QSAR studies on the human sirtuin 2 inhibition by non-covalent 7,5,2-anilinobenzamide derivatives

Abstract

Sirtuin 2 is a key enzyme in gene expression regulation that is often associated with tumor proliferation control and therefore is a relevant anticancer drug target. Anilinobenzamide derivatives have been discussed as selective sirtuin 2 inhibitors and can be developed further. In the present study, hologram and three-dimensional quantitative structure–activity relationship (HQSAR and 3D-QSAR) analyses were employed for determining structural contributions of a compound series containing human sirtuin-2-selective inhibitors that were then correlated with structural data from the literature. The final QSAR models were robust and predictive according to statistical validation (q² and r²_pred values higher than 0.85 and 0.75, respectively) and could be employed further to generate fragment contribution and contour maps. 3D-QSAR models together with information about the chemical properties of sirtuin 2 inhibitors can be useful for designing novel bioactive ligands.

Communicated by Ramaswamy H. Sarma     

Convergent QSAR studies on a series of NK3 receptor antagonists for schizophrenia treatment

The dopamine hypothesis states that decreased dopaminergic neurotransmission reduces schizophrenia symptoms. Neurokinin-3 receptor (NK₃) antagonists reduce dopamine release and have shown positive effects in pre-clinical and clinical trials. We employed 2D and 3D-QSAR analysis on a series of 40 non-peptide NK₃ antagonists. Multivariate statistical analysis, PCA and HCA, were performed to rational training/test set splitting and PLS regression was employed to construct all QSAR models. We constructed one highly predictive CoMFA model (q^2?=?0.810 and r^2?=?0.929) and acceptable HQSAR and CoMSIA models (HQSAR q^2?=?0.644 and r^2?=?0.910; CoMSIA q^2?=?0.691, r^2?=?0.911). The three different techniques provided convergent physicochemical results. All models indicate cyclopropane, piperidine and di-chloro-phenyl ring attached to cyclopropane ring and also the amide group attached to the piperidine ring could play an important role in ligand–receptor interactions. These findings may contribute to develop potential NK₃ receptor antagonists for schizophrenia.     

An explorative study on potent Gram-negative specific LpxC inhibitors: CoMFA,CoMSIA, HQSAR and molecular docking

Pathogenic Gram-negative bacteria are responsible for nearly half of the serious human infections. Hologram quantitative structure–activity relationships (HQSAR), comparative molecular field analysis (CoMFA), and comparative molecular similarity index analysis (CoMSIA) were implemented on a group of 32 of potent Gram-negative LpxC inhibitors. The most effective HQSAR model was obtained using atoms, bonds, donor, and acceptor as fragment distinction. The cross-validated correlation coefficient (q²), non-cross-validated correlation coefficient (r²), and predictive correlation coefficient (r²_Pred) for test set of HQSAR model were 0.937, 0.993, and 0.892, respectively. The generated models were found to be statistically significant as the CoMFA model had (r²?=?0.967, q²?=?0.804, r²_Pred?=?0.827); the CoMSIA model had (r²?=?0.963, q²?=?0.752, r²_Pred?=?0.857). Molecular docking was employed to validate the results of the HQSAR, CoMFA, and CoMSIA models. Based on the obtained information, six new LpxC inhibitors have been designed.     

Structural exploration of tetrahydroisoquinoline derivatives as HDAC8 inhibitors through multi-QSAR modeling study

Abstract

Histone deacetylase 8 (HDAC8) is one of the crucial HDACs responsible for influencing the epigenetic functions of the body. Overexpression of HDAC8 is found to be involved in numerous disease conditions such as tumorigenesis, cell proliferation, cancer, viral infections, neuronal disorders and other epigenetic diseases. Therefore, inhibition of HDAC8 is a primary method to combat these diseases. In this article, a multi-QSAR modeling study on tetrahydroisoquinoline derivatives was conducted to identify important contributions of the structural features of these compounds toward HDAC8 inhibition. All these QSAR modeling techniques were individually validated and justified the observations of each other. The results implied that the tetrahydroisoquinoline moiety may be effective as a cap group than as a linker moiety for HDAC8 inhibition. Different substitutions at the tetrahydroisoquinoline scaffold were also found to be crucial in modulating HDAC8 inhibition.

