Medicinal Chemistry - Volume 13, Issue 6, 2017

Background: Proteomics endeavors to study the structures, functions and interactions of proteins. Information of the protein-protein interactions (PPIs) helps to improve our knowledge of the functions and the 3D structures of proteins. Thus determining the PPIs is essential for the study of the proteomics. Objective: In this review, in order to study the application of machine learning in predicting PPI, some machine learning approaches such as support vector machine (SVM), artificial neural networks (ANNs) and random forest (RF) were selected, and the examples of its applications in PPIs were listed. Results: SVM and RF are two commonly used methods. Nowadays, more researchers predict PPIs by combining more than two methods. Conclusion: This review presents the application of machine learning approaches in predicting PPI. Many examples of success in identification and prediction in the area of PPI prediction have been discussed, and the PPIs research is still in progress.

Background: RNA-protein interactions (RPIs) play an important role in many cellular processes. In particular, noncoding RNA-protein interactions (ncRPIs) are involved in various gene regulations and human complex diseases. High-throughput experiments have provided a large number of valuable information about ncRPIs, but these experiments are expensive and timeconsuming. Therefore, some computational approaches have been developed to predict ncRPIs efficiently and effectively. Methods: In this work, we will describe the recent advance of predicting ncRPIs from the following aspects: i) the dataset construction; ii) the sequence and structural feature representation, and iii) the machine learning algorithm. Results: The current methods have successfully predicted ncRPIs, but most of them trained and tested on the small benchmark datasets derived from ncRNA-protein complexes in PDB database. The generalization performance and robust of these existing methods need to be further improved. Conclusion: Concomitant with the large numbers of ncRPIs generated by high-throughput technologies, three future directions for predicting ncRPIs with machine learning should be paid attention. One direction is that how to effectively construct the negative sample set. Another is the selection of novel and effective features from the sequences and structures of ncRNAs and proteins. The third is the design of powerful predictor.

Small molecule drugs obtained from synthetic compounds or natural products show their therapeutic effects by specifically binding to one or a few target proteins and modulating their functions. In contrast, undesirable drug-protein interactions may provoke harmful side effects. Furthermore, drug-protein interactions also play roles in drug activation, transport, metabolism and regulation of drug resistance. Therefore, systematically identifying binding proteins of a drug molecule is critical for understanding the mechanism of action of the drug at molecular level. In this review, we summarize current widely-used experimental approaches for proteome-wide target identification of small molecule drugs, including affinity purification, chemical proteomics and protein thermal stability based methods. The advance of these methods will quicken the pace of target deconvolution of small molecule drugs and hold promise for drug repositioning research. Moreover, these approaches also provide a powerful arsenal for exploring the signaling pathways of small molecule second messengers, signaling lipids and other regulatory metabolites.

During the last two decades, C-type lectin receptors (CLRs) have been demonstrated to play key roles in initiating the host immune response against fungal infection. It is well established that CLRs, such as Dectin-1, Dectin-2, Dectin-3 and Mincle recognize the cell wall component from the infected microorganisms by using their carbohydrate recognition domain (CRD). Upon stimulation, CLRs induce multiple signal transduction cascades through their own immunereceptor tyrosine-based activation motifs (ITAMs) or interacting with ITAM-containing adaptor proteins such as FcRγ, which then lead to the activation of nuclear factor kappa B (NF-ΚB) through Syk- and CARD9-dependent pathway. Dissecting CLR signal cascades and their effects on host immune cells is essential to understand the molecular mechanisms in regulating host antifungal immunity. Recently, the activated CLRs including Dectin-1 and Dectin-2 are reported to undergo lysome-mediated degradation by an E3 ubiquitin ligase CBL-b. Moreover, structural analysis will help understand the molecular mechanism of these CLRs and provide clues to rational design for effective anti-fungal drugs. Overall, we summarize the current knowledge on activating and inhibitory CLRs and discuss how to boost host immune system to fight against invasive fungal infection.

