Microwave‐assisted synthesis and insecticidal properties of biologically potent organosilicon(IV) compounds of a sulfonamide imine

Microwave‐assisted synthesis and spectroscopic studies of dimethyl‐, diphenyl‐ and triphenyl‐silicon(IV) chelates derived from the reactions of organochlorosilanes with the sodium salt of a biologically active nitrogen donor ligand N^∩NH are described. The resulting products have been isolated and characterized by elemental analyses, molecular weight determinations and conductance measurements. On the basis of electronic, infrared, ¹H, ¹³C and ²⁹Si NMR spectral studies, trigonal bipyramidal and octahedral geometries have been suggested for the resulting complexes. The biological activity of the ligand and its corresponding complexes has been examined with regard to antifungal and antibacterial activity against pathogenic fungi and bacteria, and the results are quite encouraging. All the compounds have also been found to act as nematicides and insecticides, by reducing the number of nematodes (Meloidogyne incognita) and insects (Trogoderma granarium). Copyright © 2005 John Wiley & Sons, Ltd.     

QSAR and docking studies on chalcone derivatives for antitubercular activity against M. tuberculosis H37Rv

In our prior studies, we reported some known antitubercular drugs (rifampicin and streptomycin) and newly synthesized chalcone derivatives (16–26) tested in vitro against Mycobacterium tuberculosis H₃₇Rv strain. Most of the tested compounds were efficient antimycobacterial agents showing minimum inhibitory concentration values ranging from 3.5 to 30 µg mL⁻¹. In the present work, a quantitative structure–activity relationship (QSAR) study has been performed on these active chalcone derivatives to correlate their chemical structures with their observed inhibiting activity against M. tuberculosis. A QSAR model that is able to correlate well the antitubercular activity with the chemical structures of active chalcone derivatives 16, 24, 25a, 25c, and 26 has been developed, which is potentially helpful in the design of novel and more potent antitubercular agents. The r² and rCV² of a newly derived QSAR model were 0.89 and 0.84, respectively. The QSAR study indicates that chemical properties, viz. heat of formation (kcal mol⁻¹), lowest unoccupied molecular orbital energy (eV), and amine, hydroxyl, and methyl groups counts, correlate well with the activity. In silico screening results for oral bioavailability and absorption, distribution, metabolism, excretion, and toxicity compliance showed that compounds 25a, 25c, and 24 were found active similar to rifampicin and streptomycin. The docking study for the exploration of mechanism of action showed high binding affinity of active derivatives. Copyright © 2014 John Wiley & Sons, Ltd.     

Combined 2D and 3D-QSAR,molecular modelling and docking studies of pyrazolodiazepinones as novel phosphodiesterase 2 inhibitors

Selective inhibition of phosphodiesterase 2 (PDE2) in cells where it is located elevates cyclic guanosine monophosphate (cGMP) and acts as novel analgesic with antinociceptive activity. Three-dimensional quantitative structure–activity relationship (QSAR) studies for pyrazolodiazepinone inhibitors exhibiting PDE2 inhibition were performed using comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA) and Topomer CoMFA, and two-dimensional QSAR study was performed using a Hologram QSAR (HQSAR) method. QSAR models were generated using training set of 23 compounds and were validated using test set of nine compounds. The optimum partial least squares (PLS) for CoMFA-Focusing, CoMSIA-SDH, Topomer CoMFA and HQSAR models exhibited good ‘leave-one-out’ cross validated correlation coefficient (q²) of 0.790, 0.769, 0.840 and 0.787, coefficient of determination (r²) of 0.999, 0.964, 0.979 and 0.980, and high predictive power (r²_pred) of 0.796, 0.833, 0.820 and 0.803 respectively. Docking studies revealed that those inhibitors able to bind to amino acid Gln859 by cGMP binding orientation called ‘glutamine-switch’, and also bind to the hydrophobic clamp of PDE2 isoform, could possess high selectivity for PDE2. From the results of all the studies, structure–activity relationships and structural requirements for binding to active site of PDE2 were established which provide useful guidance for the design and future synthesis of potent PDE2 inhibitors.     

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.     

