NON-EQUILIBRIUM TEMPORAL ENCODING IN RECEPTOR SIGNALING – AN INFORMATION THEORETICAL APPROACH TO UNCOVER SIGNAL TRANSDUCTION AT THE MOLECULAR SCALE

Biological sensory receptors present on the surface of cells mediate the interaction between cells and their environment. These receptors exhibit unmatched efficiency in information transduction despite experiencing thermal noise. Much literature focusing on information transduction treats receptor sensing performance as a steady-state problem. However, biological systems are constantly in motion and frequently driven far from equilibrium. This dissertation delves into the transient, far from equilibrium behavior of biological receptors to develop quantitative methods that capture information sensing at the molecular scale and uncover design principles of ligand receptors under far from equilibrium conditions. Using comprehensive theories, stochastic modeling, numerical and stochastic simulations, this dissertation uncovers the following phenomena along with development of mathematical methods to quantify and predict the effects: (1) multiplexing, which is the simultaneous transduction of multiple types of environmental information to the downstream sensory network, (2) a general equality that captures distinguishability of temporal trajectories in space and time for any Markov processes in non-equilibrium without encountering traditional sampling difficulties and (3) sensory withdrawal effect where certain sensors may show a boost in sensitivity toward a signal if a pre-exposure of the signal is followed by a transient low-signal resetting which suggest memory effects in these systems. This dissertation provides theoretical frameworks that can explain physiological observations including disease causing alterations in biological systems and can inspire design of biological sensors, optimizing signal transduction, and performing sensor adaptation analysis in pharmacology models to enhance efficacious therapy development. In the future, these methodologies may allow researchers to gain deeper insight into novel therapeutic strategies that target the temporal dynamics of receptors, rather than solely focusing on their stationary structural statistics.