5-Fluorouracil (5-FU) stands as one of the most widely prescribed chemotherapeutics. Despite over 60 years of study, a systematic synopsis of how 5-FU binds to proteins has been lacking. Investigating the specific binding patterns of 5-FU to proteins is essential for identifying additional interacting proteins and comprehending their medical implications. In this review, an analysis of the 5-FU binding environment was conducted based on available complex structures. From the earliest complex structure in 2001 to the present, two groups of residues emerged upon 5-FU binding, classified as P- and R-type residues. These high-frequency interactive residues with 5-FU include positively charged residues Arg and Lys (P type) and ring residues Phe, Tyr, Trp, and His (R type). Due to their high occurrence, 5-FU binding modes were simplistically classified into three types, based on interactive residues (within <4 Å) with 5-FU: Type 1 (P-R type), Type 2 (P type), and Type 3 (R type). In summary, among 14 selected complex structures, 8 conform to Type 1, 2 conform to Type 2, and 4 conform to Type 3. Residues with high interaction frequencies involving the N1, N3, O4, and F5 atoms of 5-FU were also examined. Collectively, these interaction analyses offer a structural perspective on the specific binding patterns of 5-FU within protein pockets and contribute to the construction of a structural interactome delineating the associations of the anticancer drug 5-FU.

MicroRNAs (miRNAs) that are mutually modulated by their interacting partners (interactome) are being increasingly noted for their significant role in pathogenesis and treatment of various human cancers. Recently, miRNA interactome dissected with multiomics approaches has been the subject of focus since individual tools or methods failed to provide the necessary comprehensive clues on the complete interactome. Even though single-omics technologies such as proteomics can uncover part of the interactome, the biological and clinical understanding still remain incomplete. In this study, we present an expert review of studies involving multiomics approaches to identification of miRNA interactome and its application in mechanistic characterization, classification, and therapeutic target identification in a variety of cancers, and with a focus on proteomics. We also discuss individual or multiple miRNA-based interactome identification in various pathological conditions of relevance to clinical medicine. Various new single-omics methods that can be integrated into multiomics cancer research and the computational approaches to analyze and predict miRNA interactome are also highlighted in this review. In all, we contextulize the power of multiomics approaches and the importance of the miRNA interactome to achieve the vision and practice of predictive, preventive, and personalized medicine in cancer research and clinical oncology.