3D-QSAR analysis of anti-cancer agents by CoMFA and CoMSIA

Three-dimensional quantitative structure–activity relationships were performed for a series of isatin derivatives as anti-cancer agents using the CoMFA and CoMSIA methods. Statistically significant CoMFA ( $r_{\text{cv}}^{2} = 0.869,\;r_{\text{ncv}}^{2} = 0.962$ ) and CoMSIA ( $r_{\text{cv}}^{2} = 0.865,\;r_{\text{ncv}}^{2} = 0.959$ ) models were generated using the training set on the basis of the common substructure-based alignment. Further, the predictive ability of the CoMFA and CoMSIA models was determined using a test set of nine compounds. Based on the information derived from CoMFA and CoMSIA contour maps, we have identified some key features for increasing the activity of compounds and have been used to design new anti-cancer agents. The newly designed molecules in this series of compounds may be more potent anti-cancer agents.     

Receptor and ligand-based 3D-QSAR study on a series of nonsteroidal anti-inflammatory drugs

Self-organizing molecular field analysis (SOMFA) has been used to study the correlation between the molecular properties of a series of 33 stilbene analogs and the cyclooxygenase-2 (COX-2) inhibitory activities. Thus, two different alignments and four charge-assigning methods using grid spacing of 1 Å were investigated to produce eight SOMFA models. The best one derived from the superposition of docked conformation with PM3 charge showed satisfied statistical results. It is characterized by a good noncross-validated r ² (0.806), cross-validated $ r_{\text{cv}}^{ 2} $ (0.799) and F test value (128.673). In addition, the resulted SOMFA model was validated by an external set of ten compounds. The statistical results, predicted correlation coefficient $ r_{\text{Test}}^{ 2} $  = 0.651, metric $ r_{{m({\text{Test}})}}^{ 2} $  = 0.514, and the squared correlation coefficient between observed and predicted values r ² = 0.762, show a satisfied predictive ability. The analysis of SOMFA model, through electrostatic and shape grids, helped in understanding the possible structural modifications of molecules to improve the inhibitory potency.     

Molecular docking and 3D-QSAR studies on the MAPKAP-K2 inhibitors

Mitogen-activated protein kinase-activated protein kinase 2 (MAPKAP-K2) has been identified as a drug target for the treatment of inflammatory diseases. Therefore, there is an urgent need to develop new classes of MAPKAP-K2 inhibitors. To understand the structure activity correlation of MAPKAP-K2 inhibitors, we have carried out a molecular docking study and three-dimensional quantitative structure–activity relationship (3D-QSAR) modeling. Both comparative molecular field analysis ( $r_{\text{cv}}^{2}$  = 0.602, $r_{\text{ncv}}^{2}$  = 0.955) and comparative molecular similarity indices analysis ( $r_{\text{cv}}^{2}$  = 0.546, $r_{\text{ncv}}^{2}$  = 0.891) models were generated using the training set on the basis of the common substructure-based alignment and gave reasonable results. The structural insights obtained from both the 3D-QSAR contour maps and molecular docking help to better interpret the structure activity relationship. The results obtained from this study will be useful in the design of potent MAPKAP-K2 inhibitors.     

Study on the quantitative structure–toxicity relationships of aconitine compounds basing on PCA-ANN method

Aconitine compounds are diterpenoid alkaloids found in the roots/rhizome of Aconitum napellus, Aconitum carmichaeli, and other Aconitum plants in the family of Ranunculanceae, which have beneficial pharmacological activity along with toxicity. The quantum chemistry parameters of thirty-six aconitine compounds were calculated using Gaussian software, and the quantitative structure–toxicity relationships of aconitine compounds were studied in mice via oral acute toxicity (LD₅₀). A model was built to more accurately predict the toxicity of aconitine compounds in mice versus oral LD₅₀. Twenty-seven aconitine compounds were used as a training dataset for building the principal component analysis combined with artificial neural network model and nine others as a forecasting dataset to test the prediction ability of the model using SAS 9.0 program software and Matlab 7.5 software. The model derived a good forecasting ability (MSE = 0.50, R ² = 0.9818 $ R_{\text{pred}}^{2} $  = 0.9457, $ r_{{{\text{m}}\left( {\text{test}} \right)}}^{2} $  = 0.9130, $ r_{{{\text{m}}\left( {\text{overal}} \right)}}^{2} $  = 0.9207, $ R_{\text{r}}^{2} $  = 0.6561, $ {\text{c}}R_{\text{r}}^{2} $  = 0.5655).     

