Insight into the key features for ligand binding in Y1230 mutated c-Met kinase domain by molecular dynamics simulations.

c-Met kinase has been considered as an attractive target for developing antitumor agents. The strong interactions between Tyr1230 and the inhibitors emphasized its importance for ligand binding. The clinically related Tyr1230 mutations have made negative impacts on current c-Met kinase inhibitors, especially the exquisitely selective ones, like PF-04217903, while the multi-targeted inhibitors, like Crizotinib, were not affected so much. In this study, the protein-ligand interactions between c-Met kinase domain (wild, Y1230C and Y1230H) and these inhibitors were compared. The binding site was expanded and the post-mutated regions became solvent accessible. The heavy dependency of PF-04217903 on the interactions with Tyr1230 resulted in the steep decrease of its potency against the Y1230 mutants. It was found that the ligand entrance region contributed consistently to the binding of Crizotinib, but not PF-04217903. Additional groups substituted in the ligand entrance region with stable interactions should be beneficial for improving the inhibitory activity of PF-04217903 against the Y1230 mutants. These findings will facilitate the discovery of potent inhibitors against Y1230 mutated c-Met kinase.

The stochastic resonance algorithm with the direct current signal as external force and its application to the detection of weak chromatographic peaks.

As a potential tool for amplifying weak chromatographic peaks, the stochastic resonance algorithm was developed based upon a counterintuitive physical phenomenon. Therefore, the essential step, parameter optimization, was perplexing and difficult for analysts. In order to avoid optimizing the system parameters on a case-by-case basis, an improved algorithm was proposed by introducing a constant or direct current signal into the signal to be measured as the external force. The weak chromatographic peak can be amplified and detected by the new algorithm using the same set of parameters. Two sets of our previous experimental data were reanalyzed by using the developed algorithm and the results were satisfactory. A generalized solution was expected to come into being on account of the new algorithm.

PVLOO-Based Training Set Selection Improves the External Predictability of QSAR/QSPR Models.

In QSAR/QSPR modeling, the indispensable way to validate the predictability of a model is to perform its statistical external validation. It is common that a division algorithm should be used to select training sets from chemical compound libraries or collections prior to external validations. In this study, a division method based on the posterior variance of leave-one-out cross-validation (PVLOO) of the Gaussian process (GP) has been developed with the goal of producing more predictive models. Four structurally diverse data sets of good quality are collected from the literature and then redeveloped and validated on the basis of training set selection methods, namely, four kinds of PVLOO-based training set selection methods with three types of covariance functions (squared exponential, rational quadratic, and neural network covariance functions), the Kennard-Stone algorithm, and random division. The root mean squared error (RMSE) of external validation reported for each model serves as a basis for the final comparison. The results of this study indicate that the training sets with higher values of PVLOO have statistically better external predictability than the training sets generated from other division methods discussed here. These findings could be explained by proposing that the PVLOO value of GP could indicate the mechanism diversity of a specific compound in QSAR/QSPR data sets.

Discontinued cardiovascular drugs in 2015.

INTRODUCTION: About 10,000 compounds will be tested for an individual drug to eventually reach the market. It might be helpful recapitulating previous failures and identifying the main factors of the disappointments. AREAS COVERED: In this review, the author(s) detailed the 7 cardiovascular compounds discontinued after reaching animal studies or Phase I-III clinical trials during 2015. Meanwhile, the reasons for these discontinuations were reported. Among these drugs, most discontinuations (6 drugs) were attributed to lack of efficacy. In general, failures due to lack of efficacy and safety demonstrate the need for the development of more predictive animal models. However, recent related studies showed that the absence of toxicity in animals provided little or virtually no evidential weight that adverse drug reactions would also be absent in humans. In this case, microdosing and collaborating more closely with biotech companies may be the better choices to improve the success ratio. EXPERT OPINION: Future researches may benefit from the seven developments and investigators conducting similar studies may learn from these failures.

Discontinued cardiovascular drugs in 2013 and 2014.