Communicated by Ramaswamy H. Sarma     

Molecular docking and QSAR analyses of aromatic heterocycle thiosemicarbazone analogues for finding novel tyrosinase inhibitors

A collection of 36 thiosemicarbazone analogues possessed a broad span of tyrosinase inhibitory activities was designed and obtained. Robust and reliable CoMFA and CoMSIA models were gained to predict the structure–activity relationship and the new modifier direction. Inhibitory activities of the compounds were found to greatly depend upon molecular shape, size, and charge. The sterically bulky group at the C-4 position of the thiophene ring contributed a high capacity for biological activity. Some bulky substituents at the C1-position and C12-position, and electron-negative groups at the C3-position, helped to improve the activity of these analogues. The molecular docking results provided visual evidence for QSAR analysis and detailed information about binding mode, affinity, and the principal mechanism between the ligands and tyrosinase. Based on these, a prospective structure modification and optimization of the most potent compound, T32, was suggested for further research.     

Molecular modelling studies on d-annulated benzazepinones as VEGF-R2 kinase inhibitors using docking and 3D-QSAR

Chemotypes comprising the d-annulated 1,3-dihydro-2H-1-benzazepin-2-one scaffold derived from the paullone structure were found to be potent vascular endothelial growth factor receptor 2 (VEGF-R2) kinase inhibitors. Three-dimensional quantitative structure-activity relationship (3D-QSAR) and docking studies were performed on a series of d-annulated benzazepinones with VEGF-R2 kinase inhibition activities. The comparative molecular field analysis and comparative molecular similarity indices analysis models using 32 molecules in the training set gave r²_cv values of 0.811 and 0.769, r² values of 0.962 and 0.953, respectively. 3D contour maps generated from the two models revealed that the electron-withdrawing groups at R₁ and the bulky, electron-withdrawing as well as hydrogen bond donor groups at R₂ position are favourable; the bulky, hydrogen bond acceptor substituent at R₃ and the minor groups at R₄ position may benefit the potency. We have designed a series of novel VEGF-R2 inhibitors by utilizing the SAR results revealed in the present study, which were predicted with excellent potencies in the developed models. The results may aid in designing of potential VEGF-R2 inhibitors with better activities.     

Pair wise binding affinity: 3D QSAR studies on a set of triazolo [1, 5-a] quinoxalines as antagonists of AMPA and KA receptors

The glutamate receptor system is implicated in the development and maintenance of epileptic seizures and it has been reported that compounds showing high affinity for both AMPA and KA binding sites are more potent anticonvulsants than compounds having selective affinity toward AMPA or KA receptor. These outcomes make such inhibitors future potential antiepileptic drugs. So, the pair wise binding affinity for AMPA and KA receptors inhibition was proposed by using the addition between biological activities of ligands. This approach for evaluation of pair wise binding affinity was exemplified using set of triazolo [1,5-a] quinoxaline for AMPA and KA receptors. The biological activity towards AMPA and KA receptors (expressed as -log IC_5O) was taken as a dependent variable for building CoMFA and CoMSIA models. The resulting models show the ways of increasing binding affinity to both AMPA and KA receptors as potential target for epilepsy. The statistically significant results show that pair wise CoMFA and CoMSIA models are better then individual models. The resulting cross-validated r²_CV value 0.806 for CoMFA is greater then 0.780 for CoMSIA pair wise model. The non-cross validated run giving a coefficient of determination r² value of 0.946 and 0.908 for CoMFA and CoMSIA respectively, provided a good correlation between the observed and computed affinities of the compounds.     

Designing potential HDAC3 inhibitors to improve memory and learning

The work presented here explores the structural and physicochemical features important for benzamide-based HDAC3 inhibitors to get an idea about the design aspect of potential inhibitors. A number of molecular modeling studies (3D-QSAR CoMFA and CoMSIA, Bayesian classification modeling) were performed on 113 diverse set of benzamide-based HDAC3 inhibitors. All these models developed are statistically reliable and correlate the SAR observations. Electron withdrawing substitution is favorable but the bulky hydrophobic group at the cap region reduces HDAC3 inhibition. Hydrophobicity and steric feature of the aryl linker function favor the activity. Aryl group substituted benzamide functionality is not favorable for HDAC3 inhibition. The amide function of the benzamide moiety is essential for Zn²⁺ chelation and the carboxylic acid function may serve as a hydrogen bond acceptor (HBA) feature. Moreover, electron withdrawing substituent at the benzamide moiety influences activity whereas steric and hydrophobic substituents reduce HDAC3 inhibition. Overall, this study may provide a valuable insight on the design of better active HDAC3 inhibitors in future.

