| 1. |
- Abraham, Mark James, et al.
(författare)
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Sharing Data from Molecular Simulations
- 2019
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Ingår i: Journal of Chemical Information and Modeling. - : AMER CHEMICAL SOC. - 1549-9596 .- 1549-960X. ; 59:10, s. 4093-4099
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Tidskriftsartikel (refereegranskat)abstract
- Given the need for modern researchers to produce open, reproducible scientific output, the lack of standards and best practices for sharing data and workflows used to produce and analyze molecular dynamics (MD) simulations has become an important issue in the field. There are now multiple well-established packages to perform molecular dynamics simulations, often highly tuned for exploiting specific classes of hardware, each with strong communities surrounding them, but with very limited interoperability/transferability options. Thus, the choice of the software package often dictates the workflow for both simulation production and analysis. The level of detail in documenting the workflows and analysis code varies greatly in published work, hindering reproducibility of the reported results and the ability for other researchers to build on these studies. An increasing number of researchers are motivated to make their data available, but many challenges remain in order to effectively share and reuse simulation data. To discuss these and other issues related to best practices in the field in general, we organized a workshop in November 2018 (https://bioexcel.eu/events/workshop-on-sharing-data-from-molecular-simulations/). Here, we present a brief overview of this workshop and topics discussed. We hope this effort will spark further conversation in the MD community to pave the way toward more open, interoperable, and reproducible outputs coming from research studies using MD simulations.
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| 2. |
- Rodriguez-Espigares, Ismael, et al.
(författare)
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GPCRmd uncovers the dynamics of the 3D-GPCRome
- 2020
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Ingår i: Nature Methods. - : Springer Nature. - 1548-7091 .- 1548-7105. ; 17:8, s. 777-787
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Tidskriftsartikel (refereegranskat)abstract
- G-protein-coupled receptors (GPCRs) are involved in numerous physiological processes and are the most frequent targets of approved drugs. The explosion in the number of new three-dimensional (3D) molecular structures of GPCRs (3D-GPCRome) over the last decade has greatly advanced the mechanistic understanding and drug design opportunities for this protein family. Molecular dynamics (MD) simulations have become a widely established technique for exploring the conformational landscape of proteins at an atomic level. However, the analysis and visualization of MD simulations require efficient storage resources and specialized software. Here we present GPCRmd (http://gpcrmd.org/), an online platform that incorporates web-based visualization capabilities as well as a comprehensive and user-friendly analysis toolbox that allows scientists from different disciplines to visualize, analyze and share GPCR MD data. GPCRmd originates from a community-driven effort to create an open, interactive and standardized database of GPCR MD simulations.
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| 3. |
- Sommer, Martha E., et al.
(författare)
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The European Research Network on Signal Transduction (ERNEST) : Toward a Multidimensional Holistic Understanding of G Protein-Coupled Receptor Signaling
- 2020
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Ingår i: ACS Pharmacology & Translational Science. - : American Chemical Society (ACS). - 2575-9108. ; 3:2, s. 361-370
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Tidskriftsartikel (refereegranskat)abstract
- G protein-coupled receptors (GPCRs) are intensively studied due to their therapeutic potential as drug targets. Members of this large family of transmembrane receptor proteins mediate signal transduction in diverse cell types and play key roles in human physiology and health. In 2013 the research consortium GLISTEN (COST Action CM1207) was founded with the goal of harnessing the substantial growth in knowledge of GPCR structure and dynamics to push forward the development of molecular modulators of GPCR function. The success of GLISTEN, coupled with new findings and paradigm shifts in the field, led in 2019 to the creation of a related consortium called ERNEST (COST Action CA18133). ERNEST broadens focus to entire signaling cascades, based on emerging ideas of how complexity and specificity in signal transduction are not determined by receptor-ligand interactions alone. A holistic approach that unites the diverse data and perspectives of the research community into a single multidimensional map holds great promise for improved drug design and therapeutic targeting.
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