From Markovian to Non-Markovian: Advancing ion channel rate process theory

被引:0
作者
Ben-Abu, Yuval [1 ,2 ]
机构
[1] Sapir Acad Coll, Phys Unit, IL-79165 Sderot, Hof Ashkelon, Israel
[2] Univ Oxford, Dept Phys, Clarendon Lab, Oxford OX1 3PU, England
关键词
Continuity; Continuous state time (occupation time); Convolution; Distribution; Ergodicity; Full (complete) probability formula indicator; function; Hitting time; Ion channel; Laplace transform; Non-Markovian random process; Probability; Random process; Random variables; Recursion; Regeneration moment; Renewal equations and theorems; States; Switch probabilities; Tauberian theorems; Transfer (switch) probabilities; Transition from one state to another; Volterra linear integral equations;
D O I
10.1016/j.bpc.2025.107484
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Ion channels are essential membrane proteins that control ionic flow and cellular electrical activity. While traditional Markovian models have provided insights into channel gating, they fail to capture the memorydependent dynamics of real ion channel behavior. This manuscript presents a novel semi non-Markovian framework for understanding ion channel gating processes. Using continuous time and discrete state space models for two and three-state systems, we derive Volterra convolution-type integral equations governing channel dynamics. Through Laplace transform analysis, we reveal asymptotic behaviors and previously hidden asymmetries between opening and closing rates. Our approach successfully predicts asymmetrical gating kinetics, characterizes infinite-state processes, and elucidates dynamic state creation-capabilities beyond conventional Markovian models. This breakthrough moves from phenomenological descriptions toward understanding the fundamental physics of ion channel gating, with significant implications for drug discovery and therapeutic development targeting ion channel dysfunction. This work establishes a new paradigm in ion channel research, providing the mathematical framework needed to unlock the full complexity of these critical cellular processes.
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页数:5
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