Docking-based 3D-QSAR modeling of the inhibitors of IMP metallo-β-lactamase

IMP metallo-β-lactamases (MBLs) confer broad-spectrum resistance to β-lactam antibiotics such as imipenem and escape the action of almost all clinically used β-lactamase inhibitors. We conducted three-dimensional quantitative structure–activity relationships (3D-QSAR) for a series of IMP-1 MBL inhibitors with the aid of docking-based alignment. While the 3D-QSAR models were created based on a training set of 41 compounds, their external predictivity was validated using a test set of eight compounds. The study has resulted in two types of satisfactory 3D-QSAR models for predicting the biological activity of new compounds: CoMFA model (r ² = 0.989; $ r_{\text{pre}}^{ 2} = 0. 8 4 3 $ ) and CoMSIA model (r ² = 0.968; $ r_{\text{pre}}^{ 2} = 0. 9 5 7 $ ). Our work will facilitate the design and optimization of new potential inhibitors.     

Relationship between plasma or serum drug concentration and amount of drug in the body at steady state upon multiple dosing

The average amount of drug in the body at steady state ( \(\bar X\) )upon repetitive dosing in a two-compartment open system is related to the average steady-state plasma level ( \(\bar C\) )by the apparent volume of distribution at steady state V_ss rather than by V_β,the apparent volume of distribution at pseudodistribution equilibrium, despite the fact that \(\bar C\) is directly proportional to 1/V_β.Multiplication of \(\bar C\) by \(\ddot V_\beta \) results in an overestimate of \(\bar X\) the magnitude of which depends on the distribution and elimination parameters of the drug. The significance and utility of the volume parameters, V_β and V_ss,employed in multicompartment systems are considered.     

Analysis of the inhibiting activity of presynaptic\alpha _{2^ - } ADRENOCEPTORS against NSAID-induced gastric mucosal lesions in the ratagainst NSAID-induced gastric mucosal lesions in the rat

Clonidine at a dose of 0.00625–0.025 mg/kg (po) inhibited the gastric mucosal lesions induced by indomethacin, acidified aspirin, naproxen and piroxicam. The gastroprotective effect was reversed by the $\alpha _{2^ - } ADRENOCEPTORS$ antagonist yohimbine (5 mg/kg sc) and by the highly selective $\alpha _{2^ - } andrenoceptor$ antagonist berbane derivative, Ch-38083 (3.5 mg/kg sc). Clonidine also decreased the gastric acid secretion in pylorus-ligated rats at a dose of 0.2 mg/kg (given intraduodenally) but not at gastroprotective doses (0.00625–0.025 mg/kg). The antisecretory effect of clonidine was reversed by both yohimbine and Ch-38083. The $\alpha _{2B^ - receptor} $ antagonist prazosin (0.1 mg/kg sc) blocked the gastroprotective effect but failed to influence the antisecretory action of clonidine. Our data suggest that the $\alpha _{2B^ - androceptor} $ subtype might be involved in gastroprotection; however, the antisecretory effect is likely to be mediated by $\alpha _{2A^ - like} $ adrenoceptor subtype.     

Theoretical studies on benzimidazole derivatives as E. coli biotin carboxylase inhibitors

Biotin carboxylase (AccC) protein plays an essential role in cell wall biosynthesis in majority of bacterial genera. Inhibition of cell wall biosynthesis might be an ideal way to control the bacterial multiplication in the host system. AccC is one of the promising targets for the antibacterial drugs production. The benzimidazole derivatives are hopeful biotin carboxylase inhibitors, which sensitizes to the Escherichia coli (E. coli) and many other bacterial species too. In steam of developing better benzimidazole derivatives, we describe a quantitative pharmacophore model of benzimidazole derivatives using Phase module of Schr?dinger LLC. This model suggested that the following features are essential for ligand binding, i.e., two aromatic rings, two hydrogen bond donors, one hydrogen bond acceptor, and one hydrophobic group. Further, atom-based 3D-QSAR model was constructed using training set of 37 inhibitors. The constructed QSAR model has cross validated co-efficient value of (Q ²) 0.736 and regression co-efficient value of (R ²) 0.937. The external validation indicated that our QSAR model possessed high predicted powers with $ r_{o}^{2} $ value of 0.933, $ r_{\text m}^{2} $ value of 0.876. The best active and least active compounds were docked into the active site of receptor using Glide and hotspots of the active site were analyzed. The QSAR elucidated here for benzimidazole derivatives combined with their binding information will provide an opportunity to explore the chemical space to promote the potency of AccC inhibitors.     

