Hyperdimensional Representation of Scaffold-Guided Fragment Library Diversification for Targeted Protein-Protein Interaction Inhibition

**Abstract:** This paper introduces a novel approach to 화합물 라이브러리 설계 centered around hyperdimensional representations of protein scaffolds and fragment libraries. Leveraging advanced hypervector embeddings and a novel iterative diversification algorithm, we present a methodology for rapidly generating highly targeted fragment libraries designed to disrupt specific protein-protein interactions (PPIs). This approach bypasses traditional virtual screening bottlenecks by focusing on scaffold-fragment combinations optimized for geometric complementarity and binding affinity, predicted through hyperdimensional similarity searches and refined with quantum mechanical calculations. The resulting library design radically accelerates the identification of PPI inhibitors, exhibiting potential for immediate commercialization in drug discovery.