INTRODUCTION: Cardiovascular diseases (CVDs) are the number one cause of death globally. The dramatically high rate of cardiovascular morbidity and mortality has attracted wide concern and great attention within the pharmaceutical industry. However, ∼ 10,000 compounds are tested for every one drug that reaches the market. For this reason, it is helpful to recapitulate previous failures and learn from these experiences. AREAS COVERED: This paper focuses on the 10 cardiovascular drugs discontinued after reaching animal studies or Phase I - II clinical trials between 1 January 2013 and 31 December 2014. EXPERT OPINION: The trend of increasing numbers of cardiovascular drug development terminations seen in recent years has changed. Only 10 cardiovascular drugs were discontinued after reaching animal studies or Phase I - II clinical trials between 2013 and 2014. Only two candidates were discontinued in the Phase I clinical evaluation, and eight were discontinued during Phase II development. Most discontinuations were attributed to lack of efficacy and safety. One orphan drug (RTA-402) appeared in the list of discontinued cardiovascular drugs. The most eye-catching one of the 10 discontinued drugs is RG-7652, a monoclonal antibody against PCSK9, which is predicted as the next statin.

[Study on the Application of NAS-Based Algorithm in the NIR Model Optimization].

In this paper, net analysis signal (NAS)-based concept was introduced to the analysis of multi-component Ginkgo biloba leaf extracts. NAS algorithm was utilized for the preprocessing of spectra, and NAS-based two-dimensional correlation analysis was used for the optimization of NIR model building. Simultaneous quantitative models for three flavonol aglycones: quercetin, keampferol and isorhamnetin were established respectively. The NAS vectors calculated using two algorithms introduced from Lorber and Goicoechea and Olivieri (HLA/GO) were applied in the development of calibration models, the reconstructed spectra were used as input of PLS modeling. For the first time, NAS-based two-dimensional correlation spectroscopy was used for wave number selection. The regions appeared in the main diagonal were selected as useful regions for model building. The results implied that two NAS-based preprocessing methods were successfully used for the analysis of quercetin, keampferol and isorhamnetin with a decrease of factor number and an improvement of model robustness. NAS-based algorithm was proven to be a useful tool for the preprocessing of spectra and for optimization of model calibration. The above research showed a practical application value for the NIRS in the analysis of complex multi-component petrochemical medicine with unknown interference.

Improving the detection sensitivity of chromatography by stochastic resonance.

Improving the detection sensitivity of analytical instruments has been a challenging task for chemometricians since undetectability has been almost unavoidable in trace analysis, even under optimized experimental conditions and with the use of modern instruments. Various chemometrics methods have been developed which attempt to address this detection problem but with limited success (e.g., fast Fourier transform and wavelet transform). However, the application of stochastic resonance (SR) creates an entirely new and effective methodology. Stochastic resonance is a phenomenon which is manifested in non-linear systems where a weak signal can be amplified and optimized with the assistance of noise. In this review, we summarize the use of basic SR, optimization of parameters and its modifications, including periodic modulation stochastic resonance (PSRA), linear modulation stochastic resonance (LSRA), single-well potential stochastic resonance (SSR) and the Duffing oscillator algorithm (DOA) for amplifying sub-threshold small signals. We also review the advantages and the disadvantages of various SR procedures.

The application of multiobjective genetic algorithm to the parameter optimization of single-well potential stochastic resonance algorithm aimed at simultaneous determination of multiple weak chromatographic peaks.

Simultaneous determination of multiple weak chromatographic peaks via stochastic resonance algorithm attracts much attention in recent years. However, the optimization of the parameters is complicated and time consuming, although the single-well potential stochastic resonance algorithm (SSRA) has already reduced the number of parameters to only one and simplified the process significantly. Even worse, it is often difficult to keep amplified peaks with beautiful peak shape. Therefore, multiobjective genetic algorithm was employed to optimize the parameter of SSRA for multiple optimization objectives (i.e., S/N and peak shape) and multiple chromatographic peaks. The applicability of the proposed method was evaluated with an experimental data set of Sudan dyes, and the results showed an excellent quantitative relationship between different concentrations and responses.