Background: Occurring at the cysteine residue in the C-terminal of a protein, prenylation is a special kind of post-translational modification (PTM), which may play a key role for statin in altering immune function. Therefore, knowledge of the prenylation sites in proteins is important for drug development as well as for in-depth understanding the biological process concerned. Objective: Given a query protein whose C-terminal contains some cysteine residues, which one can be of prenylation or none of them can be prenylated? Methods: To address this problem, we have developed a new predictor, called “iPreny-PseAAC”,by incorporating two tiers of sequence pair coupling effects into the general form of PseAAC (pseudo amino acid composition). Results: It has been observed by four different cross-validation approaches that all the important indexes in reflecting its prediction quality are quite high and fully consistent to each other. Conclusion: It is anticipated that the iPreny-PseAAC predictor holds very high potential to become a useful high throughput tool in identifying protein C-terminal cysteine prenylation sites and the other relevant areas. To maximize the convenience for most experimental biologists, the webserver for the new predictor has been established at http://app.aporc.org/iPreny-PseAAC/, by which users can easily get their desired results without needing to go through the mathematical details involved in this paper.

Background: Occurring at Lys residues, the PGK (lysine phosphoglycerylation) is a special kind of post-translational modification (PTM). It may invert the charge potential of the modified residue and change the protein structures and functions, causing various diseases in liver, brain, and kidney. Objective: From the angles of both basic research and drug development, we are facing a critical challenging problem: for an uncharacterized protein sequence containing many Lys residues, which ones can be of phosphoglycerylation, and which ones cannot? Method: To address this problem, we have developed a predictor called iPGK-PseAAC by incorporating into the general PseAAC (pseudo amino acid composition) with four different tiers of amino acid pairwise coupling information, where tiers 1, 2, 3, and 4 refer to the amino acid pairwise couplings between all the 1st, 2nd, 3rd, and 4th most contiguous residues along a protein segment, respectively. Results: Rigorous cross-validations indicated that the proposed predictor remarkably outperformed its existing counterparts. Conclusion: The proposed predictor iPGK-PseAAC will become a very useful bioinformatics tool for medicinal chemistry. For the convenience of most experimental scientists, a user-friendly webserver for iGPK-PseAAC has been established at http://app.aporc.org/iPGK-PseAAC/, by which users can easily obtain their desired results without the need to go through the complicated mathematical equations involved.

Objective: Chlorella vulgaris (C. vulgaris), a unicellular green microalga, has been widely used as a food supplement and reported to have antioxidant and anticancer properties. The current study was designed to assess the cytotoxic, apoptotic, and DNA-damaging effects of C. vulgaris growth factor (CGF), hot water C. vulgaris extracts, inlung tumor A549 and NCI-H460 cell lines. Methods: A549 cells, NCI-H460 cells, and normal human fibroblasts were treated with CGF at various concentrations (0-300 μg/ml) for 24 hr. The comet assay and γH2AX assay showed DNA damage in A549 and NCI-H460 cells upon CGF exposure. Evaluation of apoptosis by the TUNEL assay and DNA fragmentation analysis by agarose gel electrophoresis showed that CGF induced apoptosis in A549 and NCI-H460 cells. Results: Chlorella vulgaris hot water extract induced apoptosis and DNA damage in human lung carcinoma cells. Conclusion: CGF can thus be considered a potential cytotoxic or genotoxic drug for treatment of lung carcinoma.

Background: Toll-like receptor-2 (TLR2) and Toll-like receptor-4 (TLR4) have been reported to play a crucial role in tuberculosis, however, little is known about their expression in tuberculous pleuritis. Objective: The goal of this work is to explore the expressions of TLR2 and TLR4 in tuberculous pleuritis and their predominant expressions on cells. Methods: Levels of soluble TLR2 and TLR4 by enzyme linked immunosorbent assay (ELISA) in 58 patients with tuberculous pleural effusion (PE) and 43 patients with malignant PE were determined. The related genes were analyzed by RT-PCR and the membrane expressions of TLR2 and TLR4 on CD3+, CD14+, and CD19+ monocytes were assessed by using flow cytometry in 20 of 58 patients with tuberculous pleuritis. Results: Our results showed that the levels of ADA, IL-27 and IFN-γ in tuberculous PE were obviously higher than in malignant PE. Moreover, the concentrations of soluble TLR2 and soluble TLR4 in PE were significantly higher than those in peripheral blood of the same patients, as well as the levels of soluble TLR2 in tuberculous PE were significantly higher than those in malignant effusions. Furthermore, the levels of TLR2, TLR4 and IFN-γ mRNA expression were marked increased in the tuberculous PE when compared with the correspondent serum. Importantly, we found that the predominant expressions of TLR2 in monocyte were on CD19 B cells, and the predominant expressions of TLR4 were on CD14 monocytes/macrophages. Conclusion: Our findings provided the evidence of a role for TLRs expression in tuberculous PE.