Communicated by Ramaswamy H. Sarma     

Combined 3D QSAR and molecular docking studies to reveal novel cannabinoid ligands with optimum binding activity

The combination of NMR spectroscopy and molecular modeling studies provided the putative bioactive conformation for the analgesic cannabinoid (CB) ligand (−)-2-(6a,7,10,10a-tetrahydro-6,6,9-trimethylhydroxy-6H-dibenzo[b,d]pyranyl)-2-hexyl 1,3-dithiolane which served as a template in reported three-dimensional quantitative structure–activity relationship (3D QSAR) studies [Durdagi et al., J. Med. Chem. 2007, 50, 2875]. The reported 3D models of the CB1 receptor allowed us to construct a new 3D QSAR model based on theoretical calculations and molecular docking studies. Statistical comparison of the constructed two 3D QSAR studies showed the improvement of the new model. In addition, the new model can explain more effectively the experimental data and thus it can serve more efficiently in the rational drug design of pharmacologically optimized CB analogues.     

Synthesis and in vitro antibacterial activity of oxazolidine LBM-415 analogs as peptide deformylase inhibitors

The drug resistant bacteria pose a severe threat to human health. The increasing resistance of those pathogens to traditional antibacterial therapy renders the identification of new antibacterial agents with novel antibacterial mechanisms an urgent need. In this study, a series of (2S)-N-substituted-1-[(formyhydroxyamino)methyl]-1-oxohexyl]-2-oxazolidinecarboxamides were designed, synthesized and evaluated for in vitro antibacterial activity. Most of these compounds displayed good activities against Gram-positive organisms comparable to reference agent LBM-415.     

Molecular modeling study for the design of novel acetyl-CoA carboxylase inhibitors using 3D QSAR,molecular docking and dynamic simulations

Acetyl-CoA carboxylase (ACC) enzyme plays an important role in the regulation of biosynthesis and oxidation of fatty acids. ACC is a recognized drug target for the treatment of obesity and diabetes. Combination of ligand and structure-based in silico methods along with activity and toxicity prediction provides best lead compounds in the drug discovery process. In this study, a data-set of 100 ACC inhibitors were used for the development of comparative molecular field analysis (CoMFA) and comparative molecular similarity index matrix analysis (CoMSIA) models. The generated contour maps were used for the design of novel ACC inhibitors. CoMFA and CoMSIA models were used for the predication of activity of designed compounds. In silico toxicity risk prediction study was carried out for the designed compounds. Molecular docking and dynamic simulations studies were performed to know the binding mode of designed compounds with the ACC enzyme. The designed compounds showed interactions with key amino acid residues important for catalysis, and good correlation was observed between binding free energy and inhibition of ACC.     

3D-QSAR study of adamantyl N-benzylbenzamides as melanogenesis inhibitors

Three-dimensional quantitative structure–activity relationship (3D-QSAR) modeling, comparative molecular field analysis (CoMFA), and comparative molecular similarity indices analysis (CoMSIA) of polyhydroxylated N-benzylbenzamide derivatives containing an adamantyl moiety were performed to understand the mechanism of action and structure–activity relationship of these compounds. Contour map analysis indicated that steric contributions of the adamantyl moiety and electrostatic contributions of the hydroxyl group at the 3-position are important in the activity. Activities of the training set and test sets predicted by CoMFA fit well with actual activities, demonstrating that CoMFA, along with the best calculated q² value, has the best predictive ability.     

Design, synthesis and antibacterial activity of 3-methylenepyrrolidine formyl hydroxyamino derivatives as novel peptide deformylase inhibitors

The synthesis and antibacterial activity of 3-methylenepyrrolidine formyl hydroxyamino derivatives are reported. The antibacterial activities of these derivatives were evaluated to discover SAR at P^1′ and P^3′ positions, and most of these derivatives exhibit better in vitro antibacterial activity than existing drugs against drug-resistant clinical isolates including MRSA, PRSP, and Haemophilus influenzae.     

3D-QSAR studies on fluoropyrrolidine amides as dipeptidyl peptidase IV inhibitors by CoMFA and CoMSIA

Three-dimensional quantitative structure-activity relationship (3D-QSAR) analyses using CoMFA and CoMSIA methods were conducted on a series of fluoropyrrolidine amides as dipeptidyl peptidase IV (DP-IV) inhibitors. The selected ligands were docked into the binding site of the 3D model of DP-IV using the GOLD software, and the possible interaction models between DP-IV and the inhibitors were obtained. Based on the binding conformations of these fluoropyrrolidine amides and their alignment inside the binding pocket of DP-IV, predictive 3D-QSAR models were established by CoMFA and CoMSIA analyses, which had conventional r ² and cross-validated coefficient values () up to 0.982 and 0.555 for CoMFA and 0.953 and 0.613 for CoMSIA, respectively. The predictive ability of these models was validated by six compounds that were in the testing set. Structure-based investigations and the final 3D-QSAR results provide the guide for designing new potent inhibitors.