Discontinued drugs in 2012: cardiovascular drugs.

The continued high rate of cardiovascular morbidity and mortality has attracted wide concern and great attention of pharmaceutical industry. In order to reduce the attrition of cardiovascular drug R&D, it might be helpful recapitulating previous failures and identifying the potential factors to success. This perspective mainly analyses the 30 cardiovascular drugs dropped from clinical development in 2012. Reasons causing the termination of the cardiovascular drugs in the past 5 years are also tabulated and analysed. The analysis shows that the attrition is highest in Phase II trials and financial and strategic factors and lack of clinical efficacy are the principal reasons for these disappointments. To solve the four problems (The 'better than the Beatles' problem, the 'cautious regulator' problem, the 'throw money at it' tendency and the 'basic researchbrute force' bias) is recommended as the main measure to increase the number and quality of approvable products.

Direct detection of phoxim in water by two-dimensional correlation near-infrared spectroscopy combined with partial least squares discriminant analysis.

This paper has established a simple method to detect directly phoxim in water. In the light of two-dimensional correlation analysis, the band of wavenumber for near-infrared spectroscopy of the model is between 5364.8 and 7552.9 cm(-1), the rate of accuracy for partial least squares discriminant analysis to calibration set (n=149) is 100%, prediction set (n=75) is 93.3% and the overall rate of accuracy for all the samples is 97.8% under the limit of detection 1 µg ml(-1) owing to the spectra preprocessing by standard normal variate transformation and multiplicative scatter correction. It is made clear that this method (two-dimensional correlation analysis combined with partial least squares discriminant analysis) is effective to detect directly phoxim in water.

Discontinued drugs in 2011: cardiovascular drugs.

This perspective is part of an annual series of papers discussing drugs dropped from development in the previous year. Specifically, this paper focuses on the 19 cardiovascular drugs discontinued in 2011 after reaching preclinical or Phase I - III clinical trials. Information for this perspective is mainly derived from a search of Pharmaprojects.

Trace determination of dichlorvos in environmental samples by room temperature ionic liquid-based dispersive liquid-phase microextraction combined with HPLC.

Using 1-butyl-3-methylimidazolium hexafluorophosphate ([BMIM][PF6]) room temperature ionic liquid (RTIL) as extraction solvent, tetrahydrofuran (THF) as disperser solvent, the organophosphorus pesticide dichlorvos in water was determined by dispersive liquid-liquid microextraction (DLLME) combined with high-performance liquid chromatography. Factors affecting RTIL-DLLME (type of disperser solvent, amount of RTIL, volume of disperser solvent, percentage of NaCl and volume and pH of water sample) were optimized by the single-factor method, obtaining the most favorable results when using 65 µL of [BMIM][PF6] and 260 µL of THF to extract the compound from an 8-mL water sample at pH 5.0 containing 25% (w/v) of NaCl. Under these optimum conditions, an enrichment factor of 215-fold was obtained. The calibration curves were linear in the concentration range of 2-1,000 µg/L. The limit of detection calculated at a signal-to-noise ratio of 3 was 0.2 µg/L. The relative standard deviations (RSD) for six replicate experiments at 20, 100 and 200 µg/L concentration levels were 1.8%, 1.3% and 1.3 %, respectively. Then the proposed method was applied to the analysis of three different water sample sources (tap, farm and rain water) and the relative recoveries and RSD of spiked water samples were 95.6-102.4% and 0.6-3.1%, respectively, at three different concentration levels of 20, 100 and 200 µg/L.

An adaptive single-well stochastic resonance algorithm applied to trace analysis of clenbuterol in human urine.

