Computer-aided drug design platform using PyMOL
Computer-aided drug design platform using PyMOL
复制标题
DOI：
10.1007/s10822-010-9395-8
复制
发表时间：
2011-01-01
影响因子：
3.5
通讯作者：
Danielson, Matthew L.
中科院分区：
文献类型：
--
作者：
Lill, Markus A.;Danielson, Matthew L.
蛋白质-配体相互作用的理解和优化有助于药物化学家研究潜在的候选药物。在过去的几十年里，学术界已经开发了许多强大的计算机辅助药物发现工具，为蛋白质-配体相互作用提供了深入了解。由于程序是由不同的研究小组开发的，因此需要一个一致的用户友好的图形工作环境，该环境结合了诸如对接、评分、分子动力学模拟和自由能计算等计算技术。利用PyMOL，我们开发了这样一个图形用户界面，其中包含为蛋白质制备（AMBER包和Reduce）、分子力学应用（AMBER包）以及对接和评分（AutoDock维纳和SLIDE）设计的各个学术包。除了在一个界面下聚集多个计算工具外，计算平台还提供了不同程序的用户友好组合。例如，利用用AMBER进行的分子动力学（MD）模拟作为与AutoDock维纳的系综对接的输入。这项工作的总体目标是提供一个计算平台，方便药物化学家，许多谁不是计算方法的专家，利用几个常见的计算技术密切相关的药物发现。此外，我们的软件是开源的，旨在启动计算研究人员之间的合作努力，在一个单一的，易于理解的图形用户界面下联合收割机其他开源计算方法。
The understanding and optimization of protein-ligand interactions are instrumental to medicinal chemists investigating potential drug candidates. Over the past couple of decades, many powerful standalone tools for computer-aided drug discovery have been developed in academia providing insight into protein-ligand interactions. As programs are developed by various research groups, a consistent user-friendly graphical working environment combining computational techniques such as docking, scoring, molecular dynamics simulations, and free energy calculations is needed. Utilizing PyMOL we have developed such a graphical user interface incorporating individual academic packages designed for protein preparation (AMBER package and Reduce), molecular mechanics applications (AMBER package), and docking and scoring (AutoDock Vina and SLIDE). In addition to amassing several computational tools under one interface, the computational platform also provides a user-friendly combination of different programs. For example, utilizing a molecular dynamics (MD) simulation performed with AMBER as input for ensemble docking with AutoDock Vina. The overarching goal of this work was to provide a computational platform that facilitates medicinal chemists, many who are not experts in computational methodologies, to utilize several common computational techniques germane to drug discovery. Furthermore, our software is open source and is aimed to initiate collaborative efforts among computational researchers to combine other open source computational methods under a single, easily understandable graphical user interface.