Quantitative Structure–Activity Relationship Study on the Anti‐HIV‐1 Activity of Novel 6‐Naphthylthio HEPT Analogs

Abstract

The quantitative structure-activity relationship of the novel 6-naphthylthio 1-[(2-hydroxyethoxy)methyl]-6-(phenylthio) thymine derivatives for prediction of anti-human immunodeficiency virus type 1 activity was studied. The suitable set of the molecular descriptors was calculated and the important descriptors using the variable selections of the stepwise multiple linear regression and the genetic algorithm were selected. A comparison between the attained results indicated the superiority of the genetic algorithm over the stepwise multiple regression method in the feature-selection. The predictive quality of the quantitative structure-activity relationship models was tested for an external set of eight compounds, randomly chosen out of 39 compounds. The genetic algorithm-multiple linear regression model with six selected descriptors was obtained. This model, demonstrating high statistical qualities (R(2)(train) = 0.925, Q(2) = 0.872, SE (%) = 1.23, F = 49.338, R(2)(pred) = 0.944), could predict the anti-human immunodeficiency virus type 1 activity of the molecules with a prediction error percentage lower than 10%. The results suggest that electronegativity, the masses, and the atomic van der Waals volumes are the main independent factors contributing to the anti-human immunodeficiency virus type 1 activity of the studied compounds.

A quantitative structure–activity relationship study on CXL017 derivatives as effective drugs for cancer treatment

“…However, these experimental approaches are often not cost-effective and instead are time-consuming. [8] To overcome these restrictions, quantitative structure-activity relationships (QSAR)-based techniques emerged as a proper alternative and useful tool in different disciplines of science such as drug design, medicinal chemistry, and so forth within the past few decades. [9][10][11] The models generated using different QSAR approaches are basically seeking to correlate and create a rational relationship between the molecular structures of the studied compounds and their corresponding activities or properties.…”

Invariant and Variable Supramolecular Self-Assembly in 6-Substituted Uracil Derivatives: Insights from X-ray Structures and Quantum Chemical Study

“…Pyrimidine-2,4­(1 H ,3 H )-dione (uracil) and 5-methylpyrimidine-2,4­(1 H ,3 H )-dione (thymine) represent the core pharmacophore of several chemotherapeutic agents. 6-(Arylthio)-5-substituted uracils and their derivatives were discovered early as the first chemotherapeutic agents against human immunodeficiency virus type 1 (HIV-1) acting by inhibition of reverse transcriptase. − …”

Quantitative structure–activity relationship (QSAR) study of interleukin-1 receptor associated kinase 4 (IRAK-4) inhibitor activity by the genetic algorithm and multiple linear regression (GA-MLR) method

“…Thus, the input data set must be adequately split by experimental design or other splitting procedures into representative training and validation/test sets [22][23][24]. In the present work, the data splitting was performed randomly and was confirmed by the factor spaces of the descriptors, as in our previous work [10,[16][17][18]25,26]. Finally, the accuracy of the proposed model was illustrated using the following: leave one out, bootstrapping and external test set, cross-validations and Y-randomisation techniques.…”

“…QSAR studies can express the biological activities of compounds as a function of their various structural parameters and also describes how the variation in biological activity depends on changes in the chemical structure [9]. Recently, a QSAR study of biological activity has been published by our group [10][11][12]. If such a relationship can be derived from the structure-activity data, the model equation allows medicinal chemists to say with some confidence which properties are important in the mechanism of drug action.…”