Search

Objective: Druggability of a target protein depends on the interacting micro-environment between the target protein and drugs. Therefore, a precise knowledge of the interacting micro-environment between the target protein and drugs is requisite for drug discovery process. To understand such micro-environment, we performed in silico interaction analysis between a human target protein, Dipeptidyl Peptidase-IV (DPP-4), and three anti-diabetic drugs (saxagliptin, linagliptin and vildagliptin). Materials and Methods: During the theoretical and bioinformatics analysis of micro-environmental properties, we performed drug-likeness study, protein active site predictions, docking analysis and residual interactions with the protein-drug interface. Micro-environmental landscape properties were evaluated through various parameters such as binding energy, intermolecular energy, electrostatic energy, van der Waals'+H-bond+desolvo energy (EVHD) and ligand efficiency (LE) using different in silico methods. For this study, we have used several servers and software, such as Molsoft prediction server, CASTp server, AutoDock software and LIGPLOT server. Results: Through micro-environmental study, highest log P value was observed for linagliptin (1.07). Lowest binding energy was also observed for linagliptin with DPP-4 in the binding plot. We also identified the number of H-bonds and residues involved in the hydrophobic interactions between the DPP-4 and the anti-diabetic drugs. During interaction, two H-bonds and nine residues, two H-bonds and eleven residues as well as four H-bonds and nine residues were found between the saxagliptin, linagliptin as well as vildagliptin cases and DPP-4, respectively. Conclusion: Our in silico data obtained for drug-target interactions and micro-environmental signature demonstrates linagliptin as the most stable interacting drug among the tested anti-diabetic medicines. [ABSTRACT FROM AUTHOR]

Objective: Research related to induce pluripotent stem (iPS) cell generation has increased rapidly in recent years. Six transcription factors, namely OCT4, SOX2, C-MYC, KLF4, NANOG, and LIN28 have been widely used for iPS cell generation. As there is a lack of data on intra- and inter-networking among these six different transcription factors, the objective of this study is to analyze the intra- and inter-networks between them using bioinformatics. Materials and Methods:In this computational biology study, we used AminoNet, MATLAB to examine networking between the six different transcription factors. The directed network was constructed using MATLAB programming and the distance between nodes was estimated using a phylogram. The protein-protein interactions between the nuclear reprogramming factors was performed using the software STRING. Results: The relationship between C-MYC and NANOG was depicted using a phylogenetic tree and the sequence analysis showed OCT4, C-MYC, NANOG, and SOX2 together share a common evolutionary origin. Conclusion: This study has shown an innovative rapid method for the analysis of intra and inter-networking among nuclear reprogramming factors. Data presented may aid researchers to understand the complex regulatory networks involving iPS cell generation. [ABSTRACT FROM AUTHOR]

Objectives: Osteoporosis is regarded as a silent disorder affecting bone slowly, leading to an increased risk of fractures. Lately, selenium has been found to be associated with the acquisition and maintenance of bone health by affecting the bone remodeling process. However, the mechanism of action of selenium on bone is poorly understood. Here, the objective of this study is to examine the protective effects and mechanism of sodium selenite on the differentiation process of osteoblasts as well as under oxidative stress-induced conditions by evaluating the expression of osteoblast differentiation markers in the sodium selenite and/or hydrogen peroxide (H2O2)-treated MC3T3-E1 cell line. Materials and Methods: In this experimental study, we confirmed the inducible osteogenic effect of sodium selenite on MC3T3-E1 cells. Moreover, we investigated the recovery of expression levels of osteogenic markers of sodium selenite in H2O2-treated MC3T3-E1 cells. Results: It was observed that sodium selenite could promote alkaline phosphatase (ALP) activity and collagen synthesis in pre-osteoblasts. Also, sodium selenite enhanced the mRNA expression levels of osteogenic transcriptional factors, like osterix (OSX) and runt-related transcription factor 2 (Runx2). In addition, the terminal differentiation markers, such as osteocalcin (OCN) and collagen 1α (Col1α) were also increased after the treatment of sodium selenite. Also treatment of sodium selenite recused the H2O2-induced inhibition of osteoblastic differentiation of pre-osteoblasts cells via the WNT signaling pathway, implicating its antioxidant activity. Furthermore, sodium selenite restored the H2O2 repressed β-catenin stability and axin-2 reporter activity in MC3T3-E1 cells. Conclusion: It may be concluded that sodium selenite can stimulate bone formation and rescue the oxidative repression of osteogenesis by activating WNT signaling pathways. Further detailed studies on the role of selenium and its ability to stimulate bone formation via the WNT signaling pathway may project it as a potential therapeutic intervention for osteoporosis. [ABSTRACT FROM AUTHOR]