One-pot facile synthesis,crystal structure and antifungal activity of 1,2,3-triazoles bridged with amine-amide functionalities

A library of twenty five 1,2,3-triazoles bridged with amine-amide functionalities have been synthesized from reaction of N-substituted(prop-2-yn-1-yl)amines (2a–2e), 2-bromo-N-arylacetamides (4a–4e) and sodium azide through copper(I)-catalyzed alkyne-azide cycloaddition. The synthesized compounds were characterized by using FTIR, ¹H NMR, ¹³C NMR, and HRMS techniques. The structures of synthesized 5a (CCDC 1569245) and 5h (CCDC 1569249) were also confirmed by X-ray crystallography. Antifungal evaluation of newly synthesized triazoles was carried out against – Candida albicans and Aspergillus niger. Biological screening of synthesized 1,2,3-triazoles revealed moderate to good antifungal activity against tested strains.     

3D-QSAR and molecular docking study of LRRK2 kinase inhibitors by CoMFA and CoMSIA methods

Three-dimensional quantitative structure–activity relationship (3D-QSAR) modelling was conducted on a series of leucine-rich repeat kinase 2 (LRRK2) antagonists using CoMFA and CoMSIA methods. The data set, which consisted of 37 molecules, was divided into training and test subsets by using a hierarchical clustering method. Both CoMFA and CoMSIA models were derived using a training set on the basis of the common substructure-based alignment. The optimum PLS model built by CoMFA and CoMSIA provided satisfactory statistical results (q² = 0.589 and r² = 0.927 and q² = 0.473 and r² = 0.802, respectively). The external predictive ability of the models was evaluated by using seven compounds. Moreover, an external evaluation set with known experimental data was used to evaluate the external predictive ability of the porposed models. The statistical parameters indicated that CoMFA (after region focusing) has high predictive ability in comparison with standard CoMFA and CoMSIA models. Molecular docking was also performed on the most active compound to investigate the existence of interactions between the most active inhibitor and the LRRK2 receptor. Based on the obtained results and CoMFA contour maps, some features were introduced to provide useful insights for designing novel and potent LRRK2 inhibitors.     

Studies on Antimicrobial Evaluation of Some 1-((1-(1H-Benzo[d]imidazol-2-yl)ethylidene)amino)-6-((arylidene)amino)-2-oxo-4-phenyl-1, 2-dihydropyridine-3,5-dicarbonitriles

A new series of 1-((1-(1H-benzo[d]imidazol-2-yl)ethylidene)amino)-6-((arylidene)amino)-2-oxo-4-phenyl-1,2-dihydropyridine-3,5-dicarbonitriles (4a–o) have been synthesized for the development of antimicrobial agents. Newly synthesized compounds were evaluated for their in vitro antibacterial activity against Gram-positive bacteria (Pseudomonas aeruginosa, Streptococcus pyogenes), Gram-negative bacteria (Escherichia coli, Staphylococcus aureus), and antifungal activity (Candida albicans, Aspergillus niger, Aspergillus clavatus). These compounds were characterized by infrared, ¹H NMR, ¹³C NMR, and mass spectra. The synthesized compounds 4b, 4e, 4 h, and 4k showed potent antimicrobial activity against tested microorganisms.     

CoMFA and CoMSIA studies on C-aryl glucoside SGLT2 inhibitors as potential anti-diabetic agents

SGLT2 has become a target of therapeutic interest in diabetes research. CoMFA and CoMSIA studies were performed on C-aryl glucoside SGLT2 inhibitors (180 analogues) as potential anti-diabetic agents. Three different alignment strategies were used for the compounds. The best CoMFA and CoMSIA models were obtained by means of Distill rigid body alignment of training and test sets, and found statistically significant with cross-validated coefficients (q ²) of 0.602 and 0.618, respectively, and conventional coefficients (r ²) of 0.905 and 0.902, respectively. Both models were validated by a test set of 36 compounds giving satisfactory predicted correlation coefficients (r ² _pred) of 0.622 and 0.584 for CoMFA and CoMSIA models, respectively. A comparison was made with earlier 3D QSAR study on SGLT2 inhibitors, which shows that our 3D QSAR models are better than earlier models to predict good inhibitory activity. CoMFA and CoMSIA models generated in this work can provide useful information to design new compounds and helped in prediction of activity prior to synthesis.     

