Discovery of aryl-biphenyl-2-ylmethylpiperazines as novel scaffolds for 5-HT7 ligands and role of the aromatic substituents in binding to the target receptor

It has been reported that 5-HT₇ receptors are promising targets of depression and neuropathic pain. 5-HT₇ receptor antagonists have exhibited antidepressant-like profiles, while agonists have represented potential therapeutics for pain. In the course of our ongoing efforts to discover novel 5-HT₇ modulators, we designed an arylpiperazine scaffold with a substituted biphenyl-2-ylmethyl group. A series of biphenyl-2-yl-arylpiperazinylmethanes were then prepared, which showed a broad spectrum of binding affinities to the 5-HT₇ receptor depending upon the substituents attached to the biphenyl and aryl functionalities. Among those synthesized compounds, the compounds 1–24 and 1–26 showed the best binding affinities to the 5-HT₇ receptor with K_i values of 43.0 and 46.0 nM, respectively. Structure–activity relationship study in conjunction with molecular docking study proposed that the 5-HT₇ receptor might have two distinctive hydrophobic binding sites, one specific for aromatic 2-OCH₃ substituents within the arylpiperazine and the other for biphenyl methoxy group.     

Application of higher order statistics for atrial arrhythmia classification

Atrial fibrillation (AF) and atrial flutter (AFL) are the two common atrial arrhythmia encountered in the clinical practice. In order to diagnose these abnormalities the electrocardiogram (ECG) is widely used. The conventional linear time and frequency domain methods cannot decipher the hidden complexity present in these signals. The ECG is inherently a non-linear, non-stationary and non-Gaussian signal. The non-linear models can provide improved results and capture minute variations present in the time series. Higher order spectra (HOS) is a non-linear dynamical method which is highly rugged to noise. In the present study, the performances of two methods are compared: (i) 3rd order HOS cumulants and (ii) HOS bispectrum. The 3rd order cumulant and bispectrum coefficients are subjected to dimensionality reduction using independent component analysis (ICA) and classified using classification and regression tree (CART), random forest (RF), artificial neural network (ANN) and k-nearest neighbor (KNN) classifiers to select the best classifier. The ICA components of cumulant coefficients have provided the average accuracy, sensitivity, specificity and positive predictive value of 99.50%, 100%, 99.22% and 99.72% respectively using KNN classifier. Similarly, the ICA components of HOS bispectrum coefficients have yielded the average accuracy, sensitivity, specificity and PPV of 97.65%, 98.16%, 98.75% and 99.53% respectively using KNN. So, the ICA performed on the 3rd order HOS cumulants coupled with KNN classifier performed better than the HOS bispectrum method. The proposed methodology is robust and can be used in mass screening of cardiac patients.     

ECG beat classification using PCA,LDA, ICA and Discrete Wavelet Transform

Electrocardiogram (ECG) is the P-QRS-T wave, representing the cardiac function. The information concealed in the ECG signal is useful in detecting the disease afflicting the heart. It is very difficult to identify the subtle changes in the ECG in time and frequency domains. The Discrete Wavelet Transform (DWT) can provide good time and frequency resolutions and is able to decipher the hidden complexities in the ECG. In this study, five types of beat classes of arrhythmia as recommended by Association for Advancement of Medical Instrumentation (AAMI) were analyzed namely: non-ectopic beats, supra-ventricular ectopic beats, ventricular ectopic beats, fusion betas and unclassifiable and paced beats. Three dimensionality reduction algorithms; Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA) and Independent Component Analysis (ICA) were independently applied on DWT sub bands for dimensionality reduction. These dimensionality reduced features were fed to the Support Vector Machine (SVM), neural network (NN) and probabilistic neural network (PNN) classifiers for automated diagnosis. ICA features in combination with PNN with spread value (σ) of 0.03 performed better than the PCA and LDA. It has yielded an average sensitivity, specificity, positive predictive value (PPV) and accuracy of 99.97%, 99.83%, 99.21% and 99.28% respectively using ten-fold cross validation scheme.     

Prediction of drugs having opposite effects on disease genes in a directed network

Background

Developing novel uses of approved drugs, called drug repositioning, can reduce costs and times in traditional drug development. Network-based approaches have presented promising results in this field. However, even though various types of interactions such as activation or inhibition exist in drug-target interactions and molecular pathways, most of previous network-based studies disregarded this information.

Methods

We developed a novel computational method, Prediction of Drugs having Opposite effects on Disease genes (PDOD), for identifying drugs having opposite effects on altered states of disease genes. PDOD utilized drug-drug target interactions with ‘effect type’, an integrated directed molecular network with ‘effect type’ and ‘effect direction’, and disease genes with regulated states in disease patients. With this information, we proposed a scoring function to discover drugs likely to restore altered states of disease genes using the path from a drug to a disease through the drug-drug target interactions, shortest paths from drug targets to disease genes in molecular pathways, and disease gene-disease associations.

Results

We collected drug-drug target interactions, molecular pathways, and disease genes with their regulated states in the diseases. PDOD is applied to 898 drugs with known drug-drug target interactions and nine diseases. We compared performance of PDOD for predicting known therapeutic drug-disease associations with the previous methods. PDOD outperformed other previous approaches which do not exploit directional information in molecular network. In addition, we provide a simple web service that researchers can submit genes of interest with their altered states and will obtain drugs seeming to have opposite effects on altered states of input genes at http://gto.kaist.ac.kr/pdod/index.php/main.

