio of compounds to descriptors should be >5 (2) the descriptors should not be intercorrelated (inter-descriptor correlation coefficient should be less than r2<0.5). 

Highest descriptor correlations in the co-crystal data set. Only correlations calculated for the same descriptor of both molecules in a co-crystal are given. Descriptors are defined in the text. 

Uniqueness There is no rigorous way to demonstrate that 3D-QSAR models are unique even if the alignment is experimentally determined, the use of different partial atomic charges or the use of different grid probes could lead to different, valid models. This situation occurs also in classical QSAR, when various descriptors correlate well but point to different physicochemical aspects of the system. Therefore, multiple QSAR models should always be explored. 

In Eq. (5.5), the summation rans over all SF% contributions of the carbon atom A to each fc-th C-C bcp in the benzenoid ring, k is the analogue quantity in benzene and c is a normalization constant, such that SFLAI is exactiy 0 in cyclohexane. We found that this descriptor correlates well with several other structural and quanmm... 

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