AI-Driven Design and Clinical Translation of Nucleotide-Peptide and Peptide-Drug Conjugates

While nucleotide-peptide conjugates and peptide-drug conjugates demonstrate a considerable evolution as next-generation therapeutics, the successful translation of these complex agents relies on advances in bioconjugation strategies. By anchoring nucleotides or pharmaceutical payloads to multifaceted peptide scaffolds, researchers have engineered molecular platforms with dual mechanisms of action. However, to fully realize the potential of these hybrid systems, further refinements are required to ensure both in vivo stability and retention of the desired biological activities over time. This comprehensive review examines ongoing progress toward optimizing conjugation chemistry for the development of stable and efficacious NPC and PDC candidates. Through evaluation of fundamental design principles and their clinical relevance, it aims to accelerate the journey of these multilayered biomolecular constructs from theory to practice. It details various strategies to mitigate challenges such as enzymatic degradation and rapid systemic clearance, including covalent linkages (e.g., aminoacylation and thiol oxidation) and noncovalent interactions (e.g., ligand-receptor binding). Central to this emerging field is the integration of artificial intelligence and deep learning, which are rapidly transforming the design and development of NPCs and PDCs. AI-driven tools enable predictive modeling of peptide-drug interactions, intelligent linker optimization, and in silico screening of bioactive scaffolds-thus redefining the pipeline for precision therapeutics with improved selectivity and translatability. The potential of hybrid nanostructures formed by peptide-DNA conjugates for advanced drug delivery and diagnostic applications is also discussed. Furthermore, the clinical translation of PDCs demonstrates their promise in treating conditions such as cancer, neurodegenerative diseases, and inflammatory disorders, alongside the ongoing challenges regarding peptide availability, linker optimization, and scalable synthesis. The review concludes by discussing future directions of NPCs and PDCs, highlighting the role of interdisciplinary approaches in advancing precision medicine and addressing complex therapeutic needs.