Background: Benzimidazoles are important pharmacophores in drug discovery, and currently its derivatives such as flubendazole, omeprazole, and astemizole are used for the treatment of anthelmintic, ulcerative, and histaminic diseases, respectively. Objectives: The aim of the current study was to investigate the antiglycation activity of nitrobenzimidazole derivatives against fructose-mediated human serum albumin (HSA) glycation. The study was also aimed at investigating the effects of newly identified antiglycation inhibitors on AGEsinduced intracellular reactive oxygen species (ROS) production, and associated impaired proliferation of the hepatocytes. Methods: The present study focuses on the antiglycation activity of 6-nitrobenzimidazole derivatives 1-13 in in-vitro human serum albumin (HSA)- fructose model. These derivatives were also identified as non-toxic against 3T3 mouse fibroblast cell-line in MTT-based assay. The effect of the most promising derivative 5, 4-(6-nitro-1H-benzimidazol-2-yl)-1,2,3-benzenetriol, was studied in a dose dependent manner, co-incubated with fructose-derived AGEs (0- 200 μg/mL) on rat hepatocytes proliferation and associated intracellular generation of ROS via MTT-based assay and DCFHDA technique, respectively. Results: We found that derivative 5 ameliorates the elevated intracellular oxidative stress and associated diminished proliferation of the hepatocytes in response to AGEs. Conclusion: In conclusion, we identified novel 6-nitrobenzimidazole derivatives as antiglycation agents through in-vitro, and cell-based models.

Background: Uric acid is the end product of purine metabolism in humans and its increased level in serum leads to hyperuricemia. Among the different regulatory factors to control the level of uric acid in humans, xanthine oxidase (XO) is a well-established pharmacological target, as it is directly involved in uric acid production. Methods: The aim of the study was to present a systematic approach to analyze the xanthine oxidase inhibition studies from in vitro leading to in vivo. Results: Initially, dinuclear cyclam complex 1 was evaluated for in-vitro XO inhibitory activity using a spectrophotometric assay. Significant results were obtained in XO inhibition assay (IC50 = 3.70 ± 0.07 μM), in comparison to the standard drug, allopurinol (IC50 = 2.00 ± 0.01 μM). Complex 1 showed a non-competitive type of inhibition in kinetic studies. Complex 1 was also found to be non-cytotoxic in MTT assay, as it did not affect the viability of 3T3-cell line. Based on these results, compound 1 was further evaluated for the in-vivo xanthine oxidase inhibitory activity. An in-vivo model was used to evaluate the XO inhibitory activity in plasma samples of male Wistar rats. Complex 1 showed a significant inhibition of xanthine oxidase activity (50%), in comparison to the standard inhibitor allopurinol (100%). Therefore, non-cytotoxic compound 1 could be considered as an anti-hyperurecemic lead for further studies. Conclusion: Our studies concluded that complex 1 is a non-cytotoxic inhibitor that decreases the activity of XO in a non-competitive manner. It can serve as a potential anti-hyperurecemic lead after further pre-clinical and clinical studies.

Background: Bergenin, a compound derived from gallic acid, is a secondary metabolite of the plant Peltophorum dubium (Spreng.) Taub. Objective: In this study, we aimed to characterize the ability of bergenin to eliminate the radicals in non-biological systems. Methods: We evaluated bergenin's ability to protect erythrocytes from oxidative damage in a biological system. We have elucidated bergenin structure using nuclear magnetic resonance, X-ray diffraction, Fourier transform infrared spectroscopy, and differential scanning calorimetry. We then evaluated its antioxidant capacity in vitro against DPPH· , ABTS· +, hydroxyl radicals, and nitric oxide, and determined its ability to transfer electrons owing to its reduction potential and ability to chelate iron. We also evaluated its protective capacity against oxidative damage produced by AAPH in erythrocytes, its hemolytic properties, its ability to inhibit hemolysis, and its ability to maintain intracellular reduced glutathione homeostasis. Results: Bergenin concentrations between 0.1 and 3mM significantly (p < 0.05) and dose dependently decreased formation of ABTS · +, DPPH·, nitrite ions, OH., reduced formation ferricyanide, ferrozine-Fe2+complex, inhibited AAPH-induced oxidative hemolysis of erythrocytes, raised GSH levels in the presence of AAPH, inhibited AAPH-induced lipid peroxidation in erythrocytes. Conclusion: Bergenin may represent a novel alternative antioxidant, with potential applications in various industries, including drugs, cosmetics, and foods.