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Protein post-translational modifications (PTM) play vital roles in cellular regulation, modulating functions by driving changes in protein structure and dynamics. Exploring comprehensively the influence of PTM on conformational dynamics can facilitate the understanding of the related biological function and molecular mechanism. Currently, a series of excellent computation tools have been designed to analyze the time-dependent structural properties of proteins. However, the protocol aimed to explore conformational dynamics of post-translational modified protein is still a blank. To fill this gap, we present PTMdyna to visually predict the conformational dynamics differences between unmodified and modified proteins, thus indicating the influence of specific PTM. PTMdyna exhibits an AUC of 0.884 tested on 220 protein–protein complex structures. The case of heterochromatin protein 1α complexed with lysine 9-methylated histone H3, which is critical for genomic stability and cell differentiation, was used to demonstrate its applicability. PTMdyna provides a reliable platform to predict the influence of PTM on protein dynamics, making it easier to interpret PTM functionality at the structure level. The web server is freely available at http://ccbportal.com/PTMdyna. [ABSTRACT FROM AUTHOR]

Effective drug discovery contributes to the treatment of numerous diseases but is limited by high costs and long cycles. The Quantitative Structure–Activity Relationship (QSAR) method was introduced to evaluate the activity of a large number of compounds virtually, reducing the time and labor costs required for chemical synthesis and experimental determination. Hence, this method increases the efficiency of drug discovery. To meet the needs of researchers to utilize this technology, numerous QSAR-related web servers, such as Web-4D-QSAR and DPubChem, have been developed in recent years. However, none of the servers mentioned above can perform a complete QSAR modeling and supply activity prediction functions. We introduce Cloud 3D-QSAR by integrating the functions of molecular structure generation, alignment, molecular interaction field (MIF) computing and results analysis to provide a one-stop solution. We rigidly validated this server, and the activity prediction correlation was R 2 = 0.934 in 834 test molecules. The sensitivity, specificity and accuracy were 86.9%, 94.5% and 91.5%, respectively, with AUC = 0.981, AUCPR = 0.971. The Cloud 3D-QSAR server may facilitate the development of good QSAR models in drug discovery. Our server is free and now available at http://chemyang.ccnu.edu.cn/ccb/server/cloud3dQSAR/ and http://agroda.gzu.edu.cn:9999/ccb/server/cloud3dQSAR/. [ABSTRACT FROM AUTHOR]

A clear systematic delineation of the interactions between phosphorylation sites on substrates and their effector kinases plays a fundamental role in revealing cellular activities, understanding signaling modulation mechanisms and proposing novel hypotheses. The emergence of bioinformatics tools contributes to studying phosphorylation network. Some of them feature the visualization of network, enabling more effective trace of the underlying biological problems in a clear and succinct way. In this review, we aimed to provide a toolbox for exploring phosphorylation network. We first systematically surveyed 19 tools that are available for exploring phosphorylation networks, and subsequently comparatively analyzed and summarized these tools to guide tool selection in terms of functionality, data sources, performance, network visualization and implementation, and finally briefly discussed the application cases of these tools. In different scenarios, the conclusion on the suitability of a tool for a specific user may vary. Nevertheless, easily accessible bioinformatics tools are proved to facilitate biological findings. Hopefully, this work might also assist non-specialists, students, as well as computational scientists who aim at developing novel tools in the field of phosphorylation modification. [ABSTRACT FROM AUTHOR]

In order to obtain a better fermentation parameter for the production of recombinant Ganoderma lucidum immunomodulatory protein (rFIP-glu), an engineered Pichia pastoris GS115 was investigated on the fermentation time, temperature, methanol concentration and initial pH of media, while immunomodulatory activities of the rFIP-glu was confirmed. L9(33) orthogonal experiment were firstly employed to optimize various fermentation parameters in the shake-flask level. The optimized fermentation parameters were subsequently verified in a 5 L fermenter. Biological activities including cell viability and tumor necrosis factor-alpha (TNF-α) mRNA of the rFIP-glu were evaluated on murine macrophage RAW264.7 cells. The results showed that the yield of rFIP-glu was up to 368.71 μg/ml in the shake-flask, and 613.47 μg/ml in the 5 L fermenter, when the Pichia pastoris was incubated in basic media with the methanol concentration 1.0% and initial pH 6.5, and with constant shaking at 280 rpm for 4 days at 26 °C. In vitro assays of biological activity indicated that rFIP-glu had significant toxicity against RAW264.7 cells, and possessed the ability to induce TNF-α mRNA expression in macrophage RAW264.7 cells. In conclusion, engineered P. pastoris showed a good fermentation property under the optimum fermentation parameters. It could be a candidate industrial strain for further study. [ABSTRACT FROM AUTHOR]

Background: Previous studies have indicated that neurite orientation dispersion and density imaging (NODDI) could be used as a biomarker for detecting microstructural changes of brain.Purpose: To quantitatively evaluate the changes in basal ganglia (BG) and thalamus in Wilson's disease (WD) by NODDI and assess the correlation between parameters and disease severity.Study Type: Prospective case-control study.Population: In total, 24 WD patients and 25 age- and sex-matched normal controls were involved in this study.Field Strength/sequence: EPI diffusion-weighted MR images (b-values = 0, 1000, and 2000 with 30 diffusion gradient directions) were acquired on a 3T scanner.Assessment: Diffusion data were analyzed using voxel-based analysis. NODDI indices including intracellular volume fraction (Vic), orientation dispersion index (ODI), and isotropic volume fraction (Viso) were estimated from the BG and thalamus. The disease severity was assessed by two experienced neurologists based on the Global Assessment Scale (GAS). The relative importance of NODDI indices in diagnosing WD and predictive accuracy were also analyzed.Statistical Testing: The Shapiro-Wilk test, Student's t-test, χ2 test, Mann-Whitney-Wilcoxon test, Spearman rank correlation coefficient analysis and random-forest analysis were used for statistical analyses.Results: The Vic and ODI in the BG and thalamus were significantly lower in WD patients than normal controls, while the Viso in the BG and thalamus were significantly higher (P < 0.01). The Vic in the putamen and ODI in the globus pallidus were negatively correlated with clinical severity (rvic = -0.727, P < 0.001; rodi = -0.705, P < 0.001). The Vic in the putamen was the most valuable predictor for diagnosing WD and the prediction accuracy of NODDI was 95.92%.Data Conclusion: NODDI can effectively evaluate the changes of microstructure and metabolism during copper deposition in WD, and thus, it is likely to be useful in detecting the changes in the brain of this disease and assessing its progression.Level Of Evidence: 2 Technical Efficacy Stage 2 J. MAGN. RESON. IMAGING 2018;48:423-430. [ABSTRACT FROM AUTHOR]