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).     

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.     

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.     

Stability of pipethanate hydrochloride in aqueous solution

In the present investigation, an attempt has been made to apply the methods of classical chemical kinetics to the hydrolytic reaction of pipethanate hydrochloride. By successively keeping all but one variable essentially constant, it has been possible to resolve the overall effect of the individual contributing factors. Since nearly all commercial pipethanate preparations are formulated with antacid, studies were made at several constant hydrogen ion concentration ranging pH 0.4 to 7.5. Rate measurement was also carried out in temperature ranging from 25°C to 60°C. The hydrolysis of pipethanate is found to be of first order with respect to pipethanate concentration over an experimental range of hydrogen ion concentration (pH 0.4–7.5). The apparent activation energy(Ea) at pH 7.5 is 18.30 Kcal/mole and the frequency factor is 1.1408×10⁹ sec^?1. The rate of the hydrolysis has a minimum at pH 2.5–3.5. In this region the half-life of pipethanate was about 15.3 days at 60°C. The catalytic effect of water was found to be \(K_{H^{ + } } = 1.1568 \times 10^{ - 2 } min^{ - 1} \) at 60°C. The catalytic constants of the hydroxyl ions and hydrogen ions at 60°C were also found to be \(K_{OH^ - } = 4.5519 \times 10^5 min^{ - 1} \) and \(K_{H_2 O} = 3.16 \times 10^{ - 5} {\text{ min}}^{{\text{ - 1}}} \) , respectively. This reaction appears to be primarily base catalyzed hydrolysis and pipethanate is relatively reluctant toward acid catalyzed hydrolysis. A positive primary salt effect was noted in the solution of pipethanate at pH 7.5 and at 60°C.     

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.     

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.     

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.     

Effect of glycyrrhizin on the activity of CYP3A enzyme in humans

Background

Glycyrrhizin is a major ingredient of licorice which is widely used in the treatment of various diseases such as chronic hepatitis. Licorice or glycyrrhizin has been shown to alter the activity of CYP3A in rodents. The influence of glycyrrhizin on CYP3A has not been elucidated in humans.

Objective

To investigate the effects of repeated glycyrrhizin ingestion on the oral pharmacokinetics of midazolam, a probe drug for CYP3A activity in humans.

Methods

Sixteen healthy adult male subjects were enrolled in a two-phase randomized crossover design. In each phase the volunteers received placebo or glycyrrhizin for 14 days. On the 15th day, midazolam was administered and blood samples were obtained to determine midazolam plasma concentrations. Bioequivalence was assessed by determining geometric mean ratios (GMRs) and 90% confidence intervals (90% CI).

Results

The geometric mean (geometric coefficient of variation) for the $ {\hbox{AU}}{{\hbox{C}}_{0 - \infty }} $ of midazolam in the placebo group was 196.4 ng·h/ml (30.3%) and after glycyrrhizin treatment, 151.3 ng·h/ml (34.7%). The GMRs and 90% CI for $ {\hbox{AU}}{{\hbox{C}}_{0 - \infty }} $ and C_max of midazolam in the presence/absence of glycyrrhizin were 0.77 (0.70, 0.89) and 0.83 (0.74, 1.01), respectively. The 90% CI for $ {\hbox{AU}}{{\hbox{C}}_{0 - \infty }} $ and C_max for the GMR of glycyrrhizin over placebo were both out of the no-effect boundaries of 0.80–1.25.

Conclusions

Administration of glycyrrhizin resulted in a modest induction of CYP3A that was clinically relevant according to the bioequivalence analysis.     

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.     

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 \((t_{1/2_z } )\) .     

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.     

Molecular dynamics-based self-organizing molecular field analysis on 3-amino-6-arylpyrazines as the ataxia telangiectasia mutated and Rad3 related (ATR) protein kinase inhibitors

The ataxia telangiectasia mutated and Rad3 related (ATR) protein kinase is one of the apical regulators in the DNA damaging response signaling pathways. Inhibition of ATR kinase may greatly potentiates the cyto-toxicity by DNA damaging agents to the tumor cells while, have minimum effect on normal cells. In this article, the impact of ligand conformation on the three-dimensional quantitative structure–activity relationship (3D-QSAR) model of a series of 3-amino-6-arylpyrazines as ATR kinase inhibitors was investigated. We employed molecular dynamics (MDs) simulations to get the dynamic active conformations (DACs) of the compounds in the ATP-binding site of ATR kinase. As a result, the model based on the DACs extracted from the first nanosecond MD simulation is superior to that using static active conformations from docking with r ² = 0.917; $q_{\text{LOO}}^{2}$  = 0.880; standard error of estimate [SEE] = 0.259; F = 347.29; $r_{\text{pred}}^{2}$  = 0.923; SEE_pred = 0.301. Our results highlight the importance of incorporating DACs of ligand using MD simulation in 3D-QSAR studies. This study may also provide useful information to rationalize the design of novel ATR kinase inhibitors.     

