Highlights Web server for MD-TASK and MODE-TASK, with new tools and updates. Eight dynamic residue network centrality metrics for analyzing protein molecular dynamics, extended for static proteins. Comparative essential dynamics for improved comparison of independent molecular dynamic simulations of related proteins. A communication propensity tool for evaluating residue communication efficiency. Normal mode analysis of proteins from static structures and molecular dynamic simulations.
SummaryMODE-TASK, a novel and versatile software suite, comprises Principal 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. Beside the command line function, a GUI has been developed as a PyMOL plugin.Availability and implementationMODE-TASK is open source, and available for download from https://github.com/RUBi-ZA/MODE-TASK. It is implemented in Python and C++. It is compatible with Python 2.x and Python 3.x and can be installed by Conda.Supplementary information Supplementary data are available at Bioinformatics online.
The development of automated servers to predict the three-dimensional structure of proteins has seen much progress over the years. These servers make calculations simpler, but largely exclude users from the process. In this study, we present the PRotein Interactive MOdeling (PRIMO) pipeline for homology modeling of protein monomers. The pipeline eases the multi-step modeling process, and reduces the workload required by the user, while still allowing engagement from the user during every step. Default parameters are given for each step, which can either be modified or supplemented with additional external input. PRIMO has been designed for users of varying levels of experience with homology modeling. The pipeline incorporates a user-friendly interface that makes it easy to alter parameters used during modeling. During each stage of the modeling process, the site provides suggestions for novice users to improve the quality of their models. PRIMO provides functionality that allows users to also model ligands and ions in complex with their protein targets. Herein, we assess the accuracy of the fully automated capabilities of the server, including a comparative analysis of the available alignment programs, as well as of the refinement levels used during modeling. The tests presented here demonstrate the reliability of the PRIMO server when producing a large number of protein models. While PRIMO does focus on user involvement in the homology modeling process, the results indicate that in the presence of suitable templates, good quality models can be produced even without user intervention. This gives an idea of the base level accuracy of PRIMO, which users can improve upon by adjusting parameters in their modeling runs. The accuracy of PRIMO’s automated scripts is being continuously evaluated by the CAMEO (Continuous Automated Model EvaluatiOn) project. The PRIMO site is free for non-commercial use and can be accessed at https://primo.rubi.ru.ac.za/.
MDM-TASK-web is the web server for the MD-TASK and MODE-TASK software suites. The web server simplifies the set-up for computing and visualizing results from dynamic residue networks, perturbation-response scanning, dynamic cross-correlation, essential dynamics, normal mode analysis and coordination-propensity. Upgrades and new functionalities to these software suites have also been introduced via the web server. An embedded work-flow, integrated documentation and 3D visualization functionality allow for a more intuitive and easy-to-use web platform.The web server is available at https://mdmtaskweb.rubi.ru.ac.za/. It is Django-based using a MySQL database and is compatible with all major web browsers.
Background South African Natural Compounds Database (SANCDB; https://sancdb.rubi.ru.ac.za/) is the sole and a fully referenced database of natural chemical compounds of South African biodiversity. It is freely available, and since its inception in 2015, the database has become an important resource to several studies. Its content has been: used as training data for machine learning models; incorporated to larger databases; and utilized in drug discovery studies for hit identifications. Description Here, we report the updated version of SANCDB. The new version includes 412 additional compounds that have been reported since 2015, giving a total of 1012 compounds in the database. Further, although natural products (NPs) are an important source of unique scaffolds, they have a major drawback due to their complex structure resulting in low synthetic feasibility in the laboratory. With this in mind, SANCDB is, now, updated to provide direct links to commercially available analogs from two major chemical databases namely Mcule and MolPort. To our knowledge, this feature is not available in other NP databases. Additionally, for easier access to information by users, the database and website interface were updated. The compounds are now downloadable in many different chemical formats. Conclusions The drug discovery process relies heavily on NPs due to their unique chemical organization. This has inspired the establishment of numerous NP chemical databases. With the emergence of newer chemoinformatic technologies, existing chemical databases require constant updates to facilitate information accessibility and integration by users. Besides increasing the NPs compound content, the updated SANCDB allows users to access the individual compounds (if available) or their analogs from commercial databases seamlessly. Graphic abstract
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