Design, synthesis and activity evaluation of novel peptide fusion inhibitors targeting HIV-1 gp41

Molecular Docking and QSAR Study of 2-Benzoxazolinone, Quinazoline and Diazocoumarin Derivatives as Anti-HIV-1 Agents

A series of 2-benzoxazolinone, diazocoumarin and quinazoline derivatives have been shown to inhibit HIV replication in cell culture. To understand the pharmacophore properties of selected molecules and design new anti-HIV agents, quantitative structure–activity relationship (QSAR) study was developed using a descriptor selection approach based on the stepwise method. Multiple linear regression method was applied to relate the anti-HIV activities of dataset molecules to the selected descriptors. Obtained QSAR model was statistically significant with correlation coefficient R² of 0.84 and leave one out coefficient Q² of 0.73. The model was validated by test set molecules giving satisfactory prediction value (R²_test) of 0.79. Molecules also were docked on HIV integrase enzyme and showed important interactions with the key residues in enzyme active site. These data might be helpful for design and discovery of novel anti-HIV compounds.

Quantitative Structure Activity/Pharmacokinetics Relationship Studies of HIV-1 Protease Inhibitors Using Three Modelling Methods

BACKGROUND

HIV-1 protease inhibitor (PIs) is a good choice for AIDS patients. Nevertheless, for PIs, there are several bugs in clinical application, like drug resistance, the large dose, the high costs and so on, among which, the poor pharmacokinetics property is one of the important reasons that leads to the failure of its clinical application.

OBJECTIVE

We aimed to build computational models for studying the relationship between PIs structure and its pharmacological activities.

METHODS

We collected experimental values of k_off/K_i and structures of 50 PIs through a careful literature and database search. Quantitative structure activity/pharmacokinetics relationship (QSAR/QSPR) models were constructed by support vector machine (SVM), partial-least squares regression (PLSR) and back-propagation neural network (BPNN).

RESULTS

For QSAR models, SVM, PLSR and BPNN all generated reliable prediction models with the r² of 0.688, 0.768 and 0.787, respectively, and r²_pred of 0.748, 0.696 and 0.640, respectively. For QSPR models, the optimum models of SVM, PLSR and BPNN obtained the r² of 0.952, 0.869 and 0.960, respectively, and the r²_pred of 0.852, 0.628 and 0.814, respectively.

CONCLUSION

Among these three modelling methods, SVM showed superior ability than PLSR and BPNN both in QSAR/QSPR modelling of PIs, thus, we suspected that SVM was more suitable for predicting activities of PIs. In addition, 3D-MoRSE descriptors may have a tight relationship with the Ki values of PIs, and the GETAWAY descriptors have significant influence on both koff and Ki in PLSR equations.

Targeted microbicides for preventing sexual HIV transmission

Sexual transmission remains one of the most significant hurdles in the fight against HIV infection. The use of vaginal or rectal microbicides has been proposed for topical pre-exposure prophylaxis but available results from clinical trials of candidate products have been, at best, less than optimal. While waiting for the first product to get regulatory approval, novel approaches are being explored in order to enhance efficacy, as well as to assure safety. Strategies involving specific delivery of antiviral agents to key players involved in the early steps of sexual transmission have the potential to help achieving such purposes. Engineering systems that allow targeting cells, tissues or other biological structures of interest may provide a way to modulate local pharmacokinetics of promising microbicide molecules and, thus, maximize protection. This concise review discusses the identification and use of potential targets for such purpose, while detailing on several examples of targeted systems engineered as potential microbicide candidates. Furthermore, remaining challenges and hints for future work in the field of targeted microbicides are addressed.

Structure–activity relationship and binding mode studies for a series of diketo-acids as HIV integrase inhibitors by 3D-QSAR, molecular docking and molecular dynamics simulations

We explored the main factors affecting the activity of compounds by different statistical and computational methods.