Fragment-based drug discovery or FBDD is one of the main methods used by industry and academia for identifying drug-like candidates in early stages of drug discovery. NMR has a significant impact at any stage of the drug discovery process, from primary identification of small molecules to the elucidation of binding modes for guiding optimisations. The essence of NMR as an analytical tool, however, requires the processing and analysis of relatively large amounts of single data items, e.g. spectra, which can be daunting when managed manually. One bottleneck in FBDD by NMR is a lack of adequate and well-integrated resources for NMR data analysis that are freely available to the community. Thus, scientists typically resort to manually inspecting large datasets and relying predominantly on subjective interpretations. In this manuscript, we present CcpNmr AnalysisScreen, a software package that provides computational tools for automated analysis of FBDD data by NMR. We outline how the quality of collected spectra can be evaluated quickly, and how robust workflows can be optimised for reliable and rapid hit identification. With an intuitive graphical user interface and powerful algorithms, AnalysisScreen enables easy analysis of the large datasets needed in the early process of drug discovery by NMR.

基于片段的药物发现（FBDD）是工业界和学术界在药物发现早期阶段识别类药候选物的主要方法之一。 NMR 在药物发现过程的任何阶段都具有重大影响，从小分子的初步鉴定到指导优化的结合模式的阐明。然而，核磁共振作为一种分析工具的本质是需要处理和分析相对大量的单一数据项，例如光谱，这在手动管理时可能是令人畏惧的。 NMR FBDD 的一个瓶颈是缺乏足够且集成良好的 NMR 数据分析资源，这些资源可供社区免费使用。因此，科学家通常求助于手动检查大型数据集并主要依靠主观解释。在这篇手稿中，我们介绍了 CcpNmr AnalysisScreen，这是一个软件包，它提供了通过 NMR 自动分析 FBDD 数据的计算工具。我们概述了如何快速评估所收集光谱的质量，以及如何优化稳健的工作流程以实现可靠和快速的命中识别。 AnalysisScreen 具有直观的图形用户界面和强大的算法，可以轻松分析 NMR 药物发现早期过程中所需的大型数据集。