DFT‐based QSAR study and molecular design of AHMA derivatives as potent anticancer agents

A quantitative structure–activity relationship (QSAR) of 3‐(9‐acridinylamino)‐5‐hydroxymethylaniline (AHMA) derivatives and their alkylcarbamates as potent anticancer agents has been studied using density functional theory (DFT), molecular mechanics (MM+), and statistical methods. In the best established QSAR equation, the energy (E_NL) of the next lowest unoccupied molecular orbital (NLUMO) and the net charges (Q_FR) of the first atom of the substituent R, as well as the steric parameter (MR₂) of subsituent R₂ are the main independent factors contributing to the anticancer activity of the compounds. A new scheme determining outliers by “leave‐one‐out” (LOO) cross‐validation coefficient (q) was suggested and successfully used. The fitting correlation coefficient (R²) and the “LOO” cross‐validation coefficient (q²) values for the training set of 25 compounds are 0.881 and 0.829, respectively. The predicted activities of 5 compounds in the test set using this QSAR model are in good agreement with their experimental values, indicating that this model has excellent predictive ability. Based on the established QSAR equation, 10 new compounds with rather high anticancer activity much greater than that of 34 compounds have been designed and await experimental verification. © 2006 Wiley Periodicals, Inc. Int J Quantum Chem, 2007     

Design,synthesis, pharmacological evaluation and in silico ADMET prediction of novel substituted benzimidazole derivatives as angiotensin II–AT1 receptor antagonists based on predictive 3D QSAR models

In this study we designed novel substituted benzimidazole derivatives and predicted their absorption, distribution, metabolism, excretion and toxicity (ADMET) properties, based on a predictive 3D QSAR study on 132 substituted benzimidazoles as AngII–AT₁ receptor antagonists. The two best predicted compounds were synthesized and evaluated for AngII–AT₁ receptor antagonism. Three different alignment tools for comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were used. The best 3D QSAR models were obtained using the rigid body (Distill) alignment method. CoMFA and CoMSIA models were found to be statistically significant with leave-one-out correlation coefficients (q²) of 0.630 and 0.623, respectively, cross-validated coefficients (r²_cv) of 0.651 and 0.630, respectively, and conventional coefficients of determination (r²) of 0.848 and 0.843, respectively. 3D QSAR models were validated using a test set of 24 compounds, giving satisfactory predicted results (r²_pred) of 0.727 and 0.689 for the CoMFA and CoMSIA models, respectively. We have identified some key features in substituted benzimidazole derivatives, such as lipophilicity and H-bonding at the 2- and 5-positions of the benzimidazole nucleus, respectively, for AT₁ receptor antagonistic activity. We designed 20 novel substituted benzimidazole derivatives and predicted their activity. In silico ADMET properties were also predicted for these designed molecules. Finally, the compounds with best predicted activity were synthesized and evaluated for in vitro angiotensin II–AT₁ receptor antagonism.     

Synthesis and insecticidal activities of novel spin‐labeled derivatives of camptothecin

Continuing our search for natural product based compounds for the control of Brontispa longissima larvae, eight spin‐labeled camptothecin derivatives 7a–h and the intermediate 2 were first tested for their insecticidal activities against fifth‐instar larvae of Brontispa longissima. Among all the tested compounds, especially compounds 7a and 2 showed promising insecticidal activities with the corrected mortality rates of 69.55% and 74.07% against fifth‐instar larvae of B. longissima, respectively. The different insecticidal activity ranges of these compounds indicated that the variation of the structures of l ‐amino acids in these compounds markedly affected the activity profiles of this compound class, and some important SAR information has been revealed from it. © 2011 Wiley Periodicals, Inc. Heteroatom Chem 22:687–691, 2011; View this article online at wileyonlinelibrary.com . DOI 10.1002/hc.20734     

Combined QSAR-based virtual screening and fluorescence binding assay to identify natural product mediators of Interferon Regulatory Factor 7 (IRF-7) in pulmonary infection

