AutoDock Suite: High Performance Software Environment for Drug Design

项目摘要 计算机对接是药物发现和设计的重要工具，它对于 开发目前临床上使用的许多药物。鉴于不断增长的试验性可获得性 具有原子分辨率的确定结构，它的应用已经成为最重要的之一 基于结构的方法。对接发挥的关键作用从以下出版物的数量中可见一斑 它(在过去4年中被引用超过11万条)，以及它在许多药物开发中的关键作用，目前在 临床应用。尽管现在被许多研究人员常规使用了几十年，但仍然有许多开放的 需要应对的挑战。其中一个主要的原因是评分准确率的提高。 功能，这将降低来自虚拟筛查的假阳性数量，并提高成功率 费率。另一种是需要更高效的计算性能，以便不仅能够虚拟筛选 最近开发的非常大的虚拟图书馆(现在甚至可以轻松地包含数十亿 化学品)，还有用低温电子显微镜表征的新的大分子络合物，如 以及同源建模和从头建模。这些限制的组合阻碍了 对接对这些问题的适用性。我们建议开发更好的工具来解决这些问题 挑战，以提高速度、准确性，并提供在大型库和 大分子结构。

Project Summary Computational docking is an essential tool for drug discovery and design, and it has been essential to the development of many drugs currently in clinical use. Given the growing availability of experimentally determined structures with atomic resolution, its application has become among the most important structure-based methods. The key role played by docking is underscored by the number of publications about it (more than 110k citations in the last 4 years), and its key role in the development of many drugs currently in clinical use. Despite being used now routinely by many researchers for decades, there are still many open challenges that need to be addressed. One of the main ones is the increase of accuracy of the scoring function, which would lower the number of false positives from virtual screenings, and increase the success rates. The other is the need for more efficient computing performance to be able to virtually screen not only the very large virtual libraries that have been developed recently (which can now easily contain even billions of chemicals), but also the new large macromolecular complexes that are being characterized with cryoEM, as well as homology modeling and de novo modeling. The combination of these limitations hinders the applicability of docking to these problems. We are proposing to develop better tools to address these challenges, to improve speed, accuracy, and provide the capability of navigating through large libraries and macromolecular structures.