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Abstract  Acylthiocarbamates (ATCs) have been identified as a class of potent non-nucleoside HIV-1 reverse transcriptase (RT) inhibitors. A computational strategy based on molecular docking studies followed by comparative molecular fields analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) was used to identify the most important features impacting ATC antiretroviral activity. The CoMSIA model proved to be the more predictive, with r 2 ncv = 0.89, r cv 2 = 0.38, standard error of estimate (SEE) = 0.494, F = 84, and r 2 pred = 0.81. The results of these studies will be useful in designing new ATCs with improved potency, also against clinically relevant resistant mutants. Figure Docking of the most active acylthiocarbamate into the non-nucleoside reverse transcriptase inhibitor binding site [ABSTRACT FROM AUTHOR]

Abstract  Symmetric formimidoester disulfides (DSs) have recently been identified as a new class of potent non-nucleoside HIV-1 reverse transcriptase (RT) inhibitors. Given that three geometric isomers for DSs are possible, a computational strategy based on molecular docking studies, followed by comparative molecular fields analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) was used in order to identify the most probable DS isomer interacting with RT, to elucidate the atomic details of the RT/DS interaction, and to identify key features impacting DS antiretroviral activity. The CoMFA model was found to be the more predictive, with values of $${\text{r}}_{{\text{ncv}}}^{\text{2}} = {\text{0}}{\text{.95}}$$, $${\text{r}}_{{\text{cv}}}^{\text{2}} = {\text{0}}{\text{.482}}$$, SEE = 0.264, F = 80, and $${\text{r}}_{{\text{pred}}}^{\text{2}} = {\text{0}}{\text{.73}}$$. Figure Selected docking pose of the E,Z isomer of compound 15into the NNIBS [non-nucleoside reverse transcriptase (RT) inhibitor (NNRTI) binding site]. The RT surface electrostatic distribution (Connolly surface) is shown. Green areas are related to hydrophobic region while magenta areas indicate for H-bond regions [ABSTRACT FROM AUTHOR]

Abstract  In order to elucidate the structural requirements for human CB1 receptor antagonism, 78 antagonists belonging to five different chemical classes were selected from the literature and docked into the receptor binding site, built by homology modeling techniques. To further explore the structure-activity relationships within the considered chemical classes, a pharmacophore model and a QSAR analysis were developed. In a first step five alignments, one for each group of compounds were generated. All of them were then submitted to a MOE pharmacophore search in order to obtain a final pharmacophore model representative of the whole dataset which was used to elaborate the following 3D-QSAR analysis, by means of the CoMFA methodology. The results of these investigations are expected to be useful in the process of design and development of new potent CB1 antagonists. Figure Compounds 1-78 are aligned into the putative CB1 receptor binding site. The three key features shared by all of them are reported in coloured spheres. The hydrophobic/aromatic ones are depicted in purple while the acceptor functions are coloured in blue. [ABSTRACT FROM AUTHOR]