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      2D, 3D-QSAR and docking studies of 1,2,3-thiadiazole thioacetanilides analogues as potent HIV-1 non-nucleoside reverse transcriptase inhibitors

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          Abstract

          Background

          The discovery of clinically relevant inhibitors of HIV-RT for antiviral therapy has proven to be a challenging task. To identify novel and potent HIV-RT inhibitors, the quantitative structure–activity relationship (QSAR) approach became very useful and largely widespread technique forligand-based drug design.

          Methods

          We perform the two- and three-dimensional (2D and 3D) QSAR studies of a series of 1,2,3-thiadiazole thioacetanilides analogues to elucidate the structural properties required for HIV-RT inhibitory activity.

          Results

          The 2D-QSAR studies were performed using multiple linear regression method, giving r 2 = 0.97 and q 2 = 0.94. The 3D-QSAR studies were performed using the stepwise variable selection k-nearest neighbor molecular field analysis approach; a leave-one-out cross-validated correlation coefficient q 2 = 0.89 and a non-cross-validated correlation coefficient r 2 = 0.97 were obtained. Docking analysis suggests that the new series have comparable binding affinity with the standard compounds.

          Conclusions

          This approach showed that hydrophobic and electrostatic effects dominantly determine binding affinities which will further useful for development of new NNRTIs.

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          Most cited references11

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          Validation of the general purpose tripos 5.2 force field

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            Novel variable selection quantitative structure--property relationship approach based on the k-nearest-neighbor principle

            A novel automated variable selection quantitative structure-activity relationship (QSAR) method, based on the kappa-nearest neighbor principle (kNN-QSAR) has been developed. The kNN-QSAR method explores formally the active analogue approach, which implies that similar compounds display similar profiles of pharmacological activities. The activity of each compound is predicted as the average activity of K most chemically similar compounds from the data set. The robustness of a QSAR model is characterized by the value of cross-validated R2 (q2) using the leave-one-out cross-validation method. The chemical structures are characterized by multiple topological descriptors such as molecular connectivity indices or atom pairs. The chemical similarity is evaluated by Euclidean distances between compounds in multidimensional descriptor space, and the optimal subset of descriptors is selected using simulated annealing as a stochastic optimization algorithm. The application of the kNN-QSAR method to 58 estrogen receptor ligands as well as to several other groups of pharmacologically active compounds yielded QSAR models with q2 values of 0.6 or higher. Due to its relative simplicity, high degree of automation, nonlinear nature, and computational efficiency, this method could be applied routinely to a large variety of experimental data sets.
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              Dimerization inhibitors of HIV-1 reverse transcriptase, protease and integrase: a single mode of inhibition for the three HIV enzymes?

              The genome of human immunodeficiency virus type 1 (HIV-1) encodes 15 distinct proteins, three of which provide essential enzymatic functions: a reverse transcriptase (RT), an integrase (IN), and a protease (PR). Since these enzymes are all homodimers, pseudohomodimers or multimers, disruption of protein-protein interactions in these retroviral enzymes may constitute an alternative way to achieve HIV-1 inhibition. A growing number of dimerization inhibitors for these enzymes is being reported. This mini review summarizes some approaches that have been followed for the development of compounds that inhibit those three enzymes by interfering with the dimerization interfaces between the enzyme subunits.
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                Author and article information

                Journal
                Org Med Chem Lett
                Org Med Chem Lett
                Organic and Medicinal Chemistry Letters
                Springer
                2191-2858
                2012
                12 June 2012
                : 2
                : 22
                Affiliations
                [1 ]Institute of pharmacy, Nirma University, Ahmedabad, Gujarat, 382481, India
                [2 ]R. C. Patel Institute of Pharmaceutical Education and Research, Shirpur, Dhule District, Maharashtra, 425405, India
                Article
                2191-2858-2-22
                10.1186/2191-2858-2-22
                3495901
                22691718
                fad0660c-f8ea-4b41-af43-4cd1c30c4ef8
                Copyright ©2012 Jain et al.; licensee Springer.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 13 December 2011
                : 17 April 2012
                Categories
                Original Article

                Pharmaceutical chemistry
                1,2,3-thiadiazole thioacetanilides,hiv-rt inhibitors;k-nearest neighbor molecular field analysis (knn-mfa),qsar, docking

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