Intrinsic Bond Strength Index as a halogen bond interaction energy predictor

Halogen bonds (XBs) have become increasingly popular over the past few years with numerous applications in catalysis, material design, anion recognition, and medicinal chemistry. To avoid a \textit{post factum} rationalization of XB trends, descriptors can be tentatively employed to predict the strength of potential halogen bonds. These typically comprise the electrostatic potential maximum at the tip of the halogen, ${V_{S, max}}$, or properties based on the topological analysis of the electronic density. However, such descriptors either can only be used with confidence for specific families of halogen bonds or require intense computations and, therefore, are not particularly attractive for large datasets with diverse compounds or biochemical systems. Therefore, the development of a simple, widely applicable, and computationally feasible descriptor remains a challenge as it would facilitate the discovery of new XB applications while also improving the existing ones. Recently, the Intrinsic Bond Strength Index (IBSI) has been proposed as a new tool to evaluate any bond strength, however, it has not been extensively explored in the context of halogen bonding. In this work, we show that IBSI values linearly correlate with the interaction energy of diverse sets of halogen-bonded complexes and therefore, can be used to quantitatively predict halogen bond strength. The linear fit models based on quantum-mechanics-based electron density provided MAEs typically below 1~kcal~mol$^{-1}$. Moreover, we also explored the exciting possibility to use a promolecular density approach (\pro{}), which only requires the complex geometry as an input which is computationally cheap. Surprisingly, the performance was comparable to the QM-based methods, thus opening the door for the usage of \pro{} as a fast, yet accurate, XB strength descriptor in large datasets but also in biomolecular systems such as protein–ligand complexes.