دورية أكاديمية
MD–Ligand–Receptor: A High-Performance Computing Tool for Characterizing Ligand–Receptor Binding Interactions in Molecular Dynamics Trajectories
| العنوان: | MD–Ligand–Receptor: A High-Performance Computing Tool for Characterizing Ligand–Receptor Binding Interactions in Molecular Dynamics Trajectories |
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| المؤلفون: | Michele Pieroni, Francesco Madeddu, Jessica Di Martino, Manuel Arcieri, Valerio Parisi, Paolo Bottoni, Tiziana Castrignanò |
| المصدر: | International Journal of Molecular Sciences, Vol 24, Iss 14, p 11671 (2023) |
| بيانات النشر: | MDPI AG, 2023. |
| سنة النشر: | 2023 |
| المجموعة: | LCC:Biology (General) LCC:Chemistry |
| مصطلحات موضوعية: | molecular dynamics, protein–ligand interactions, nucleic acid–ligand interactions, computational modeling of molecular systems, Biology (General), QH301-705.5, Chemistry, QD1-999 |
| الوصف: | Molecular dynamics simulation is a widely employed computational technique for studying the dynamic behavior of molecular systems over time. By simulating macromolecular biological systems consisting of a drug, a receptor and a solvated environment with thousands of water molecules, MD allows for realistic ligand–receptor binding interactions (lrbi) to be studied. In this study, we present MD–ligand–receptor (MDLR), a state-of-the-art software designed to explore the intricate interactions between ligands and receptors over time using molecular dynamics trajectories. Unlike traditional static analysis tools, MDLR goes beyond simply taking a snapshot of ligand–receptor binding interactions (lrbi), uncovering long-lasting molecular interactions and predicting the time-dependent inhibitory activity of specific drugs. With MDLR, researchers can gain insights into the dynamic behavior of complex ligand–receptor systems. Our pipeline is optimized for high-performance computing, capable of efficiently processing vast molecular dynamics trajectories on multicore Linux servers or even multinode HPC clusters. In the latter case, MDLR allows the user to analyze large trajectories in a very short time. To facilitate the exploration and visualization of lrbi, we provide an intuitive Python notebook (Jupyter), which allows users to examine and interpret the results through various graphical representations. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1422-0067 1661-6596 |
| Relation: | https://www.mdpi.com/1422-0067/24/14/11671; https://doaj.org/toc/1661-6596; https://doaj.org/toc/1422-0067 |
| DOI: | 10.3390/ijms241411671 |
| URL الوصول: | https://doaj.org/article/f47b37e797294a259f3df560f6141b5d |
| رقم الأكسشن: | edsdoj.f47b37e797294a259f3df560f6141b5d |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 14220067 16616596 |
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| DOI: | 10.3390/ijms241411671 |