Explore chapters and articles related to this topic
Dependence and Independence: Structures, Testing, and Measuring
Published in Albert Vexler, Alan D. Hutson, Xiwei Chen, Statistical Testing Strategies in the Health Sciences, 2017
Albert Vexler, Alan D. Hutson, Xiwei Chen
Bolboaca and Jäntschi (2006) studied a sample of 67 pyrimidine derivatives with inhibitory activity on Escherichia coli dihydrofolate reductase (DHFR) by the use of molecular descriptor families on structure–activity relationships. The use of Pearson, Spearman, Kendall, and gamma correlation coefficients in the analysis of structure–activity relationships of biologic active compounds was studied and presented.
Lead optimization of 4-(thio)-chromenone 6-O-sulfamate analogs using QSAR, molecular docking and DFT – a combined approach as steroidal sulfatase inhibitors
Published in Journal of Receptors and Signal Transduction, 2021
The energy minimized compounds were subjected to molecular descriptor calculation for calculating 2D descriptors using PaDEL freeware version 2.21 [25]. A large number of descriptors were calculated and the variables were pre-filtered by deleting all the missing values and excluding the zero values to avoid correlation among the descriptors. Furthermore, pairwise correlation was used to filter out the descriptors with more than 0.70 values. From the correlation matrix (Table 2) obtained after filtering all the excluded descriptors, the electrotopological 2D descripotrs BCUTp-1h, SdssC and maxHBa [26] showed greater correlation with activity. The major contributing features toward STS inhibition in a thiochromenone nucleus are hydrophobic and electronic features. The detailed descriptor analysis that contributes for maximum potency is BCUTp-1h which is the nlow highest polarizability weighted BCUTS, SdssC is the sum of atom type E-states for (strong) hydrogen bond acceptors.The best models developed from hydrophobic and E-state descriptors after conducting many trial models are presented here.
QSPR modelling of in vitro degradation half-life of acyl glucuronides
Published in Xenobiotica, 2019
For the aromatic acids class, half-lives of meta- and para- substituted benzoic acid AGs were asserted to be correlated with the pKa of the corresponding parent compounds (Camilleri et al., 2017). We also determined a correlation (R = 0.40) between the half-lives of the aromatic AGs and the pKa of the compounds within the class. For the low pKa values, the half-lives are short, the most probable indication of the hydrolysis of the AGs. We then attempted to find a more representative molecular descriptor comprising all aromatic AGs (30 compounds) by searching in the descriptor pool. A DRAGON descriptor, R3v was found to be highly correlated (R = 0.78) with the half-lives. This descriptor is among the GETAWAY (Geometry, Topology and Atom Weights AssemblY) descriptors calculated as R autocorrelation of lag 3/weighted by van der Waals volume of the molecule. GETAWAY descriptors provide geometrical information of the molecule enriched with various atomic weighting schemes (Consonni et al., 2002). The van der Waals volume of a molecule is an important characteristic that plays a major role in the binding of molecules. For example, it was previously used in the prediction of plasma protein binding of drugs (Ghafourian & Amin, 2013) and the binding to adenosine receptor (Perez Gonzalez et al., 2006).
Quantitative structure–activity relationship models for compounds with anticonvulsant activity
Published in Expert Opinion on Drug Discovery, 2019
Carolina L. Bellera, Alan Talevi
Quantitative Structure–Activity Relationships (QSAR) have become a cornerstone in the drug discovery and Medicinal Chemistry fields, where they can be used to explain the differences in the activity of congeneric series, identify novel bioactive scaffolds (through virtual screening) and drive the design and optimization of new drug candidates [8–10]. QSAR methods attempt to establish a correlation between molecular features and/or physicochemical properties (numerically captured into molecular descriptors), and biological properties, reflected either as a continuous or a categorical variable [8,9]. Probably, the most popular definition of a molecular descriptor belongs to Consonni and Todeschini, ‘the molecular descriptor is the final result of a logic and mathematical procedure which transforms chemical information encoded within a symbolic representation of a molecule into a useful number or the result of some standardized experiment’ [11].