Structure-based CoMFA and CoMSIA study of indolinone inhibitors of PDK1

Phosphoinositide-dependent protein kinase-1 (PDK1) is a Ser/Thr kinase which phosphorylates and activates members of the AGC kinase group known to control processes such as tumor cell growth, protection from apoptosis, and tumor angiogenesis. In this paper, CoMFA and CoMSIA studies were carried out on a training set of 56 conformationally rigid indolinone inhibitors of PDK1. Predictive 3D QSAR models, established using atom fit alignment rule based on crystallographic-bound conformation, had cross-validated (r _cv²) values of 0.738 and 0.816 and non-cross-validated (r _ncv²) values of 0.912 and 0.949 for CoMFA and CoMSIA models, respectively. The predictive ability of the CoMFA and CoMSIA models was determined using a test set of 14 compounds, which gave predictive correlation coefficients (r _pred²) of 0.865 and 0.837, respectively. Structure-based interpretation of the CoMFA and CoMSIA field properties provided further insights for the rational design of new PDK1 inhibitors. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

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.     

Development of docking-based 3D QSAR models for the design of substituted quinoline derivatives as human dihydroorotate dehydrogenase (hDHODH) inhibitors

Abstract

This study has investigated docking-based 3D quantitative structure–activity relationships (QSARs) for a range of quinoline carboxylic acid derivatives by comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). A docking study has shown that most of the compounds formed H-bonds with Arg136 and Gln47, which have already been shown to be essential for the binding of ligands at the active site of the hydroorotate dehydrogenase adenovirus (hDHODH). Bioactive conformations of all the molecules obtained from the docking study were used for the 3D QSAR study. The best CoMFA and CoMSIA models were obtained for the training set and were found to be statistically significant, with cross-validated coefficients (q² ) of 0.672 and 0.613, r² _cv of 0.635 and 0.598 and coefficients of determination (r² ) of 0.963 and 0.896, respectively. Both models were validated by a test set of 15 compounds, giving satisfactory predicted correlation coefficients (r² _pred) of 0.824 and 0.793 for the CoMFA and CoMSIA models, respectively. From the docking-based 3D QSAR study we designed 34 novel quinoline-based compounds and performed structure-based virtual screening. Finally, in silico pharmacokinetics and toxicities were predicted for 24 of the best docked molecules. The study provides valuable information for the understanding of interactions between hDHODH and the novel compounds.     

Strategies to design pyrazolyl urea derivatives for p38 kinase inhibition: a molecular modeling study

The p38 protein kinase is a serine–threonine mitogen activated protein kinase, which plays an important role in inflammation and arthritis. A combined study of 3D-QSAR and molecular docking has been undertaken to explore the structural insights of pyrazolyl urea p38 kinase inhibitors. The 3D-QSAR studies involved comparative molecular field analysis (CoMFA) and comparative molecular similarity indices (CoMSIA). The best CoMFA model was derived from the atom fit alignment with a cross-validated r ² (q ²) value of 0.516 and conventional r ² of 0.950, while the best CoMSIA model yielded a q ² of 0.455 and r ² of 0.979 (39 molecules in training set, 9 molecules in test set). The CoMFA and CoMSIA contour maps generated from these models provided inklings about the influence of interactive molecular fields in the space on the activity. GOLD, Sybyl (FlexX) and AutoDock docking protocols were exercised to explore the protein–inhibitor interactions. The integration of 3D-QSAR and molecular docking has proffered essential structural features of pyrazolyl urea inhibitors and also strategies to design new potent analogues with enhanced activity.     

Molecular modeling of triazine type MDR modulators using CoMFA and CoMSIA approaches

In the present study a series of 30 triazine derivatives was investigated by 3D QSAR methods with respect to their MDR reversing activity in vitro . Two approaches were applied and compared: comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Molecular models with good predictive power were derived using steric, electrostatic and hydrophobic fields of the compounds. The results indicated the dominant role of the electrostatic and hydrophobic fields for MDR reversing activity of the investigated modulators. The obtained statistical parameters ( Q cv 2 , Q pr 2 ) showed that the CoMFA and CoMSIA models have similar predictivity. The CoMSIA models were slightly better than the CoMFA ones and obtained with lower number of principal components. The models were graphically interpreted using CoMFA and CoMSIA contour plots. The structural regions responsible for the differences in anti-MDR activity were analyzed in respect to their electrostatic and hydrophobic nature. An easier interpretation of the CoMSIA contour plots was noticed.     

