The article discusses the role of dynamic conformational ensembles in biomolecular recognition, challenging the traditional "induced fit" hypothesis. Instead, it proposes the "conformational selection" model, which suggests that protein conformations preexist and the ligand selects the most favored conformation. After binding, the ensemble undergoes a population shift, redistributing the conformational states. Both mechanisms play roles in molecular recognition, with conformational selection likely optimizing side-chain and backbone interactions post-binding through induced fit. The article reviews experimental evidence supporting conformational selection in various interactions, including protein-ligand, protein-protein, protein-DNA, protein-RNA, and RNA-ligand interactions. It highlights the implications of this model for drug design, biomolecular engineering, and molecular evolution, emphasizing the importance of considering conformational heterogeneity and dynamic processes in these fields.The article discusses the role of dynamic conformational ensembles in biomolecular recognition, challenging the traditional "induced fit" hypothesis. Instead, it proposes the "conformational selection" model, which suggests that protein conformations preexist and the ligand selects the most favored conformation. After binding, the ensemble undergoes a population shift, redistributing the conformational states. Both mechanisms play roles in molecular recognition, with conformational selection likely optimizing side-chain and backbone interactions post-binding through induced fit. The article reviews experimental evidence supporting conformational selection in various interactions, including protein-ligand, protein-protein, protein-DNA, protein-RNA, and RNA-ligand interactions. It highlights the implications of this model for drug design, biomolecular engineering, and molecular evolution, emphasizing the importance of considering conformational heterogeneity and dynamic processes in these fields.