On Figure . is shown the Williams plot for the regression model, where the applicability domain is defined within ±3σ and a leverage threshold h* = 0.25. From the plot is apparent that all compounds of the training set are within the applicability domain except 3 with leverage values greater than the warning h*. These 3 chemicals could influence the performance of the model, however, like 108 their standard residuals are well within the established limits and thus, not model outliers to be considered for removal from the training set. There are also 2 structures from the external test set with h > h* marked (with †) on Table as warning predictions. There are also 3 external set compounds outside of the established limits of the standard residuals, which explains the lower R 2 of the independent external set. In our study we did not try to define upfront what structural alerts are statistically significant/important. Instead, we let the machine learning algorithms decide the importance of the molecular descriptors. In Table . are listed some of the most significant structural alerts. In fragment-based drug design, structural alerts serve as critical tools for identifying promising fragment scaffolds with potential to bind to a target protein. By recognizing specific molecular features associated with desired or undesired properties, these alerts enable early prediction of a fragment's suitability for progression into lead optimization. This knowledge helps focus drug discovery efforts on compounds with higher likelihood of success while minimizing the risk of developing molecules with liabilities such as toxicity or poor pharmacokinetics. As has been described briefly in the introduction, TBK1 is composed of four domains -kinase domain, ubiquitin-like domain, scaffold/dimerization domain and TANK-binding domain. The structure of TBK1 has been determined with several structures from across different methodologies (X-ray, cryo-EM) and species and are available in the Protein Data Bank (PDB). Many of the reported structures of TBK1 are in the presence of an inhibitor such as the withdrawn drug amlexanox (CAS RN: 68302-57-8) 102 and a highly selective small molecule inhibitor in development, BAY-985 (CAS RN: 2409479-29-2) 112 . Both inhibitors appear to be competitive in nature, binding around the same area as ATP would.