Department of Biochemistry, Biophysics, and Molecular Biology, Iowa State University, Ames, IA 50011-0320, USA.
BMC Bioinformatics. 2010 Feb 17;11:92. doi: 10.1186/1471-2105-11-92.
Knowledge-based potentials have been widely used in the last 20 years for fold recognition, protein structure prediction from amino acid sequence, ligand binding, protein design, and many other purposes. However generally these are not readily accessible online.
Our new knowledge-based potential server makes available many of these potentials for easy use to automatically compute the energies of protein structures or models supplied. Our web server for protein energy estimation uses four-body potentials, short-range potentials, and 23 different two-body potentials. Users can select potentials according to their needs and preferences. Files containing the coordinates of protein atoms in the PDB format can be uploaded as input. The results will be returned to the user's email address.
Our Potentials 'R' Us server is an easily accessible, freely available tool with a web interface that collects all existing and future protein coarse-grained potentials and computes energies of multiple structural models.
在过去的 20 年中，基于知识的势能已被广泛用于折叠识别、从氨基酸序列预测蛋白质结构、配体结合、蛋白质设计和许多其他目的。然而，这些势能通常不容易在线获得。
我们的新基于知识的势能服务器提供了许多这些势能，以便于轻松使用，自动计算提供的蛋白质结构或模型的能量。我们的蛋白质能量估计网络服务器使用四体势能、短程势能和 23 种不同的二体势能。用户可以根据需要和偏好选择势能。可以上传包含 PDB 格式蛋白质原子坐标的文件作为输入。结果将返回用户的电子邮件地址。
我们的 Potentials 'R' Us 服务器是一个易于访问、免费提供的工具，具有网络界面，可收集所有现有的和未来的蛋白质粗粒度势能，并计算多个结构模型的能量。