Abstract

Interferon regulatory factor-7 (IRF-7) is involved in pulmonary infection and pneumonia. Here, a synthetic strategy that combined quantitative structure–activity relationship (QSAR)-based virtual screening and in vitro binding assay was described to identify new and potent mediator ligands of IRF-7 from natural products. In the procedure, a QSAR scoring function was developed and validated using Gaussian process (GP) regression and a structure-based set of protein–ligand affinity data. By integrating hotspot pocket prediction, pharmacokinetics profile analysis and molecular docking calculations, the scoring function was successfully applied to virtual screening against a large library of structurally diverse, drug-like natural products. With the method we were able to identify a number of potential hits, from which several compounds were found to have moderate or high affinity to IRF-7 using fluorescence binding assays, with dissociation constants K_d at micromolar level. We have also examined the structural basis and noncovalent interactions of computationally modelled IRF-7 complex with its potent ligands. It is revealed that hydrophobic forces and van der Waals contacts play a central role in stabilization of the complex architecture, while few hydrogen bonds confer additional specificity for the protein–ligand recognition.     

QSAR and mode of action studies of insecticidal ecdysone agonists†

A series of our SAR and QSAR studies of synthetic moulting hormone agonists, dibenzoylhydrazines (DBH), exhibiting insecticidal/larvicidal activity are reviewed in this article. We prepared a number of analogues where various substituents are introduced into the two benzene rings of DBH and measured their biological activity using various biological systems. Larvicidal activity was against larvae of the rice stem borer Chilo suppressalis and the moulting hormone activity was in terms of the stimulation of N-acetylglucosamine incorporation in a cultured integument system of the same insect species. Binding affinity to the ecdysone receptor was assayed with intact Sf-9 cell lines in which the ADME processes are negligible as well as using receptor proteins obtained by in vitro translation of the responsible cDNA cloned from cell-free preparation of integumentary tissue of C. suppressalis. Variations in the biological activity indices were either correlated between two types of activity or correlated using physicochemical molecular and substituent parameters in terms of the classical QSAR. Comparisons among correlations and with recently revealed X-ray crystallographic findings clearly indicate the physicochemical meaning of parameters significant in the correlation equations to help understanding molecular mechanism of the moulting hormonal action.     

取代苯丙酮肟衍生物的合成、QSAR研究以及优化

本文介绍了用结合化学、生物实验以及计算机辅助分子设计方法优化对瓜类白粉病毒有抑制作用的先导化合物的研究。用3－取代氨基－1－芳基丙酮－1－肟以及卤代烃合成了44个取代苯丙酮肟衍生物。生物测试的结果表示这些化合物大部分对瓜类白粉病毒有抑制作用。基于这些生物测试,对这44个化合物做了QSAR研究。根据所得CoMFA (rcv2, S 以及 r2 分别为0.577, 0.258, 0.962) 和 CoMSIA (rcv2, S 以及 r2 分别为0.583, 0.343, 0.932) 模型,设计了3个新化合物,而且预测结果显示,它们无致癌和致突变毒性。测试结果显示预测活性与实验活性相对应,说明这两个模型具有较高的预测准确率。     

Grid potential analysis,virtual screening studies and ADME/T profiling on N‐arylsulfonylindoles as anti‐HIV‐1 agents

A grid potential analysis employing a novel approach of 3D quantitative structure–activity relationships (QSAR) as AutoGPA module in MOE2009.10 was performed on a dataset of 42 compounds of N‐arylsulfonylindoles as anti‐HIV‐1 agents. The uniqueness of AutoGPA module is that it automatically builds the 3D‐QSAR model on the pharmacophore‐based molecular alignment. The AutoGPA‐based 3D‐QSAR model obtained in the present study gave the cross‐validated Q² value of 0.588, r²_pred value of 0.701, r²_m statistics of 0.732 and Fisher value of 94.264. The results of 3D‐QSAR analysis indicated that hydrophobic groups at R₁ and R₂ positions and electron releasing groups at R₃ position are favourable for good activity. To find similar analogues, virtual screening on ZINC database was carried out using generated AutoGPA‐based 3D‐QSAR model and showed good prediction. In addition to those mentioned earlier, in‐silico ADME absorption, distribution, metabolism and excretion profiling and toxicity risk assessment test was performed, and results showed that majority of compounds from current dataset and newly virtually screened hits generated were within their standard limit. Copyright © 2013 John Wiley & Sons, Ltd.