Abstract
Diaryl ureas (DU) are a cornerstone scaffold in organic and medicinal chemistry, celebrated for their unique structural attributes and broad range of biomedical applications. Their therapeutic reach has broadened beyond kinase inhibition in cancer therapy to encompass diverse mechanisms, including modulation of chromatin remodeling complexes, interference with developmental signaling pathways, and inhibition of stress-activated protein kinases in inflammatory disorders. A critical element in the rational design and optimization of DU-based therapeutics is a detailed understanding of their molecular recognition by target proteins. In this study, we employed a multi-tiered computational approach to investigate the molecular determinants of DU-protein interactions. A large-scale data mining of the Protein Data Bank resulted in an in-house dataset of 158 non-redundant, high-resolution crystal structures of DU-protein complexes. This dataset serves as the basis for a systematic analysis of nonbonded interactions, including hydrogen bonding, salt bridges, π-π stacking, CH-π, cation-π, and XH-π interactions (X = OH, NH, SH). Advanced electronic structure calculations at the B2PLYP/def2-QZVP level are applied to quantify the energetic contributions of these interactions and their roles in molecular recognition of diaryl ureas in their target proteins. The study led to the following findings: central to the molecular recognition of diaryl ureas in proteins are nonbonded π interactions-predominantly CH-π and π-π stacking-that synergize with hydrogen bonding to achieve high binding affinity and specificity. Aromatic R groups in diaryl ureas play a pivotal role by broadening the interaction footprint within hydrophobic protein pockets, enabling energetically favorable and diverse binding modes. Comparative analyses highlight that diaryl ureas with aromatic R groups possess a more extensive and robust interaction profile than those with non-aromatic counterparts, emphasizing the critical importance of nonbonded π interactions in molecular recognition. These findings enhance our understanding of molecular recognition of diaryl ureas in proteins and provide valuable insights for the rational design of diaryl ureas as potent and selective inhibitors of protein kinases and other therapeutically significant proteins.