GPCR分子動力學模擬數據在線平臺
作者：
小柯機器人發布時間：2020/7/16 16:25:46
西班牙Pompeu Fabra大學Jana Selent小組建立了三維G-蛋白耦合受體（GPCRs）分子動力學模擬數據的在線共享平臺。 相關論文於2020年7月13日發表於《自然—方法學》。
這裡研究人員建立了名為GPCRmd （http://gpcrmd.org/）的一個在線平臺，整合了網絡可視化功能以及全面、用戶友好的分析工具箱。它允許來自不同學科的科學家可視化分析和共享GPCR分子動力學（MD）模擬數據。GPCRmd來源於領域內推動的創建一個開放的、交互式和標準化的GPCR分子模擬資料庫的需求。GPCRmd是一個領域驅動的在線平臺，用於可視化、分析和共享G-蛋白耦合受體（GPCR）分子動力學數據。該平臺目前包含100%的GPCR類型，71%的受體亞型和80%的GPCR家族。
據了解，G-蛋白耦合受體(GPCRs)參與大量生理過程，是獲批准藥品最常見的靶點。在過去的十年裡，GPCR的新的三維分子結構(3D-GPCRome)爆炸式增長，大大提高了針對這一蛋白家族的機理理解和藥物設計機會。分子動力學（MD）模擬已經成為探索蛋白質原子水平構象廣泛使用的技術。然而，分析和可視化分子動力學模擬數據需要有效的存儲資源和專業軟體。
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