西班牙Pompeu Fabra大学Jana Selent小组建立了三维G-蛋白耦合受体（GPCRs）分子动力学模拟数据的在线共享平台。 相关论文于2020年7月13日发表于《自然—方法学》。

这里研究人员建立了名为GPCRmd （http://gpcrmd.org/）的一个在线平台，整合了网络可视化功能以及全面、用户友好的分析工具箱。它允许来自不同学科的科学家可视化分析和共享GPCR分子动力学（MD）模拟数据。GPCRmd来源于领域内推动的创建一个开放的、交互式和标准化的GPCR分子模拟数据库的需求。GPCRmd是一个领域驱动的在线平台，用于可视化、分析和共享G-蛋白耦合受体（GPCR）分子动力学数据。该平台目前包含100%的GPCR类型，71%的受体亚型和80%的GPCR家族。

据了解，G-蛋白耦合受体(GPCRs)参与大量生理过程，是获批准药品最常见的靶点。在过去的十年里，GPCR的新的三维分子结构(3D-GPCRome)爆炸式增长，大大提高了针对这一蛋白家族的机理理解和药物设计机会。分子动力学（MD）模拟已经成为探索蛋白质原子水平构象广泛使用的技术。然而，分析和可视化分子动力学模拟数据需要有效的存储资源和专业软件。

附：英文原文

Title: GPCRmd uncovers the dynamics of the 3D-GPCRome

Author: Ismael Rodrguez-Espigares, Mariona Torrens-Fontanals, Johanna K. S. Tiemann, David Aranda-Garca, Juan Manuel Ramrez-Anguita, Tomasz Maciej Stepniewski, Nathalie Worp, Alejandro Varela-Rial, Adrin Morales-Pastor, Brian Medel-Lacruz, Gspr Pndy-Szekeres, Eduardo Mayol, Toni Giorgino, Jens Carlsson, Xavier Deupi, Slawomir Filipek, Marta Filizola, Jos Carlos Gmez-Tamayo, Angel Gonzalez, Hugo Gutirrez-de-Tern, Mireia Jimnez-Ross, Willem Jespers, Jon Kapla, George Khelashvili, Peter Kolb, Dorota Latek, Maria Marti-Solano, Pierre Matricon, Minos-Timotheos Matsoukas, Przemyslaw Miszta, Mireia Olivella, Laura Perez-Benito, Davide Provasi, Santiago Ros, Ivn R. Torrecillas, Jessica Sallander, Agnieszka Sztyler, Silvana Vasile, Harel Weinstein, Ulrich Zachariae, Peter W. Hildebrand, Gianni De Fabritiis, Ferran Sanz, David E. Gloriam, Arnau Cordomi, Ramon Guix-Gonzlez, Jana Selent

Issue&Volume: 2020-07-13

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. GPCRmd is a community-driven online platform to visualize, analyze and share G-protein-coupled receptor (GPCR) molecular dynamics data. It currently contains simulation data representing 100% of GPCR classes, 71% of receptor subtypes and 80% of GPCR families.

DOI: 10.1038/s41592-020-0884-y

Source: https://www.nature.com/articles/s41592-020-0884-y