Cigarette craving and withdrawal symptoms during temporary abstinence and the effect of nicotine gum

Rationale

It is widely believed that nicotine withdrawal symptoms appear within a few hours of stopping smoking, but few data exist documenting their emergence in naturalistic settings. In several countries, nicotine replacement products are licensed for relief of withdrawal symptoms during temporary abstinence, but again, there are no data supporting this from naturalistic settings.

Objectives

To examine the emergence of cigarette craving and withdrawal symptoms during temporary abstinence in a naturalistic setting while using either nicotine or placebo gum.

Methods

Double-blind, randomised, placebo-controlled study in which 132 dependent smokers abstained for 6 h with the assistance of either nicotine (2 mg, n?=?42 or 4 mg, n?=?24) or placebo (n?=?66) gum while travelling on a non-smoking train. Outcome measures were ratings of craving and mood withdrawal symptoms prior to treatment and at regular intervals during abstinence.

Results

In a multivariate analysis of all symptoms, there was no interaction between treatment and time [F(21,110)?=?1.28, p?=?0.20, $ \eta_{\mathrm{p}}^2 $ ?=?0.20] nor an effect of treatment [F(7,124)?=?0.45, p?=?0.87, $ \eta_{\mathrm{p}}^2 $ ?=?0.03]. There was an effect of time [F(21,110)?=?11.59, p?<?0.001, $ \eta_{\mathrm{p}}^2 $ ?=?0.69) and univariate analyses revealed that the majority of symptoms increased linearly throughout the period of abstinence with detectable onsets typically between the first 60 and 180 min of abstinence.

Conclusions

Smokers who temporarily abstain in naturalistic settings experience craving and withdrawal symptoms that emerge linearly over the first 6 h of abstinence. Changes in craving and several mood withdrawal symptoms can be detected within the first 3 h. Nicotine gum may not have an acute effect on the development of these symptoms.     

The pharmacokinetics of furazlocillin in healthy humans

The pharmacokinetics of the novel acylureidopenicillin furazlocillin, 6-[D-2-(3-furfurylidenamino-2-oxo-imidazolidine-1-carboxamido)-2-(4-hydroxyphenyl)-acetamido]-penicillanic acid and of its penicilloic acid derivative were investigated in five healthy male volunteers after intravenous administration of 2 and 4 g dosages. The volunteers were either in a lying or sitting position throughout the duration of the studies. The concentrations of the drug in plasma and urine were measured by two different methods in parallel: a microbiological assay and a newly developed high pressure liquid chromatography method. The latter method was also applicable for quantitation of the penicilloic acid derivative in these biological fluids. The drug's plasma protein binding (66%) and apparent red cell-plasma partition coefficient (0.055) were concentration independent. The pharmacokinetics of the drug were first order only at the lower dose level The apparent half lives of three distinguishable phases were, respectively, 4 \((t_{1/2_1 } )\) , 18 \((t_{1/2_2 } )\) , and 64 \((t_{1/2_z } )\) .     

