Probing coexistence of robust threshold and ultrasensitivity in molecular switches and cascades

Molecular switches are fundamental building blocks in many biophysical processes. These switches arise from dissimilar molecular interactions, affected by intrinsic and extrinsic noise, but exhibit a common ON-OFF behavior that suffices for signal transduction, amplification, and relay. Such repertoires of different mechanisms pose a fundamental question: which mechanisms in a noisy environment confer ultrasensitivity as a switch while also ensuring robust decoding of the concentration threshold required for information interpretation? In this paper, we design molecular switches based on molecular-exchange mechanisms (MEM) and dimeric ligand formation, comprising reversible interactions, and compare them stochastically with other switch-forming mechanisms. Our results reveal that the MEM and Dimer mechanisms exhibit improved robustness of the threshold against noise and appear less uncertain if assessed information-theoretically. This superiority is reflected in their switch-like behavior, making them less prone to flipping states in noisy environments. Extending beyond single-switch comparisons, we also explore alternative switch cascades and assess their performance against noise. Alongside this, the continuing expansion of this work is transformed to a Physics-Informed Neural Network (PINN) form that can predict switching behavior for variation in input signal. More importantly, the PINN-switch can ensure that any agentic-AI driven design adheres to the biological and physical constraints indispensable in a molecular switch. Insights from this study may be helpful in drug design and synthetic circuits aimed at therapeutics and other aqueous applications.