Comparative molecular field analysis and comparative molecular similarity index analysis studies on 1H NMR chemical shift of NH group of diaryl triazene derivatives

Comparative molecular field analysis (CoMFA), comparative molecular field analysis region focusing (CoMFA‐RF) for optimizing the region for the final partial least square analysis, and comparative molecular similarity indices analysis (CoMSIA) methods were employed to develop three‐dimensional quantitative structure–activity relationship (3D‐QSAR) models of ¹H NMR chemical shift of NH proton of diaryl triazene derivatives. The best orientation was searched by all‐orientation search (AOS) strategy to minimize the effect of the initial orientation of the structures. The predictive abilities of CoMFA‐RF and CoMSIA models were determined using a test set of ten compounds affording predictive correlation coefficients of 0.721 and 0.754, respectively, indicating good predictive power. For further model validation, cross validation (leave one out), progressive scrambling, and bootstrapping were also applied. The accuracy and speed of obtained 3D‐QSAR models for the prediction of ¹H NMR chemical shifts of NH group of diaryl triazene derivatives were greater compared to some computational well‐known procedures. Copyright © 2013 John Wiley & Sons, Ltd.     

Use of 3D QSAR to investigate the mode of binding of pyrazinones to HIV-1 RT

Abstract  

Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) based on the docked conformation were performed for 24 pyrazinone derivatives. All compounds were docked into the wild-type HIV-1 RT binding pocket and the lowest-energy docked configurations were used to construct the 3D QSAR models. The CoMFA and CoMSIA models enable good prediction of inhibition by the pyrazinones, with r_\textcv² r_{\text{cv}}^{2}  = 0.703 and 0.735. Results obtained from CoMFA and CoMSIA based on the docking conformation of the pyrazinones are, therefore, powerful means of elucidating the mode of binding of pyrazinones and suggesting the design of new potent NNRTIs.     

Three-dimensional Quantitative Structure-Activity Relationship Analyses of a Series of Butenolide ETA Antagonists

Two kinds of Three-dimensional Quantitative Structure-activity Relationship(3D-QSAR) methods,comparative molecular filed analysis(CoMFA) and comparative molecular similarity indices analysis (CoMSIA) ,were applied to analyze the structure-activity relationship of a series of 63 butenolide ETA selective antagonists with respect to their inhibition against human ETA receptor,The CoMFA and CoMSIA models were developed for the conceivable alignment of the molecules based on a template structure from the crystallized data.The statistical results from the initial orientation of the aligned molecules show that the 3D-QSAR model from CoMFA(q^2=0.543) is obviously superior to that from the conventional CoMSIA(q^2=0.407).In order to refine the model,all-space search (ASS) was applied to minimize the field sampling process.By rotating and translating the molecular aggregate within the grid systematically,all the possible samplings of the molecular fields were tested and subsequently the one with the highest q^2 was picked out .The comparison of the sensitivity of CoMFA and CoMSIA to different space orientation shows that the CoMFA q^2 values are more sensitive to the translations and rotations of the aligned molecules with respect to the lattice than those of CoMSIA.The best CoMFA model from ASS was further refined by the region focused technique.The high quality of the best model is indicated by the high corss-validated correlation and the prediction on the external test set.The CoMFA coefficient contour plots identify several key features that explain the wide range of activities,which may help us to design new effective ETA selective antagonists.     