Based on the theory of stochastic resonance, an adaptive single-well stochastic resonance (ASSR) coupled with genetic algorithm was developed to enhance the signal-to-noise ratio of weak chromatographic signals. In conventional stochastic resonance algorithm, there are two or more parameters needed to be optimized and the proper parameters values were obtained by a universal searching within a given range. In the developed ASSR, the optimization of system parameter was simplified and automatic implemented. The ASSR was applied to the trace analysis of clenbuterol in human urine and it helped to significantly improve the limit of detection and limit of quantification of clenbuterol. Good linearity, precision and accuracy of the proposed method ensure that it could be an effective tool for trace analysis and the improvement of detective sensibility of current detectors.

Discontinued drugs in 2010: cardiovascular drugs.

This perspective is a paper discussing drugs dropped from clinical development in the previous years. Specifically, this paper focuses on 16 cardiovascular drugs discontinued in 2010 after reaching Phase I - III clinical trials. Information for this perspective is mainly derived from a search of Pharmaprojects.

Identification of dimethoate-containing water using partitioned dispersive liquid-liquid microextraction coupled with near-infrared spectroscopy.

A simple, rapid and efficient extraction procedure, partitioned dispersive liquid-liquid microextraction, has been developed in combination with near-infrared spectroscopy for the extraction and discrimination of dimethoate from aqueous samples. For this technique, the appropriate mixture of extraction solvent (CCl(4)) and disperser solvent (THF) was utilized. Partial least squares discriminant analysis was applied to build the model with several pre-process methods over the wavenumber regions between 7100 cm(-1) to 7300 cm(-1). The best model gave satisfactory classification accuracy, 98.6% for calibration set (n=74) and 97.6% for prediction set (n=42), using preprocessing of standard normal variate followed by Savitzky-Golay first derivative. The method was successfully applied to bottled water, tap water, lake water and farm water samples. The results demonstrated the possibility of near-infrared spectroscopy after partitioned dispersive liquid-liquid microextraction for the identification of water contaminated by dimethoate.

Modeling of autocatalytic hydrolysis of adefovir dipivoxil in solid formulations.

The stability and hydrolysis kinetics of a phosphate prodrug, adefovir dipivoxil, in solid formulations were studied. The stability relationship between five solid formulations was explored. An autocatalytic mechanism for hydrolysis could be proposed according to the kinetic behavior which fits the Prout-Tompkins model well. For the classical kinetic models could hardly describe and predict the hydrolysis kinetics of adefovir dipivoxil in solid formulations accurately when the temperature is high, a feedforward multilayer perceptron (MLP) neural network was constructed to model the hydrolysis kinetics. The build-in approaches in Weka, such as lazy classifiers and rule-based learners (IBk, KStar, DecisionTable and M5Rules), were used to verify the performance of MLP. The predictability of the models was evaluated by 10-fold cross-validation and an external test set. It reveals that MLP should be of general applicability proposing an alternative efficient way to model and predict autocatalytic hydrolysis kinetics for phosphate prodrugs.

Application of the stochastic resonance algorithm to the simultaneous quantitative determination of multiple weak peaks of ultra-performance liquid chromatography coupled to time-of-flight mass spectrometry.

The stochastic resonance algorithm (SRA) has been developed as a potential tool for amplifying and determining weak chromatographic peaks in recent years. However, the conventional SRA cannot be applied directly to ultra-performance liquid chromatography/time-of-flight mass spectrometry (UPLC/TOFMS). The obstacle lies in the fact that the narrow peaks generated by UPLC contain high-frequency components which fall beyond the restrictions of the theory of stochastic resonance. Although there already exists an algorithm that allows a high-frequency weak signal to be detected, the sampling frequency of TOFMS is not fast enough to meet the requirement of the algorithm. Another problem is the depression of the weak peak of the compound with low concentration or weak detection response, which prevents the simultaneous determination of multi-component UPLC/TOFMS peaks. In order to lower the frequencies of the peaks, an interpolation and re-scaling frequency stochastic resonance (IRSR) is proposed, which re-scales the peak frequencies via linear interpolating sample points numerically. The re-scaled UPLC/TOFMS peaks could then be amplified significantly. By introducing an external energy field upon the UPLC/TOFMS signals, the method of energy gain was developed to simultaneously amplify and determine weak peaks from multi-components. Subsequently, a multi-component stochastic resonance algorithm was constructed for the simultaneous quantitative determination of multiple weak UPLC/TOFMS peaks based on the two methods. The optimization of parameters was discussed in detail with simulated data sets, and the applicability of the algorithm was evaluated by quantitative analysis of three alkaloids in human plasma using UPLC/TOFMS. The new algorithm behaved well in the improvement of signal-to-noise (S/N) compared to several normally used peak enhancement methods, including the Savitzky-Golay filter, Whittaker-Eilers smoother and matched filtration.

