Drive-specific selection in multistable mechanical networks.

Systems with many stable configurations abound in nature, both in living and inanimate matter, encoding a rich variety of behaviors. In equilibrium, a multistable system is more likely to be found in configurations with lower energy, but the presence of an external drive can alter the relative stability of different configurations in unexpected ways. Living systems are examples par excellence of metastable nonequilibrium attractors whose structure and stability are highly dependent on the specific form and pattern of the energy flow sustaining them.

Self-organized computation in the far-from-equilibrium cell.

Recent progress in our understanding of the physics of self-organization in active matter has pointed to the possibility of spontaneous collective behaviors that effectively compute things about the patterns in the surrounding patterned environment. Here, we describe this progress and speculate about its implications for our understanding of the internal organization of the living cell.

Machine learning outperforms thermodynamics in measuring how well a many-body system learns a drive.

Diverse many-body systems, from soap bubbles to suspensions to polymers, learn and remember patterns in the drives that push them far from equilibrium. This learning may be leveraged for computation, memory, and engineering. Until now, many-body learning has been detected with thermodynamic properties, such as work absorption and strain.

Design of conditions for self-replication.

A "self-replicator" is usually understood to be an object of definite form that promotes the conversion of materials in its environment into a nearly identical copy of itself. The challenge of engineering novel, micro- or nanoscale self-replicators has attracted keen interest in recent years, both because exponential amplification is an attractive method for generating high yields of specific products and, also, because self-reproducing entities have the potential to be optimized or adapted through rounds of iterative selection. Substantial steps forward have been achieved both in the engineering of particular self-replicating molecules and in the characterization of the physical basis for possible mechanisms of self-replication.

Nonequilibrium associative retrieval of multiple stored self-assembly targets.

Many biological systems rely on the ability to self-assemble different target structures using the same set of components. Equilibrium self-assembly suffers from a limited capacity in such cases, due to an increasing number of decoy states that grows rapidly with the number of targets encoded. Moreover, improving the kinetic stability of a target at equilibrium carries the price of introducing kinetic traps, leading to slower assembly.

Active regeneration unites high- and low-temperature features in cooperative self-assembly.

Cytoskeletal filaments are capable of self-assembly in the absence of externally supplied chemical energy, but the rapid turnover rates essential for their biological function require a constant flux of adenosine triphosphate (ATP) or guanosine triphosphate (GTP) hydrolysis. The same is true for two-dimensional protein assemblies employed in the formation of vesicles from cellular membranes, which rely on ATP-hydrolyzing enzymes to rapidly disassemble upon completion of the process. Recent observations suggest that the nucleolus, p granules, and other three-dimensional membraneless organelles may also demand dissipation of chemical energy to maintain their fluidity.

Least-rattling feedback from strong time-scale separation.

In most interacting many-body systems associated with some "emergent phenomena," we can identify subgroups of degrees of freedom that relax on dramatically different time scales. Time-scale separation of this kind is particularly helpful in nonequilibrium systems where only the fast variables are subjected to external driving; in such a case, it may be shown through elimination of fast variables that the slow coordinates effectively experience a thermal bath of spatially varying temperature. In this paper, we investigate how such a temperature landscape arises according to how the slow variables affect the character of the driven quasisteady state reached by the fast variables.

Limits of predictions in thermodynamic systems: a review.

The past twenty years have seen a resurgence of interest in nonequilibrium thermodynamics, thanks to advances in the theory of stochastic processes and in their thermodynamic interpretation. Fluctuation theorems provide fundamental constraints on the dynamics of systems arbitrarily far from thermal equilibrium. Thermodynamic uncertainty relations bound the dissipative cost of precision in a wide variety of processes.

Self-Organized Resonance during Search of a Diverse Chemical Space.

Recent studies of active matter have stimulated interest in the driven self-assembly of complex structures. Phenomenological modeling of particular examples has yielded insight, but general thermodynamic principles unifying the rich diversity of behaviors observed have been elusive. Here, we study the stochastic search of a toy chemical space by a collection of reacting Brownian particles subject to periodic forcing.