Conclusions

Our results showed that ‘effect type’ and ‘effect direction’ information in the network based approaches can be utilized to identify drugs having opposite effects on diseases. Our study can offer a novel insight into the field of network-based drug repositioning.

     

A Lightweight Radio Propagation Model for Vehicular Communication in Road Tunnels

Radio propagation models (RPMs) are generally employed in Vehicular Ad Hoc Networks (VANETs) to predict path loss in multiple operating environments (e.g. modern road infrastructure such as flyovers, underpasses and road tunnels). For example, different RPMs have been developed to predict propagation behaviour in road tunnels. However, most existing RPMs for road tunnels are computationally complex and are based on field measurements in frequency band not suitable for VANET deployment. Furthermore, in tunnel applications, consequences of moving radio obstacles, such as large buses and delivery trucks, are generally not considered in existing RPMs. This paper proposes a computationally inexpensive RPM with minimal set of parameters to predict path loss in an acceptable range for road tunnels. The proposed RPM utilizes geometric properties of the tunnel, such as height and width along with the distance between sender and receiver, to predict the path loss. The proposed RPM also considers the additional attenuation caused by the moving radio obstacles in road tunnels, while requiring a negligible overhead in terms of computational complexity. To demonstrate the utility of our proposed RPM, we conduct a comparative summary and evaluate its performance. Specifically, an extensive data gathering campaign is carried out in order to evaluate the proposed RPM. The field measurements use the 5 GHz frequency band, which is suitable for vehicular communication. The results demonstrate that a close match exists between the predicted values and measured values of path loss. In particular, an average accuracy of 94% is found with R² = 0.86.     

Tissue expression and cellular localization of phospholipid hydroperoxide glutathione peroxidase (PHGPx) mRNA in male mice

Phospholipid hydroperoxide glutathione peroxidase (PHGPx) is an ubiquitous antioxidant enzyme, but the exact expression pattern in mammalian tissues is still unknown. The expression and cellular localization of PHGPx mRNA were examined in male mice using real time-polymerase chain reaction and in situ hybridization techniques. The rank order of PHGPx mRNA expression across tissues exhibiting substantial levels of expression was:testes ≫ heart > cerebrum ≥ ileum > stomach = liver = jejunum ≥ epididymis. In testes, PHGPx mRNA was highly expressed in spermiogenic cells and Leydig cells. The signal was also expressed in the molecular layer, Purkinje cell layer, and white matter of cerebellum, the pituicytes of neurohypophysis, the parafollicular cells and follicular basement membrane of thyroid, the exocrine portion of pancreas, the tubular epithelium of kidney, the smooth muscle cells of arteries, and the red pulp of spleen. In the gastrointestinal tract, PHGPx mRNA expression was mainly observed in the keratinized surface epithelium of forestomach, the submucosal glands and serosa layers, and further the Paneth cells of intestines. PHGPx mRNA appeared to be ubiquitously expressed in the parenchyma of heart, liver, and lung. These results indicate that PHGPx exhibits a cell- and tissue-specific expression pattern in mice.     

In vivo surveillance and elimination of teratoma-forming human embryonic stem cells with monoclonal antibody 2448 targeting annexin A2

This study describes the use of a previously reported chimerised monoclonal antibody (mAb), ch2448, to kill human embryonic stem cells (hESCs) in vivo and prevent or delay the formation of teratomas. ch2448 was raised against hESCs and was previously shown to effectively kill ovarian and breast cancer cells in vitro and in vivo. The antigen target was subsequently found to be Annexin A2, an oncofetal antigen expressed on both embryonic cells and cancer cells. Against cancer cells, ch2448 binds and kills via antibody-dependent cell-mediated cytotoxicity (ADCC) and/or antibody-drug conjugate (ADC) routes. Here, we investigate if the use of ch2448 can be extended to hESC. ch2448 was found to bind specifically to undifferentiated hESC but not differentiated progenitors. Similar to previous study using cancer cells, ch2448 kills hESC in vivo either indirectly by eliciting ADCC or directly as an ADC. The treatment with ch2448 post-transplantation eliminated the in vivo circulating undifferentiated cells and prevented or delayed the formation of teratomas. This surveillance role of ch2448 adds an additional layer of safeguard to enhance the safety and efficacious use of pluripotent stem cell-derived products in regenerative medicine. Thereby, translating the use of ch2448 in the treatment of cancers to a proof of concept study in hESC (or pluripotent stem cell [PSC]), we show that mAbs can also be used to eliminate teratoma forming cells in vivo during PSC-derived cell therapies. We propose to use this strategy to complement existing methods to eliminate teratoma-forming cells in vitro. Residual undifferentiated cells may escape in vitro removal methods and be introduced into patients together with the differentiated cells.     

Total synthesis and biological evaluation of methylgerambullone

First total synthesis of methylgerambullone (MGB, 1) isolated from Glycosmis angustifolia was completed via a convergent route. The effect of MGB on the contractile responses of the isolated guinea-pig ileum induced by acetylcholine was investigated. As a result, it showed a potent relaxation rate (78.66 ± 4.30% at 100 mg/L) in a concentration-dependent manner on longitudinal smooth muscle contraction of isolated guinea-pig ileum induced by 1 μM acetylcholine.