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Glenister, M.

Publications and source records attributed to Glenister, M..

3 recordsLinked to original sources

DNA template heterogeneity and in vitro transcription reaction conditions impact the poly(A) tail length and heterogeneity of mRNA

mRNA technology has emerged as a powerful new class of medicines. Importantly, this RNA-based approach holds promise for treatments beyond vaccines and infectious diseases, including treatments for cancer, metabolic disorders, cardiovascular conditions and autoimmune diseases. The 3-polyadenylated (poly(A)) tail of mRNA is required for ribosome initiation, translation, and mRNA stability and is considered a critical quality attribute. In this study, novel direct mass spectrometry approaches were used for the analysis of both the DNA template and corresponding mRNA generated via in vitro transcription. Nucleotide resolution of the poly(A/T) sequence of the DNA template and mRNA poly(A) tail was achieved. The results show that the mRNA poly(A) tail length and heterogeneity is impacted by the heterogeneity of the DNA template, the DNA template design and RNA manufacturing conditions, including relative NTP concentrations. These results provide further important mechanistic insight into the poly(A) tail length and heterogeneity of mRNAs synthesised in vitro, including the identification of 3-end additions of cytidine to mRNA poly(A) tails. The ability to rapidly assess DNA template quality, combined with monitoring mRNA poly(A) tail length and heterogeneity, is important as part of the characterisation of mRNA precision medicines and ensuring consistent quality of mRNA from manufacturing processes.

biochemistry↗

MDM-TASK-web: A web platform for protein dynamic residue networks and modal analysis

MDM-TASK-web is the web server for the MD-TASK and MODE-TASK software suites. It simplifies the set-up required to perform and visualize results from dynamic residue network analysis, perturbation-response scanning, dynamic cross-correlation, essential dynamics and normal mode analysis. In a nutshell, the server gives access to updated versions of the tool suites, and offers new functionalities and integrated 2D/3D visualization. An embedded work-flow, integrated documentation and visualization tools shortens the number of steps to follow, starting from calculations to result visualization. The web server (available at https://mdmtaskweb.rubi.ru.ac.za/) is powered by Django and a MySQL database, and is compatible with all major web browsers. All scripts implemented in the web platform are freely available at https://github.com/RUBi-ZA/MD-TASK/tree/mdm-task-web and https://github.com/RUBi-ZA/MODE-TASK/tree/mdm-task-web. HighlightsO_LIMDM-TASK-web is the web server for highly utilized MD-TASK and MODE-TASK with updates C_LIO_LIEight residue network centrality metrics are available to analyze static and dynamic proteins C_LIO_LINovel comparative essential dynamics is established to compare independent MD simulations C_LIO_LICommunication propensity tool to evaluate residue communication efficiency is implemented. C_LIO_LINormal mode analysis from static and protein MD simulations is provided C_LI

bioinformatics↗

MODE-TASK: Large-scale protein motion tools

SummaryMODE-TASK, a novel software suite, comprises Principle Component Analysis, Multidimensional Scaling, and t-Distributed Stochastic Neighbor Embedding techniques using molecular dynamics trajectories. MODE-TASK also includes a Normal Mode Analysis tool based on Anisotropic Network Model so as to provide a variety of ways to analyse and compare large-scale motions of protein complexes for which long MD simulations are prohibitive.\n\nAvailability and ImplementationMODE-TASK has been open-sourced, and is available for download from https://github.com/RUBi-ZA/MODE-TASK, implemented in Python and C++.\n\nSupplementary informationDocumentation available at http://mode-task.readthedocs.io.

bioinformatics↗