Assuming the target of interest has already been identified, hit identification is usually the first step in the drug discovery process and this is the aspect we concentrate on in this article.

A meticulous examination of recent FDA-approved drugs and drugs in clinical stage studies, indicates a substantial contribution of various NMR-based techniques to the whole drug discovery process (Petros et al. Nowadays, it is possible, albeit not frequently done, to conduct the entire drug discovery process by NMR: from hit detection and binding site identification to the determination of the ligand orientation and hit optimisation. Over the years, the versatility of NMR as a non-destructive and adaptable analytical tool has encouraged the development of multiple fragment-based drug discovery (FBDD) approaches by NMR (Dias and Ciulli ( 2014). 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. 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. In this manuscript, we present CcpNmr AnalysisScreen, a software package that provides computational tools for automated analysis of FBDD data by NMR. Thus, scientists typically resort to manually inspecting large datasets and relying predominantly on subjective interpretations. 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. spectra, which can be daunting when managed manually. The essence of NMR as an analytical tool, however, requires the processing and analysis of relatively large amounts of single data items, e.g. 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. 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.

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