Exploring the molecular basis for selective cytotoxicity of lamellarins against human hormone-dependent T47D and hormone-independent MDA-MB-231 breast cancer cells

Abstract  

The common structural requirements for cytotoxicity of lamellarins against two human breast cancer cell lines were determined using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. Twenty lamellarins were selected to serve as the training set, whereas another group of six compounds were used as the test set. The best CoMFA and CoMSIA models for both cell lines yielded satisfactory predictive ability with r _cv² values in the range of 0.659–0.728. Additionally, the contour maps obtained from both the CoMFA and CoMSIA models agreed well with the experimental results and may be used in the design of more potent cytotoxic compounds for human breast cancers. Both analyses not only suggested structural requirements of various substituents around the lamellarin skeleton for their cytotoxic activity against both human breast cancer cell lines but also revealed the molecular basis for the differences between the saturated and unsaturated D-rings of the lamellarins.     

Docking-based 3D-QSAR study of pyridyl aminothiazole derivatives as checkpoint kinase 1 inhibitors

Checkpoint kinase 1 (Chk1) is a promising target for the design of novel anticancer agents. In the present work, molecular docking simulations and three-dimensional quantitative structure–activity relationship (3D-QSAR) studies were performed on pyridyl aminothiazole derivatives as Chk1 inhibitors. AutoDock was used to determine the probable binding conformations of all the compounds inside the active site of Chk1. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models were developed based on the docking conformations and alignments. The CoMFA model produced statistically significant results with a cross-validated correlation coefficient (q²) of 0.608 and a coefficient of determination (r²) of 0.972. The reliable CoMSIA model with q² of 0.662 and r² of 0.970 was obtained from the combination of steric, electrostatic and hydrogen bond acceptor fields. The predictive power of the models were assessed using an external test set of 14 compounds and showed reasonable external predictabilities (r²_pred) of 0.668 and 0.641 for CoMFA and CoMSIA models, respectively. The models were further evaluated by leave-ten-out cross-validation, bootstrapping and progressive scrambling analyses. The study provides valuable information about the key structural elements that are required in the rational design of potential drug candidates of this class of Chk1 inhibitors.     

3D-QSAR studies and molecular docking on [5-(4-amino-1<Emphasis Type="Italic">H</Emphasis>-benzoimidazol-2-yl)-furan-2-yl]-phosphonic acid derivatives as fructose-1,6-biphophatase inhibitors

Fructose-1,6-biphophatase has been regarded as a novel therapeutic target for the treatment of type 2 diabetes mellitus (T2DM). 3D-QSAR and docking studies were performed on a series of [5-(4-amino-1H-benzoimidazol-2-yl)-furan-2-yl]-phosphonic acid derivatives as fructose-1,6-biphophatase inhibitors. The CoMFA and CoMSIA models using thirty-seven molecules in the training set gave r _cv² values of 0.614 and 0.598, r ² values of 0.950 and 0.928, respectively. The external validation indicated that our CoMFA and CoMSIA models possessed high predictive powers with r ₀² values of 0.994 and 0.994, r _m² values of 0.751 and 0.690, respectively. Molecular docking studies revealed that a phosphonic group was essential for binding to the receptor, and some key features were also identified. A set of forty new analogues were designed by utilizing the results revealed in the present study, and were predicted with significantly improved potencies in the developed models. The findings can be quite useful to aid the designing of new fructose-1,6-biphophatase inhibitors with improved biological response.     

3D-QSAR (CoMFA,CoMSIA, HQSAR and topomer CoMFA), MD simulations and molecular docking studies on purinylpyridine derivatives as B-Raf inhibitors for the treatment of melanoma cancer

As per the World Health Organization (WHO), cancer is the second most leading cause of death after cardiovascular diseases in worldwide with around 9.88 million total new cases and 1.08 million were observed due to skin cancer in 2018. Amongst two types of skin cancer, progression of melanoma cancer is increasing day by day due to the environmental changes than non-melanoma cancer. Most of B-Raf mutation, specifically B-RafV600E, is responsible for the progression of the melanoma cancer. Here, various 3D-QSAR techniques like comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), molecular hologram QSAR (HQSAR) and topomer CoMFA were used to design novel B-Raf inhibitors by using 28 synthetic B-Raf inhibitors. Except for topomer CoMFA model, remaining models were generated by three different alignment methods in which distil-based alignment method was found best and gave prominent statistical values. After performing N-fold statistical validation, in CoMFA, q², r² and r²_pred values were found to be 0.638, 0.969 and 0.848, respectively. Similarly, q², r² and r²_pred values were found to be 0.796, 0.978 and 0.891 in CoMSIA (SHD) and 0.761, 0.973 and 0.852 in CoMSIA (SH) by N-fold statistical validation. In HQSAR analysis, statistical values were found for q² as 0.984, r² as 0.999 and r²_pred as 0.634 with 97 as best hologram length (BHL). The results of topomer CoMFA showed the q² value of 0.663 and the r² value of 0.967. Important features of purinylpyridine were identified by contour map analysis of all 3D-QSAR techniques, which could be useful to design the novel molecules as B-Raf inhibitors for the treatment of melanoma cancer.

