Resource for Structure-based Computational Drug Discovery and Design (RSD3)

项目总结 自动对接是一种计算方法，现在通常用于识别 有可能成为新药。在过去的三十年里，我们开发了对接方法和 我们的对接软件AutoDock不是被引用最多的对接软件，在同行中被引用超过40,000次 回顾了相关文献。因此，它已成为社区的重要资源。我们寻求创造一种 国家资源，使我们能够维护和更新此软件，以适应不断发展的硬件 平台和操作系统，通过整合最新版本使软件保持最新和相关 算法开发，并支持其庞大的用户社区。在这些努力的同时，一个重要的 建议资源的目标是规划一条通往自给自足的软件生态系统的道路， 来自世界各地的贡献者将在之后为维护和进一步开发该软件做出贡献 这个奖项的终生获得者。这个目标已经被其他成功的开放源码项目实现了，比如Debian 和Python，以及许多同事的书面兴趣增强了我们的信心，AutoDock软件也 才能达到这个目标。为此，我们提出了三个具体目标。我们的首要目标是维护和实现现代化 软件代码。这项关键工作是软件保持功能并能够解决 不断变化的社区需求。当我们彻底检查软件时，我们将利用更新的工具包来生成 现代直观的图形用户界面。这些接口使研究人员，如临床 例如，计算技能有限的医生或化学家使用对接来更好地理解 药物的作用机理及其优化。我们的第二个目标是让我们的软件工具 可与其他重要的建模软件工具互操作，例如分子动力学。不仅 这是否增加了对接导致新的治疗分子的潜力，但它也服务于我们的目标 创建一个开发人员社区，他们最终将维护这个软件生态系统。最后是我们的第三个 最终的目标是支持庞大的用户社区，扩大它，并确保软件易于使用 发现、获取并安装。 我们在开发开放源码软件以推广软件最佳实践方面有着长期的记录 工程化，并使这些工具可用、有用，并可供社区使用。同样，我们也有 多年来一直支持和发展我们的用户社区。这使我们处于一个独特的位置来创建 建议的研究，如果得到资助，将允许我们将这些有价值的软件代码转换为社区 支持的软件生态系统确保此软件将继续支持新颖的设计 这个奖项有效期之外的治疗分子。

Project summary Automated docking is a computational method that is now routinely used for identifying small molecules that have the potential to be new drugs. Over the past three decades we have developed docking methods and our docking software AutoDock is not the most cited docking software with over 40,000 citations in the peer reviewed literature. As such, it has become an important resource for the community. We seek to create a national resource that will allow us to maintain and modernize this software to adapt to evolving hardware platforms and operating systems, to keep the software up to date and relevant by incorporating the latest algorithmic developments, and to support its large user community. In parallel with these efforts, an important goal of the proposed Resource is to chart a path toward a self-sustained software ecosystem where contributors from around the world will contribute to maintain and further develop this software after the lifetime of this award. This goal has been achieved by other successful open source projects such as Debian and Python, and the written interest of many colleagues bolster our confidence that the AutoDock software too can reach this goal. To this end we propose three specific aims. Our first aim is to maintain and modernize the software code. This critical work is needed for the software to remain functional and able to address the evolving needs of the community. As we overhaul the software, we will leverage newer toolkits for generating modern and intuitive graphical user interfaces. These interfaces enable researchers, such as clinical physicians or chemists with limited computational skills for instance, to use docking to better understand the mechanism of action of a drug and optimize it. Our second aim is concerned with making our software tools interoperable with other important modeling software tools such as molecular dynamics for instance. Not only does this augment the potential of docking to lead to novel therapeutic molecules, but it also serves our goal to create a community of developers who will ultimately maintain this software ecosystem. Finally our third and final aim is about supporting the large user community, growing it and ensuring that the software is easily discovered, obtained and installed. We have a long track record of developing open source software promoting best practices in software engineering, and making these tools usable, useful, and available to the community. Likewise we have supported and grown our user community for many years. This puts us in a unique position to create the proposed research which, if funded, will allow us to convert this valuable software code into a community supported software ecosystem ensuring that this software will continue to support the design of novel therapeutic molecules beyond the lifetime of this award.