N-phenyl ureidobenzenesulfonates,a novel class of promising human dihydroorotate dehydrogenase inhibitors

N-phenyl ureidobenzenesulfonates (PUB-SOs) is a new class of promising anticancer agents inducing replication stresses and cell cycle arrest in S-phase. However, the pharmacological target of PUB-SOs was still unidentified. Consequently, the objective of the present study was to identify and confirm the pharmacological target of the prototypical PUB-SO named 2-ethylphenyl 4-(3-ethylureido)benzenesulfonate (SFOM-0046) leading to the cell cycle arrest in S-phase. The antiproliferative and the cytotoxic activities of SFOM-0046 were characterized using the NCI-60 screening program and its fingerprint was analyzed by COMPARE algorithm. Then, human dihydroorotate dehydrogenase (hDHODH) colorimetric assay, uridine rescuing cell proliferation and molecular docking in the brequinar-binding site were performed. As a result, SFOM-0046 exhibited a mean antiproliferative activity of 3.5 μM in the NCI-60 screening program and evidenced that leukemia and colon cancer cell panels were more sensitive to SFOM-0046. COMPARE algorithm showed that the SFOM-0046 cytotoxic profile is equivalent to the ones of brequinar and dichloroallyl lawsone, two inhibitors of hDHODH. SFOM-0046 inhibited the hDHODH in the low nanomolar range (IC₅₀ = 72 nM) and uridine rescued the cell proliferation of HT-29, HT-1080, M21 and MCF-7 cancer cell lines in the presence of SFOM-0046. Finally, molecular docking showed a binding pose of SFOM-0046 interacting with Met43 and Phe62 present in the brequinar-binding site. In conclusion, PUB-SOs and notably SFOM-0046 are new small molecules hDHODH inhibitors triggering replication stresses and S-phase arrest.     

A novel Golgi mannosidase inhibitor: Molecular design,synthesis, enzyme inhibition,and inhibition of spheroid formation

Effective chemotherapy for solid cancers is challenging due to a limitation in permeation that prevents anticancer drugs from reaching the center of the tumor, therefore unable to limit cancer cell growth. To circumvent this issue, we planned to apply the drugs directly at the center by first collapsing the outer structure. For this, we focused on cell–cell communication (CCC) between N-glycans and proteins at the tumor cell surface. Mature N-glycans establish CCC; however, CCC is hindered when numerous immature N-glycans are present at the cell surface. Inhibition of Golgi mannosidases (GMs) results in the transport of immature N-glycans to the cell surface. This can be employed to disrupt CCC. Here, we describe the molecular design and synthesis of an improved GM inhibitor with a non-sugar mimic scaffold that was screened from a compound library. The synthesized compounds were tested for enzyme inhibition ability and inhibition of spheroid formation using cell-based methods. Most of the compounds designed and synthesized exhibited GM inhibition at the cellular level. Of those, AR524 had higher inhibitory activity than a known GM inhibitor, kifunensine. Moreover, AR524 inhibited spheroid formation of human malignant cells at low concentration (10 µM), based on the disruption of CCC by GM inhibition.     

Physiological functions of the TRPM4 channels via protein interactions

Transient Receptor Potential, Melastatin-related, member 4 (TRPM4) channels are Ca²⁺-activated Ca²⁺-impermeable cation channels. These channels are expressed in various types of mammalian tissues including the brain and are implicated in many diverse physiological and pathophysiological conditions. In the past several years, the trafficking processes and regulatory mechanism of these channels and their interacting proteins have been uncovered. Here in this minireview, we summarize the current understanding of the trafficking mechanism of TRPM4 channels on the plasma membrane as well as heteromeric complex formation via protein interactions. We also describe physiological implications of protein-TRPM4 interactions and suggest TRPM4 channels as therapeutic targets in many related diseases. [BMB Reports 2015; 48(1): 1-5]     

Design,synthesis and in vitro pharmacology of GluK1 and GluK3 antagonists. Studies towards the design of subtype-selective antagonists through 2-carboxyethyl-phenylalanines with substituents interacting with non-conserved residues in the GluK binding sites

