Structural investigations of anthranilimide derivatives by CoMFA and CoMSIA 3D-QSAR studies reveal novel insight into their structures toward glycogen phosphorylase inhibition

In the present work, three-dimensional quantitative structure–activity relationship (3-D QSAR) studies on a set of 70 anthranilimide compounds has been performed using docking-based as well as substructure-based molecular alignments. This resulted in the selection of more statistically relevant substructure-based alignment for further studies. Further, molecular models with good predictive power were derived using CoMFA (r ^2?=?0.997; Q ^2?=?0.578) and CoMSIA (r ^2?=?0.976; Q ^2?=?0.506), for predicting the biological activity of new compounds. The so-developed contour plots identified several key features of the compounds explaining wide activity ranges. Based on the information derived from the CoMFA contour maps, novel leads were proposed which showed better predicted activity with respect to the already reported systems. Thus, the present study not only offers a highly significant predictive QSAR model for anthranilimide derivatives as glycogen phosphorylase (GP) inhibitors which can eventually assist and complement the rational drug-design attempts, but also proposes a highly predictive pharmacophore model as a guide for further development of selective and more potent GP inhibitors as anti-diabetic agents.     

Docking-based CoMFA and CoMSIA study of azaindole carboxylic acid derivatives as promising HIV-1 integrase inhibitors

Three-dimensional quantitative structure–activity relationship (3D-QSAR) studies were performed based on a series of azaindole carboxylic acid derivatives that had previously been reported as promising HIV-1 integrase inhibitors. Docking studies to explore the binding mode were performed based on the highly active molecule 36. The best docked conformation of molecule 36 was used as template for alignment. The comparative molecular field analysis (CoMFA) model (including steric and electrostatic fields) yielded the cross validation q ² = 0.655, non-cross validation r ² = 0.989 and predictive r ² _pred = 0.979. The best comparative molecular similarity indices analysis (CoMSIA) model (including steric, electrostatic, hydrophobic and hydrogen-bond acceptor fields) yielded the cross validation q ² = 0.719, non-cross validation r ² = 0.992 and predictive r ² _pred = 0.953. A series of new azaindole carboxylic acid derivatives were designed and the HIV-1 integrase inhibitory activities of these designed compounds were predicted based on the CoMFA and CoMSIA models.     

Synthesis and structures of two molybdenum(VI) complexes derived from similar benzohydrazone ligands with catalytic properties

Two new structurally similar molybdenum(VI) complexes, [MoO₂L¹(CH₃OH)] (1) and [MoO₂L²(CH₃OH)] (2), where L¹ is the dianionic form of N′-(2-hydroxy-5-nitrobenzylidene)-2-methylbenzohydrazide and L² is the dianionic form of N′-(2-hydroxy-4-methoxybenzylidene)-2-methylbenzohydrazide, were prepared and structurally characterized by elemental analysis, infrared spectra, and single-crystal X-ray diffraction. 1 crystallizes in the monoclinic space group P2₁/c, with unit cell dimensions a?=?7.941(1), b?=?14.337(2), c?=?15.141(2)?Å, β?=?92.782(2)°, V?=?1721.8(4)?ų, Z?=?4, R₁?=?0.0286, wR₂?=?0.0650, GOOF?=?1.028. 2 crystallizes in the triclinic space group P-1, with unit cell dimensions a?=?8.003(1), b?=?10.608(1), c?=?10.880(1)?Å, α?=?95.745(2)°, β?=?97.627(2)°, γ?=?105.762(2)°, V?=?872.0(2)?ų, Z?=?2, R₁?=?0.0226, wR₂?=?0.0595, GOOF?=?1.116. X-ray analysis indicates that Mo in the complexes are coordinated by the phenolate oxygen, imino nitrogen, and enolate oxygen of the benzohydrazone, methanol, and two oxo groups, generating octahedral coordination. The oxidation of olefins with the complexes as catalysts was evaluated, indicating that the complexes showed excellent catalytic efficiency in oxidation of most aliphatic and aromatic substrates under mild conditions using tert-butyl hydrogen peroxide as oxidant.     

Pharmacophore modelling,virtual screening and molecular docking studies on PLD1 inhibitors

Lipid metabolism plays a significant role in influenza virus replication and subsequent infection. The regulatory mechanism governing lipid metabolism and viral replication is not properly understood to date, but both Phospholipase D (PLD1 and PLD2) activities are stimulated in viral infection. In vitro studies indicate that chemical inhibition of PLD1 delays viral entry and reduction of viral loads. The current study reports a three-dimensional pharmacophore model based on 35 known PLD1 inhibitors. A sub-set of 25 compounds was selected as the training set and the remaining 10 compounds were kept in the test set. One hundred and twelve pharmacophore models were generated; a six-featured pharmacophore model (AADDHR.57) with survival score (2.69) produced a statistically significant three-dimensional quantitative structure–activity relationship model with r² = 0.97 (internal training set), r² = 0.71 (internal test set) and Q² = 0.64. The predictive power of the pharmacophore model was validated with an external test set (r² = 0.73) and a systematic virtual screening work-flow was employed showing an enrichment factor of 23.68 at the top 2% of the dataset (active and decoys). Finally, the model was used for screening of the filtered PubChem database to fetch molecules which can be proposed as potential PLD1 inhibitors for blocking influenza infection.