Abstract
Microtubules as essential biopolymers implicated into electrical intracellular transport open a lot of questions about their intrinsic character of dynamic instability. Both experimental and theoretical investigations are used to understand their behavior in order to mimic and build powerful and smart biomaterials. So, in this paper, by analytical and computational approaches, we proposed an electrical analogue computer of microtubule’s protofilament drawing from the partial differential equation which describes microtubule’s motion. Using the computing elements, namely, operational amplifiers, capacitors, and resistors, we designed analytically the bioelectronic circuit of the microtubule’s protofilament. To validate our model, Runge–Kutta code was used to solve the partial differential equation of MT’s motion on software Matlab, and then, the results obtained are used as a controller to fit and validate numerical results obtained by running the bioelectronic circuit on software PSpice. It is shown that the analogue circuit displayed spontaneous electrical activity consistent with self-sustained electrical oscillations. We found out that two behaviors were exhibited by the voltage generated from the electrical analogue computer of MT’s protofilament; amplification and damping behaviors are modulated by the values of the resistor of the summing operational amplifier. From our study, it is shown that low values of the resistor promote damping behavior while high values of the resistor promote an amplification behavior. So microtubule’s protofilament exhibits different spontaneous regimes leading to different oscillatory modes. This study put forward the possibility to build microtubule’s protofilament as a biotransistor.
Highlights
At the nanoscale, biological systems displayed electrical activity that cares biological communication via electrical signals [1]
In the theoretical viewpoint, researchers were inspired by a general RLC-cell circuit by considering the values of elements usually estimated experimentally. is consideration is powerful but not sufficient to generate a realistic and unique circuit characterizing the natural MTs. us, in this work, we propose an electrical analogue computer of microtubule by drawing from the partial differential equation describing the dynamics of the system
What we will do is to compare numerical results obtained from the partial differential equation using Runge–Kutta code to numerical results obtained from the analogue computer simulated on PSpice. e paper is organized as follows: Section 2 gives an overview about computing elements; in Section 3, the analogue computer of MT’s protofilament is presented, Section 4 investigates numerical results on Matlab and PSpice, and Section 5 concludes the study
Summary
Biological systems displayed electrical activity that cares biological communication via electrical signals [1]. Gutierrez et al reported that isolated brain MTs are electrical oscillators that behave as “ionic-based” transistors and amplify electrical signals which may have important implications in neuronal computational capabilities [21]. In the theoretical viewpoint, researchers were inspired by a general RLC-cell circuit by considering the values of elements usually estimated experimentally. Is consideration is powerful but not sufficient to generate a realistic and unique circuit characterizing the natural MTs. us, in this work, we propose an electrical analogue computer of microtubule by drawing from the partial differential equation describing the dynamics of the system. Composed by electrical computing elements such as resistors, capacitors, and operational amplifiers, an electrical analogue computer is an active network capable of simulating any set of linear and nonlinear partial differential equations. What we will do is to compare numerical results obtained from the partial differential equation using Runge–Kutta code to numerical results obtained from the analogue computer simulated on PSpice. e paper is organized as follows: Section 2 gives an overview about computing elements; in Section 3, the analogue computer of MT’s protofilament is presented, Section 4 investigates numerical results on Matlab and PSpice, and Section 5 concludes the study
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