In order to identify compounds selective for the GluK1 and GluK3 subtypes of kainate receptors we have designed and synthesized a series of (S)-2-amino-3-((2-carboxyethyl)phenyl)propanoic acid analogs with hydrogen bond donating and accepting substituents on the aromatic ring. Based on crystal structures of GluK1 in complex with related ligands, the compounds were designed to explore possible interactions with non-conserved residues outside the glutamate ligand binding site and challenge the water binding network. Apart from obtaining GluK1 selective antagonists one analog with a phenyl-substituted urea (compound 31) showed some preference for GluK3 over GluK1-receptors. Docking studies indicate that this preference may be attributed to contacts between the NH of the urea substituent and non-conserved Ser741 and Ser761 residues.     

Abnormality in Translational Regulation of Catalase Expression in Disorders of Peroxisomal Biogenesis

Abstract: Peroxisomal disorders are a newly described group of inherited neurological diseases. In disorders of peroxisomal biogenesis, e.g., Zellweger syndrome, owing to the lack of peroxisomes, catalase, a peroxisomal enzyme, is found to be present in the cytoplasm instead. We observed higher catalase activity (7.59 ± 0.41 mU/mg of protein) in cultured skin fibroblasts from Zellweger patients than in control fibroblasts (4.45 ± 0.29 mU/mg of protein). Moreover, we also found that the majority of the catalase in Zellweger cells was present in the inactive form. The specific activities following reactivation in Zellweger and control cells were 12.1 and 4.9 mU/mg of protein, respectively. To understand the molecular basis of higher levels of catalase in Zellweger than control cells, we examined the rate of synthesis and turnover of catalase and levels of catalase mRNA and protein levels in Zellweger cells as compared with control cells. The initial rates of synthesis of catalase in Zellweger (1.68 ± 0.15 mU/mg of protein) and control (1.51 ± 0.14 mU/mg of protein) cells were similar. The rates of turnover of catalase in Zellweger (t_1/2 = 47 ± 8 h) and control (t_1/2 = 49 ± 7 h) were also similar. Consistent with the enzyme activity, the levels of catalase protein were higher in Zellweger cells as compared with control cells. On the other hand, there was no difference in the level of catalase mRNA between control and Zellweger cells. Although the rate of synthesis in Zellweger and control cells were initially similar, it was down-regulated to a lower level at ～72 h of culture in control fibroblasts as compared with Zellweger cells, which continued to synthesize catalase at the same rate up to 5 days in culture. The presence of similar levels of mRNA in control and Zellweger cells and continued synthesis of catalase in Zellweger cells at a higher level as compared with control cells suggest a loss of regulation at the translational level.     

Automatic detection of pulmonary nodules in CT images by incorporating 3D tensor filtering with local image feature analysis

Computer-aided detection (CAD) technology has been developed and demonstrated its potential to assist radiologists in detecting pulmonary nodules especially at an early stage. In this paper, we present a novel scheme for automatic detection of pulmonary nodules in CT images based on a 3D tensor filtering algorithm and local image feature analysis. We first apply a series of preprocessing steps to segment the lung volume and generate the isotropic volumetric CT data. Next, a unique 3D tensor filtering approach and local image feature analysis are used to detect nodule candidates. A 3D level set segmentation method is used to correct and refine the boundaries of nodule candidates subsequently. Then, we extract the features of the detected candidates and select the optimal features by using a CFS (Correlation Feature Selection) subset evaluator attribute selection method. Finally, a random forest classifier is trained to classify the detected candidates. The performance of this CAD scheme is validated using two datasets namely, the LUNA16 (Lung Nodule Analysis 2016) database and the ANODE09 (Automatic Nodule Detection 2009) database. By applying a 10-fold cross-validation method, the CAD scheme yielded a sensitivity of 79.3% at an average of 4 false positive detections per scan (FP/Scan) for the former dataset, and a sensitivity of 84.62% and 2.8 FP/Scan for the latter dataset, respectively. Our detection results show that the use of 3D tensor filtering algorithm combined with local image feature analysis constitutes an effective approach to detect pulmonary nodules.