     

Synthesis and Antimicrobial Activity of 1‐[(Substituted Carbamoyl)Amino]‐1H,3H‐1λ5‐[1,3,2]oxazaphospholo[3,4‐a]benzimidazol‐1‐ones

1‐[(Substituted carbamoyl)amino]‐1H,3H‐1λ⁵‐[1,3,2]oxazaphospholo[3,4‐a]benzimidazol‐1‐ones were synthesized by reacting benzimidazole 2‐methanol (4) with different chlorides of carbamidophosphoric acids (3) in the presence of triethylamine at 40–45°C. Their ¹H, ¹³C, and ³¹P NMR spectral data were discussed. The title compounds were tested for their activity against the fungi Aspergillus niger and Fusarium solani and bacteria Staphylococcus aureus and Escherichia coli. These compounds showed moderate antibacterial activity when compared with antifungal activity.     

Synthesis,spectral, stereochemical and biological evaluation of (E)-2-(3-pentyl-2,6-diarylpiperidin-4-ylidene)-N-phenylhydrazinecarbothioamide derivatives

A series of new (E)-2-(3-pentyl-2,6-diarylpiperidin-4-ylidene)-N-phenylhydrazinecarbothioamides (1-6) were synthesized from the corresponding 3-pentyl-2,6-diarylpiperidine-4-ones condensation with phenyl thiosemicarbazide. Their chemical structures were confirmed by means of elemental analysis, FT-IR, ¹H, and ¹³C NMR spectral techniques and for compound 3, HOMOCOSY, HSQC, HMBC, NOESY, and DEPT NMR spectral techniques. From the NMR spectral data the compounds (1-6) are shown to exist in normal chair conformation with equatorial orientation of all the phenyl groups at C-2 and C-6 and pentyl group at C-3. The synthesized compounds were screened for their bacterial activity against Pseudomonas aeruginosa, Staphylococcus aureus, Salmonella typhi, and Escherichia coli and fungal activity against Candida albicans, Rhizopus sp, Aspergillus niger, and Aspergillus flasvus.     

Synthesis of novel 1,2,3-thiadizoles and 1,2,3-selenadiazoles as new antimicrobial agents

Abstract

A series of novel 1,2,3-thiadiazoles and 1,2,3-selenadiazoles having a long alkyl chain were synthesized by reacting semicarbazones with SOCl₂ and SeO₂, respectively. The structures of the target compounds 5–12 were confirmed by spectroscopy (IR, ¹H NMR, ¹³C NMR, and MS) and elemental analysis. Their antibacterial and antifungal activities were evaluated against six bacteria (Pseudomonas aeruginosa, Escherichia coli, Klebsiella pneumoniae, Proteus mirabilis, Enterococcus faecalis, Staphylococcus epidermidis, Staphylococcus aureus) and three fungi (Candida albicans, Candida parapsilosis, Candida tropicalis). The results of bioassays indicated that the compounds 5-Dodecyl-4-(4-methoxy-phenyl)-[1-3]selenadiazole (7), 4-Methyl-5-tetradecyl-[1-3]selenadiazole (8) and 5-Dodecyl-4-(4-methoxy-phenyl)-[1-3]thiadiazole (11) displayed moderate antibacterial activity against S. Epidermidis. On the other hand, according to antifungal screening results, compounds 5-Dodecyl-4-phenyl-[1-3]selenadiazole (5), 4-p-Tolyl-5-undecyl-[1-3]selenadiazole (6), and 5-Dodecyl-4-(4-methoxy-phenyl)-[1-3]selenadiazole (7) exhibited significant antifungal activities studied yeast strains.