Pharmacophore modeling, 3D-QSAR, and molecular docking study on naphthyridine derivatives as inhibitors of 3-phosphoinositide-dependent protein kinase-1

The 3-phosphoinositide-dependent protein kinase-1 (PDK1) is an imminent target for discovering novel anticancer drugs. In order to understand the structure–activity correlation of naphthyridine-based PDK-1 inhibitors, we have carried out a combined pharmacophore, three-dimensional quantitative structure–activity relationship (3D-QSAR), and molecular docking studies. The study has resulted in six point pharmacophore models with four hydrogen bond acceptors (A), one hydrogen bond donor (D), and one aromatic ring (R) are used to derive a predictive atom-based 3D-QSAR model. The generated 3D-QSAR model shows that the alignment has good correlation coefficient for the training set compounds which comprises the values of R ² = 0.96, SD = 0.2, and F = 198.2. Test set compounds shows Q ² = 0.84, RMSE = 0.56, and Pearson-R = 0.84. The external validation was carried out to validate the predicted QSAR model which shows good predictive power of $ r_{m}^{2} $  = 0.83 and k = 1.01, respectively. The external validation results also confirm the fitness of the model. The results indicated that, atom-based 3D-QSAR models and further modifications in PDK1 inhibitors via pharmacophore hypothesis are rational for the prediction of the activity of new inhibitors in prospect of drug design.     

k nearest neighbor-molecular field analysis on human HCV NS5B polymerase inhibitors: 2,5-disubstituted imidazo[4,5-c]pyridines

The k nearest neighbor-molecular field analysis (kNN-MFA) is used to study the correlation between the molecular properties and biological activities of the recently reported 2,5-disubstituted imidazo[4,5-c]pyridines as anti-HCV agents. The most predictive kNN-MFA model derived from the superposition of docked conformations, has good cross-validated q ² (0.96) and satisfied predictive ability $ r_{\text{pred}}^{2} $ (0.88). It could rationalize the HCV inhibitory activity profile of many compounds used in the present study as well as the important structural features responsible for activity. Furthermore, the effects of various structural modifications on biological activity are investigated, and biological activities of novel structures are estimated using the developed 3D QSAR model.     

Surface characterization of 2-hydroxypyrimidine sulphate by inverse gas chromatography

The net retention volumes, V _N , of n-alkanes and polar probes on 2-hydroxypyrimidine sulphate (2-HPS) drug surface are determined at 323.15, 328.15 and 333.15 K using inverse gas chromatography. The dispersive surface free energy, $ \gamma_{S}^{d} $ of 2-HPS are evaluated by applying Schultz method as well as Dorris–Gray method and found that $ \gamma_{S}^{d} $ values are higher by 8 per cent in the latter method. The $ \gamma_{S}^{d} $ values are decreasing in both the methods with increase of temperature. The specific component of the free energy of adsorption, $ \Updelta G_{a}^{S} $ , for polar probes are obtained by three methods proposed by Schultz et al., Saint Flour–Papirer and Sawyer–Brookman. The Lewis acid–base parameters, K _a and K _b , are calculated using $ \Updelta G_{a}^{S} $ values. The surface character value, S = (K _b /K _a ) according to the Schultz et al., is found to be 3.9 whereas the S value in the other two methods are found to be 6.2 and 5.6. The results demonstrate that the 2-HPS powder surface contain relatively more basic sites and can interact strongly in the acidic media.     

Design of novel anaplastic lymphoma kinase (ALK) inhibitors based on predictive 3D QSAR models using different alignment strategies

Anaplastic lymphoma kinase (ALK) is involved in many signaling mechanisms that lead to cell-cycle progression; overexpression of ALK has been found in many types of cancers. ALK is a recognized target for the development of small-molecule inhibitors for the treatment of cancer. In this study, a diverse set of 71 ALK inhibitors were aligned by three different methods (pharmacophore, docking-based, and rigid body (Distill) alignment) for the development of comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models. The best 3D QSAR models were obtained, which used rigid body (Distill) alignment of test and training set molecules. CoMFA and CoMSIA models were found statistically significant with leave-one-out correlation coefficients (q ²) of 0.816 and 0.838, respectively; cross-validated coefficients ( $r_{\text{cv}}^{2}$ ) of 0.812 and 0.837, respectively; and conventional coefficients (r ²) of 0.969 and 0.966, respectively. QSAR models were validated by a test set of 14 compounds giving satisfactory prediction of correlation coefficients ( $r_{\text{pred}}^{2}$ ) of 0.910 and 0.904 for CoMFA and CoMSIA models, respectively. Based on the generated contour maps, we have designed 10 novel ALK inhibitors and predicted their activities. Finally, molecular docking study was performed for designed molecules. The designed compounds showed good potential to be used as ALK inhibitors.