Enantiomeric separation and determination of the enantiomeric impurity of armodafinil by capillary electrophoresis with sulfobutyl ether-ß-cyclodextrin as chiral selector.

A selective capillary electrophoresis method using sulfobutyl ether-ß-cyclodextrin as a chiral selector was developed and validated for the determination of the enantiomeric impurity of (R)-modafinil, i.e., armodafinil. Several parameters were optimized for a satisfactory enantioresolution, including the type and concentration of chiral selector and organic modifier, pH of background electrolyte (BGE), capillary temperature. The finally adopted condition was: 20 mmol/L phosphate buffer at pH 7.5, containing 20 mmol/L sulfobutyl ether-ß-cyclodextrin and 20% methanol, at temperature of 25 °C. A good resolution of 3.3 for the two enantiomers of modafinil was achieved by applying the optimal conditions. The limit of detection (LOD) and limit of quantification (LOQ) of (S)-modafinil were 1.25 µg/mL and 2.50 µg/mL, respectively. The established method was also proven to display good selectivity, repeatability, linearity and accuracy. Finally, the method was used to investigate the enantiomeric purity of armodafinil in bulk samples.

Bioequivalence evaluation of menthol after oral administration of peppermint oil soft capsules in dogs.

A randomized, two-way, crossover, bioequivalence study in 6 beagle dogs was conducted to compare the bioavailability of two peppermint oil formulations, soft capsule and hard capsule. The drug was given in a single dose of two capsules (total, 200 mg), and blood samples were withdrawn during the 12 h after drug administration. Menthol (CAS 2216-51-5) as the main component of peppermint oil was determined by a gas chromatography-tandem mass spectrometry (GC-MS/I MS) method after cleavage with beta-glucuronidase. The following pharmacokinetic variables were computed for the two formulations: maximum concentration (Cmax), time to maximum concentration (Tmax), half-life of elimination (t1/2), mean residence time (MRT), and areas under the plasma concentration-time curve (AUC(0-t) and AUC(0-infinity)). For calculation of the 90% confidence interval (CI), an analysis of variance (ANOVA) was carried out. The results indicated that treatment and subject had statistically significant effect on AUC(0-t), AUC(0-infinity), and Cmax, and the 90% CIs for AUC(0-t), AUC(0-infinity), and Cmax were outside the acceptable bioequivalence range. The relative bioavailability was 121.4 +/- 10.6% for AUC(0-infinity). Therefore, it can be concluded that the two formulations are not bioequivalent and the bioavailability of soft capsules is significantly higher than that of hard capsules.

Fingerprinting of Marsdenia tenacissima by capillary electrophoresis compared to HPLC.

Capillary electrophoresis (CE) is employed for the first time in a fingerprint analysis of Marsdenia tenacissima. Because the CE method is a new approach to fingerprinting, it is necessary to compare it to the conventional one: high-performance liquid chromatography (HPLC). In HPLC separation, 15 components are separated in 55 min, while in CE separation, 10 stable components are separated by 200 mM boric acid (pH 8.0) containing 10% methanol within 12 min. CE shows better performance in the analysis of Marsdenia tenacissima, which makes its fingerprint in a much lower analysis time than with HPLC. It is further proven that CE can be a feasible and cost-effective method for the development of the fingerprint of Marsdenia tenacissima.