INI1/SMARCB1 binds to HIV-1 integrase (IN) through its Rpt1 domain and exhibits multifaceted role in HIV-1 replication. Determining the NMR structure of INI1-Rpt1 and modeling its interaction with the IN-C-terminal domain (IN-CTD) reveal that INI1-Rpt1/IN-CTD interface residues overlap with those required for IN/RNA interaction. Mutational analyses validate our model and indicate that the same IN residues are involved in both INI1 and RNA binding. INI1-Rpt1 and TAR RNA compete with each other for IN binding with similar IC50 values. INI1-interaction-defective IN mutant viruses are impaired for incorporation of INI1 into virions and for particle morphogenesis. Computational modeling of IN-CTD/TAR complex indicates that the TAR interface phosphates overlap with negatively charged surface residues of INI1-Rpt1 in three-dimensional space, suggesting that INI1-Rpt1 domain structurally mimics TAR. This possible mimicry between INI1-Rpt1 and TAR explains the mechanism by which INI1/SMARCB1 influences HIV-1 late events and suggests additional strategies to inhibit HIV-1 replication.

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In order to gain insight into the structural and molecular requirements influencing the anticonvulsant activity against Pentylenetetrazole (PTZ)‐induced seizures and [35S] tert‐Butyl‐bicyclophosphorothionate (TBPS) displacement property (a measure of binding to GABAA receptor), Quantitative Structure–Activity Relationship (QSAR) studies have been performed on a series of congeneric anticonvulsant agents proposed to act by binding to the lactone site of the GABAA receptor. The aim of this work was to identify and analyse the various functionalities, which determine the TBPS displacement property and anticonvulsant activity by correlating with various molecular descriptors. Statistical techniques like Principal Component Analysis (PCA), Partial Least Squares (PLS), Multiple Linear Regression (MLR) and Genetic Function Approximation (GFA) were applied to identify the structural and physicochemical requirements for TBPS displacement property and anticonvulsant activity. The generated equations were statistically validated using leave‐one‐out cross‐validation technique and randomization. The best models were also validated by prediction of activity of compounds, not used for the development of QSAR models. The results from reasonably good QSAR models (statistically validated) clearly indicated that TBPS displacement property and the anticonvulsant activity are defined by different molecular parameters. Based on this finding, a novel approach is proposed, using integrated QSAR modelling, for the identification of potential and selective anticonvulsant agents.

The structure of a protein can be very informative of its function. However, determining protein structures experimentally can often be very challenging. Computational methods have been used successfully in modeling structures with sufficient accuracy. Here we have used computational tools to predict the structure of an evolutionarily conserved and functionally significant domain of