Anti-HIV (human immunodeficiency virus) drug discovery has been increasingly focusing on HIV integrase (IN) as a potential therapeutic target. This enzyme is required for the integration of reverse transcribed proviral DNA into the host cell's genome and is essential for the propagation of the HIV life cycle. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) three-dimensional quantitative structure-activity relationship (3D QSAR) studies and docking simulations were conducted on a series of potent conformationally restrained cinnamoyl inhibitors of HIV-1 IN (Artico; et al. J. Med. Chem. 1998, 41, 3948-3960). Predictive 3D QSAR models were established using SYBYL multifit molecular alignment rule, which had conventional r(2) and cross-validated coeffiecient (q(2)) values up to 0.981 and 0.721 for CoMFA and 0.975 and 0.804 for CoMSIA, respectively. These models were validated by an external test set (Burke; et al. J. Med. Chem. 1995, 38, 4171-4178). CoMFA and CoMSIA 3D QSAR models were also derived using a molecular alignment obtained by docking the compounds into the active site of HIV IN. These latter models were comparable to multifit-derived models in terms of relative descriptor field contributions and the partial least squares (PLS) contour maps. The CoMSIA 3D QSAR models performed better than the CoMFA models. The superior performance of CoMSIA was attributed to the large contribution of hydrogen-bonding interactions to the inhibitory activity differences among the compounds. This was supported by FlexX binding energy scores that correlated well with the inhibitory activity differences between hydroxylated compounds and their corresponding methoxy or deoxy counterparts. The CoMFA and CoMSIA PLS contour maps and MOLCAD-generated active site electrostatic, lipophilicity, and hydrogen-bonding potential surface maps, as well as the docking results, were integrated to propose a binding mode for the cinnamoyl inhibitors at the active site of HIV-1 IN.

Parkinson's disease (PD), a neurodegenerative disorder, is the second most common neurological illness in United States. Neurologically, it is characterized by the selective degeneration of a unique population of cells, the nigrostriatal dopamine neurons. The current treatment is symptomatic and mainly involves replacement of dopamine deficiency. This therapy improves only motor symptoms of Parkinson's disease and is associated with a number of adverse effects including dyskinesia. Therefore, there is unmet need for more comprehensive approach in the management of PD. Cannabis and related compounds have created significant research interest as a promising therapy in neurodegenerative and movement disorders. In this review we examine the potential benefits of medical marijuana and related compounds in the treatment of both motor and nonmotor symptoms as well as in slowing the progression of the disease. The potential for cannabis to enhance the quality of life of Parkinson's patients is explored.

An essential step in the HIV life cycle is integration of the viral DNA into the host chromosome. This step is catalyzed by a 32-kDa viral enzyme HIV integrase (IN). HIV-1 IN is an important and validated target, and the drugs that selectively inhibit this enzyme, when used in combination with reverse transcriptase (RT) and protease (PR) inhibitors, are believed to be highly effective in suppressing the viral replication. IN catalyzes two discrete enzymatic processes referred to as 3' processing and DNA strand transfer. As a part of a study to optimize new lead molecules we previously identified from a series of 2-mercaptobenzenesulfonamides (MBSAs), we applied three-dimensional quantitative structure-activity relationship methods, comparative molecular field analysis (CoMFA), and comparative molecular similarity indices analysis (CoMSIA) to training sets of up to 66 compounds. Two different conformational templates were used: Conf-d, obtained from docking into the HIV-1 IN active site and Conf-s obtained by a systematic conformational search, using lead compounds 1 and 14, respectively. Reliable models of good predictive power were obtained after removal of compounds with high residuals. The Conf-s models tended to perform better than the Conf-d models. Cross-validated coefficients (q(2)) of up to 0.719 (strand transfer CoMSIA, Conf-s) regression coefficients (r(2)) of up to 0.932 (strand transfer CoMSIA, Conf-d) were obtained, with the number of partial least squares (PLS) components varying from 3 to 6, and the number of outliers being 4 in most of the models. Because all biological data were determined under exactly the same conditions using the same enzyme preparation, our predictive models are promising for drug optimization. Therefore, these results combined with docking studies were used to guide the rational design of new inhibitors. Further synthesis of 12 new analogues was undertaken, and these were used as a test set for validation of the quantitative structure-activity relationship (QSAR) models. For compounds with closely related structures, binding energies given by the FlexX scoring function correlated with HIV-1 IN inhibitory activity.