arXiv subjects

Michal Kurzynski

Publications and source records attributed to Michal Kurzynski.

6 recordsLinked to original sources

arXiv2018

Biological molecular machines can process information to reduce energy losses

Biological molecular machines are enzymes that simultaneously catalyze two processes, one donating free energy and second accepting it. Recent studies show that most native protein enzymes have a rich stochastic dynamics that often manifests in fluctuating rates of the catalyzed processes and the presence of short-term memory resulting from transient non-ergodicity. For such dynamics, we prove the generalized fluctuation theorem predicting a possible reduction of energy dissipation at the expense of creating some information stored in memory. The theoretical relationships are verified in computer simulations of random walk on a model critical complex network. The transient utilization of memory may turn out to be crucial for the movement of protein motors and the reason for most protein machines to operate as dimers or higher organized assemblies. From a broader physical point of view, the division of free energy into the operation and organization energy is worth emphasizing. Information can be assigned a physical meaning of a change in the value of both these functions of state.

physics.bio-ph↗

arXiv2017

Information processing in biological molecular machines

Biological molecular machines are bifunctional enzymes that catalyze two processes: one donating free energy and the other accepting it. Recent studies show that most protein enzymes have rich stochastic dynamics of transitions between the multitude of conformation substates that make up their native state. This dynamics often manifests itself in fluctuating rates of the catalyzed processes and the presence of short-term memory. For such stochastic dynamics, after dividing the free energy into operational and organizational energy, we proved the generalized fluctuation theorem, which leads to the extension of the second law of thermodynamics to include two competing functions of process: dissipation and information. Computer simulation of the course of catalyzed processes taking place on the model network of substates, expressed in jumps of unit values at random moments of time, indicates the possibility of negative dissipation of the organizational free energy at the expense of information temporarily stored in memory, i.e. the behavior like Maxwell's demon. Because similar courses can be registered in observation of real systems, all theses of the paper are open to experimental verification.

physics.bio-ph↗

arXiv2015

Steady-state distributions of probability fluxes on complex networks

The methodology based on the random walk processes is adapted and applied to a comprehensive analysis of the statistical properties of the probability fluxes. To this aim we define a simple model of the Markovian stochastic dynamics on a complex network extended by the additional transition, called hereafter the gate. The random skips through the gate, driven by the external constant force, violate the detailed balance in the network. We argue, using a theoretical approach and numerical simulations, that the stationary distributions of the probability fluxes emergent under such conditions converge, regardless of the network topology, to the normal distribution. This result, combined with the stationary fluctuation theorem, permits to show that its standard deviation depends directly on the square root of the average flux. In turn, the central result of our paper relates this quantity to the external constant force and the two parameters that entirely characterize the normal distribution of the probability fluxes both close to as well as far from the equilibrium state. Also, the other effects that modify these parameters, such as the addition of shortcuts to the tree-like network, the extension and configuration of the gate and a change in the network size studied by means of the computer simulations are widely discussed in terms of the rigorous theoretical predictions.

cond-mat.stat-mech↗

arXiv2014

Do biological molecular machines act as Maxwell's demons?

The nanoscopic isothermal machines are not only energy but also information transducers. We show that the generalized fluctuation theorem with information creation and entropy reduction can be fulfilled for the enzymatic molecular machines with the stochastic dynamics, which offers a choice of the work performance in a variety of ways. A model of such dynamics, specified by a critical complex network, is investigated. The main conclusion of the study is that the processing of free energy has to be distinguished from the processing of organization, which we identify with an adequately defined thermodynamic variable. Maxwell's demon utilizes entropy reduction for creation of information, which, from the former point of view, may be used for a reduction of energy losses, hence ultimately, for the performance of work. From the latter point of view, however, it can be used for other purposes, for example molecular recognition. This can be the case of biological molecular machines. From the biological perspective, the ascertainment is important, that the information creation and storage take place in the long lasting transient stages before completing the free energy transduction cycles. From a broader physical perspective, a supposition could be of special importance, that information is a change of organization, the thermodynamic function of state of the system.

physics.bio-ph↗

arXiv2011

Output-input coupling in thermally fluctuating biomolecular machines

Biological molecular machines are proteins that operate under isothermal conditions hence are referred to as free energy transducers. They can be formally considered as enzymes that simultaneously catalyze two chemical reactions: the free energy-donating reaction and the free energy-accepting one. Most if not all biologically active proteins display a slow stochastic dynamics of transitions between a variety of conformational substates composing their native state. In the steady state, this dynamics is characterized by mean first-passage times between transition substates of the catalyzed reactions. On taking advantage of the assumption that each reaction proceeds through a single pair (the gate) of conformational transition substates of the enzyme-substrates complex, analytical formulas were derived for the flux-force dependence of the both reactions, the respective stalling forces and the degree of coupling between the free energy-accepting (output) reaction flux and the free energy-donating (input) one. The theory is confronted with the results of random walk simulations on the 5-dimensional hypercube. The formal proof is given that in the case of reactions proceeding through single gates, the degree of coupling cannot exceed unity. As some experiments suggest such exceeding, looking for conditions of increasing the degree of coupling over unity challenges theory. Though no analytical formulas for models involving more transition substates are available, study simulations of random walks on several model networks indicate that the case of the degree of coupling value higher than one occurs in a natural way for scale-free tree-like networks. This supports a hypothesis that the protein conformational transition networks, like higher level biological networks: the proteome and the metabolome, have evolved in a process of self-organized criticality.

physics.bio-ph↗

arXiv1994

Protein-Machine model of a single enzymatic reaction

The theory of biochemical processes needs simple but realistic models of phenomena underlying microscopic dynamics of proteins. Many experiments performed in the 1980s have demonstrated that within the protein native state, apart from usual vibrational dynamics, a rich interconformational (activated) dynamics exists. The slowness of this dynamics makes any conventional theory of chemical reactions inapplicable for description of enzymatic reactions. It is presumably a rule that it is the process of conformational relaxation, and not the details of chemical mechanism, that affects their rate. In a simple model of Protein-Machine type, applied in constructing a novel theory of enzymatic reaction, conformational dynamics is treated as a realative quasi-continuous motion of solid-like structural elements of protein. Simple and tractable formulas for the chemical relaxation time and the enzyme turnover number in the steady state conditions are found. The important result obtained is that the kinetic mechanisms close to and far from the equilibrium can differ.

cond-mat↗