Quantitative Structure–Activity Relationship Analysis of Some Thiourea Derivatives with Activities Against HIV‐1 (IIIB)

Abstract

Two-dimensional (2D) and Three-dimensional (3D) Quantitative Structure -Activity Relationship (QSAR) studies have been carried out on a series of 42 recently synthesized thiourea derivatives to find out the structural requirements of their protection of MT-4 cells against Human Immunodeficiency Virus (HIV)-1 (IIIB). The statistically significant 2D-QSAR model (r 2 ¼ 0.897) was developed by Genetic Function Approximation (GFA) when the number of descriptors in equation was set to four, indicating descriptors of S_aaCH, Shadow_XYfrac, Lowest Unoccupied Molecular Orbital (LUMO), and Hydrogen-Bond Acceptors (Hbond Acceptor) mainly control the bioactivity. The validation of the model was done by the full cross-validation tests, randomization tests, and external test set prediction. Molecular Field Analysis (MFA) investigated the substitutional requirements for the favorable receptor -drug interaction and constructed the best 3D-QSAR model using Genetic Partial Least Squares (G/PLS) method, showing that the electrostatic fields contribute significantly toward bioactivity. The results obtained by combining both methodologies give insight into the key features for designing more potent analogs against HIV-1(IIIB).

Quantitative Structure‐property Relationship Studies on Amino Acid Conjugates of Jasmonic Acid as Defense Signaling Molecules

“…A brute force approach was first used to investigate the number of descriptors necessary and adequate for the QSPR equation. As the number of descriptors in the equation increased one by one, the effect of added new terms was evaluated using cross‐validated r 2 ( r 2 CV ) as the limiting factor for the number of descriptors to be used in the model (Chen et al 2008; Nair and Sobhia 2008; Li et al 2008c, 2009). As shown in Table 2, adding the number of descriptors in the equation does increase the r 2 CV value of the best model, but r 2 CV and conventional r 2 increase a little when the number of descriptors ranges from 4 to 5.…”

“…From the cross‐validation test r 2 CV of 0.987 indicated that the results obtained were not by chance correlation. The randomization tests (Deswal and Roy 2006; Chen et al 2008; Li et al 2008a, 2008c, 2009) were carried out at 90% (nine trials), 95% (19 trials), 98% (49 trials) and 99% (99 trials) confidence levels and carried out by repeatedly permuting the dependent variable set. The results of randomization tests (Table 4) showed that none of the permuted datasets produced the random r comparable to non‐random r of 0.995, suggesting that the value obtained for the original GFA method‐derived model was significant.…”

Cluster Analysis and QSAR Study of Some Anti‐hepatitis B Virus Agents Comprising 4‐Aryl‐6‐chloro‐quinolin‐2‐ones and 5‐Aryl‐7‐chloro‐1,4‐benzodiazepines

“…The predictive power of the model was calculated by 2 pred r ＝(SD-PRESS)/SD, 6,34,35 where SD is the sum of squared deviations between the pIC 50 of each molecule and the mean pIC 50 of the molecules in the training set and PRESS is the sum of squared deviations between the predicted and calculated pIC 50 values for each molecule in the test set. The high 2 pred r value of 0.989 for the test set accounts for good predictive ability of model (1).…”

“…2 The selection of the best model 28 was based on the values of LOF (Friedman's Lack of Fit), r 2 (square of the correlation coefficient), tion coefficient), F-Test, LSE (least square error), 2 CV r (cross-validated r 2 ), 2 BS r (bootstrap correlation coefficient) and PRESS (predicted sum of deviation squares). A brute force approach [33][34][35] was first employed to investigate the number of descriptors necessary and adequate for the QSAR equation. As shown in Table 3, adding the number of descriptors in the equation does increase the r 2 and 2 CV r values of the best model.…”

Oxyhalogen-sulfur chemistry: Kinetics and mechanism of oxidation of n-acetylthiourea by aqueous bromate and acidified bromate

“…For example, comparatively, the 4-aminoquinoline pharmacophore has been exploited in a variety of ways to derive antimalarials [24][25][26] , but it is exclusively for one disease and has not found significant use for any other disease. The ease of synthesis of substituted thioureas [27][28][29][30][31][32][33] means that there are now hundreds of these analogues available which have not yet been characterized. 7,34 Although effective, drugs containing the thiourea functional group have been found to exhibit some toxicity.…”