MartiniGlass: a Tool for Enabling Visualization of Coarse-Grained Martini Topologies.

IF 5.6 2区 化学 Q1 CHEMISTRY, MEDICINAL
Christopher Brasnett, Siewert J Marrink
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引用次数: 0

Abstract

As molecular modeling gains ever more prominence in understanding cellular processes, high quality visualization of models and dynamics has never been more important. Naturally, much molecular visualization software is written to enable the visualization of atomic level details in structures. While necessary, this means that visualization of increasingly popular coarse-grained (CG) models remains a challenge. Here, we present a Python package, MartiniGlass, that facilitates the visualization of systems simulated with the widely used CG Martini force field using the popular visualization package VMD. MartiniGlass rapidly processes molecular topologies and accounts for important topological features at CG resolution, such as secondary structure restraints, preparing them for easy visualization of simulated trajectories.

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来源期刊
CiteScore
9.80
自引率
10.70%
发文量
529
审稿时长
1.4 months
期刊介绍: The Journal of Chemical Information and Modeling publishes papers reporting new methodology and/or important applications in the fields of chemical informatics and molecular modeling. Specific topics include the representation and computer-based searching of chemical databases, molecular modeling, computer-aided molecular design of new materials, catalysts, or ligands, development of new computational methods or efficient algorithms for chemical software, and biopharmaceutical chemistry including analyses of biological activity and other issues related to drug discovery. Astute chemists, computer scientists, and information specialists look to this monthly’s insightful research studies, programming innovations, and software reviews to keep current with advances in this integral, multidisciplinary field. As a subscriber you’ll stay abreast of database search systems, use of graph theory in chemical problems, substructure search systems, pattern recognition and clustering, analysis of chemical and physical data, molecular modeling, graphics and natural language interfaces, bibliometric and citation analysis, and synthesis design and reactions databases.
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