Kagami Luciano Porto, das Neves Gustavo Machado, Timmers Luís Fernando Saraiva Macedo, Caceres Rafael Andrade, Eifler-Lima Vera Lucia
Laboratory of Medicinal Organic Synthesis (LaSOM), Faculty of Pharmacy, Federal University of Rio Grande do Sul, Ipiranga Avenue, n° 2752, Porto Alegre, RS, 90610-000, Brazil; Programa de Pós-gradução de Ciências da Saúde da Universidade Federal de Ciências da Saúde de Porto Alegre (UFCSPA), Rua Sarmento Leite, n° 245, Porto Alegre, Rio Grande do Sul, 90050-170, Brazil.
Laboratory of Medicinal Organic Synthesis (LaSOM), Faculty of Pharmacy, Federal University of Rio Grande do Sul, Ipiranga Avenue, n° 2752, Porto Alegre, RS, 90610-000, Brazil; Programa de Pós-gradução de Ciências da Saúde da Universidade Federal de Ciências da Saúde de Porto Alegre (UFCSPA), Rua Sarmento Leite, n° 245, Porto Alegre, Rio Grande do Sul, 90050-170, Brazil.
Comput Biol Chem. 2020 Jun 24;87:107322. doi: 10.1016/j.compbiolchem.2020.107322.
Although molecular dynamics encompasses several applications, studies focusing on biomolecular systems are central issues of this research area. Such simulations require the generation of trajectory files, which provide a path for the analysis and interpretation of results with biological significance. However, although several programs have been developed in Python language for the analyses of molecular dynamics (MD) trajectories, they usually require some knowledge of programming languages in order to write or run the scripts using command lines, which certainly hinders the access of MD simulations to many scientists with the necessary biological background to interpret their results. To ease the access to Python packages focusing on MD trajectory analyses, we built a user-friendly and easy-to-install graphical PyMOL interface. Geo-Measures integrates the PyMOL functionalities with MDTraj, a powerful library of trajectory analyses, allowing the users to access up to 14 different types of analyses. Two sample cases are reported here to demonstrate the use of Geo-Measures. In the first example, which involves the use a MD trajectory file of hemoglobin from the MoDEL MD bank, we exemplified the analyses of the following variables: root mean square deviation, radius of gyration, free energy landscape and principal component analysis. In the second case, we built a trajectory file for the ecto-5'-nucleotidase using the LiGRO program to study the carbon alpha pincer angles, to define the secondary structure of the proteins and to analyze the Modevectors. This user-friendly graphical PyMOL plugin, which can be used to generate several descriptive analyses for protein structures, is open source and can be downloaded at: https://pymolwiki.org/index.php/Geo_Measures_Plugin.
尽管分子动力学包含多种应用,但专注于生物分子系统的研究是该研究领域的核心问题。此类模拟需要生成轨迹文件,这些文件为分析和解释具有生物学意义的结果提供了途径。然而,尽管已经用Python语言开发了几个程序用于分析分子动力学(MD)轨迹,但它们通常需要一些编程语言知识才能使用命令行编写或运行脚本,这无疑阻碍了许多具有必要生物学背景以解释结果的科学家进行MD模拟。为了便于访问专注于MD轨迹分析的Python包,我们构建了一个用户友好且易于安装的图形化PyMOL界面。Geo-Measures将PyMOL功能与MDTraj(一个强大的轨迹分析库)集成在一起,允许用户进行多达14种不同类型的分析。这里报告了两个示例案例以展示Geo-Measures的使用。在第一个示例中,涉及使用来自MoDEL MD库的血红蛋白的MD轨迹文件,我们举例说明了对以下变量的分析:均方根偏差、回转半径、自由能景观和主成分分析。在第二个案例中,我们使用LiGRO程序为胞外5'-核苷酸酶构建了一个轨迹文件,以研究碳α钳角、定义蛋白质的二级结构并分析模式向量。这个用户友好的图形化PyMOL插件可用于生成蛋白质结构的多种描述性分析,它是开源的,可在以下网址下载:https://pymolwiki.org/index.php/Geo_Measures_Plugin。