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.     

The Bateman function revisited: A critical reevaluation of the quantitative expressions to characterize concentrations in the one compartment body model as a function of time with first-order invasion and first-order elimination

The Bateman function, $A''(e^{ - k_e t} - e^{ - k_a t} )$ , quantifies the time course of a first-order invasion (rate constant k_a) to, and a first-order elimination (rate constant k_e) from, a one-compartment body model where A″=(γDose)k_a/(k _a?k _e) V. The rate constants (whenk _a>3k _e) are frequently determined mined by the “method of residuals” or “feathering”. The rate constantk _a is actually the sum of rate constants for the removal of drug from the invading compartment. “Flip-flop”, the interchange of the values of the evaluated rate constants, occurs whenk _e>3k _a. Whether ?k _a or ?k _e is estimable from the terminal lnC-t slope can be determined from which apparent volume of distribution,V, derived from the Baterman function is the most reasonable. The Bateman function and “feathering” fail when the rate constants are equal. The time course is then expressed byC=γDtk e ^?kt . The determination of such equalk values can be obtained by the nonlinear fitting of suchC-t data with random error to the Bateman function. Also, rate constant equality can be concluded when 1/t _max and the k _min (value ofk _e at the minimum value of $e^{ - k_e t_{max} } /k_e$ plotted against variablek _e values) are synonymous or whenk _min t _max approximates unity. Simpler methods exist to evaluateC-t data. When a drug has 100% bioavailability, regression ofDose/V/C onAUC/C in the nonabsorption phase givesk _e no matter what is the ratio ofm=k _a /k _e . Sincek _e t _max=lnm/(m?1),m can be determined from the given table relatingm andk _e t _max. When γ is unknown,k _e can be estimated from the abscissas of intersections of plots of $C_{max} e^{k_e t_{max} }$ andk _e AUC, both plotted vs. arbitrary values ofk _e, and γD/V values are estimable from the ordinate of the intersection. Also, when γ is unknown,k _e can be estimated from the abscissas of intersections (or of closest approaches) of $e^{k_e t_{max} } /k_e$ andAUC/C _max, both plotted vs. arbitrary values ofk _e. TheC-t plot of the Modified Bateman function, $C = Be^{ - \lambda _2 t} - Ae^{ - \lambda _1 t}$ , does not commence at the origin (i.e., whent _c=0=0 and when a lag time does not exist). However,T _C=0 = ln(A/B/(λ₁-λ₂ whenA>B. AUC ^A″ without time lag is the same asAUC ^A≠B and $A'' = Be^{ - \lambda _2 t} = Ae^{ - \lambda _1 t}$ . Thet _max of theC-t plot of the latter ist _c=0 later than thet _max of theC-t plot of the former which commences att=0. However, (AUMC _uncorr ^A≠B )_∞ =B/λ ₂ ² -A/λ ₁ ² differs fromAUMC _corr ^A≠B ) =A″t _C=0 (1/λ₂-1/λ₁ +A″(1/λ ₂ ² -1/λ ₁ ² ). (AUMC _corr ^A″ ) =A″(1/λ ₂ ² -1/λ ₁ ² ) whenC-t plots start att=0.AUMC _uncorr ^{A ≠ B} is not valid. The (MRT _uncorr ^{A ≠ B} )_∞ is also an invalidMRT estimate, $(B/\lambda _2^2 - A/\lambda _1^2 )/e^{t_{c = 0} } (B/\lambda _2 - A/\lambda _1 )$ , but whenA>B, C-t curves which start at the origin,C _t=0 , haveMRT values displaced byMRT _corr ^{A ≠ B} =MRT ^{[A′ or A' = A = B]} ; +t _C=0 . Thet _max of the Bateman function is also displaced byt _C=0 when theA exceeds theB of its modified form. Dose-dependent pharmacokinetics can be concluded fromC-t data generated by various firstorder invading nonintravenous doses if drug absorption is 100%. Thek _e values can be determined if the apparent volume of distribution of the one-compartment body model is known. Plots ofm/AUC _t ^p vs. timet have a slope of — CL_ME, (the negative of the clearance of the metabolite) and an intercept of the clearance of the precursor, CL_PM, provided that all of the precursor had been absorbed. Similar studies could determine the appararent volume of distribution of the metabolite and the clearance (and thus the rate constant,k _PM=CL_PM/V _P) of the precursor to the metabolite.     

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.