Spontaneous fine-tuning to environment in many-species chemical reaction networks.

A chemical mixture that continually absorbs work from its environment may exhibit steady-state chemical concentrations that deviate from their equilibrium values. Such behavior is particularly interesting in a scenario where the environmental work sources are relatively difficult to access, so that only the proper orchestration of many distinct catalytic actors can power the dissipative flux required to maintain a stable, far-from-equilibrium steady state. In this article, we study the dynamics of an in silico chemical network with random connectivity in an environment that makes strong thermodynamic forcing available only to rare combinations of chemical concentrations.

Minimum energetic cost to maintain a target nonequilibrium state.

In the absence of external driving, a system exposed to thermal fluctuations will relax to equilibrium. However, the constant input of work makes it possible to counteract this relaxation and maintain the system in a nonequilibrium steady state. In this article, we use the stochastic thermodynamics of Markov jump processes to compute the minimum rate at which energy must be supplied and dissipated to maintain an arbitrary nonequilibrium distribution in a given energy landscape.

Measurement of Rapid Protein Diffusion in the Cytoplasm by Photo-Converted Intensity Profile Expansion.

The fluorescence microscopy methods presently used to characterize protein motion in cells infer protein motion from indirect observables, rather than measuring protein motion directly. Operationalizing these methods requires expertise that can constitute a barrier to their broad utilization. Here, we have developed PIPE (photo-converted intensity profile expansion) to directly measure the motion of tagged proteins and quantify it using an effective diffusion coefficient.

Dissipation Bounds All Steady-State Current Fluctuations.

Near equilibrium, small current fluctuations are described by a Gaussian distribution with a linear-response variance regulated by the dissipation. Here, we demonstrate that dissipation still plays a dominant role in structuring large fluctuations arbitrarily far from equilibrium. In particular, we prove a linear-response-like bound on the large deviation function for currents in Markov jump processes.

Far-from-equilibrium distribution from near-steady-state work fluctuations.

A long-standing goal of nonequilibrium statistical mechanics has been to extend the conceptual power of the Boltzmann distribution to driven systems. We report some new progress towards this goal. Instead of writing the nonequilibrium steady-state distribution in terms of perturbations around thermal equilibrium, we start from the linearized driven dynamics of observables about their stable fixed point, and expand in the strength of the nonlinearities encountered during typical fluctuations away from the fixed point.

Dissipative adaptation in driven self-assembly.

In a collection of assembling particles that is allowed to reach thermal equilibrium, the energy of a given microscopic arrangement and the probability of observing the system in that arrangement obey a simple exponential relationship known as the Boltzmann distribution. Once the same thermally fluctuating particles are driven away from equilibrium by forces that do work on the system over time, however, it becomes significantly more challenging to relate the likelihood of a given outcome to familiar thermodynamic quantities. Nonetheless, it has long been appreciated that developing a sound and general understanding of the thermodynamics of such non-equilibrium scenarios could ultimately enable us to control and imitate the marvellous successes that living things achieve in driven self-assembly.

Structural Basis for Modulation of Quality Control Fate in a Marginally Stable Protein.

The human von Hippel-Lindau (VHL) tumor suppressor is a marginally stable protein previously used as a model substrate of eukaryotic refolding and degradation pathways. When expressed in the absence of its cofactors, VHL cannot fold and is quickly degraded by the quality control machinery of the cell. We combined computational methods with in vivo experiments to examine the basis of the misfolding propensity of VHL.

Quantitative theory of hydrophobic effect as a driving force of protein structure.

Various studies suggest that the hydrophobic effect plays a major role in driving the folding of proteins. In the past, however, it has been challenging to translate this understanding into a predictive, quantitative theory of how the full pattern of sequence hydrophobicity in a protein shapes functionally important features of its tertiary structure. Here, we extend and apply such a phenomenological theory of the sequence-structure relationship in globular protein domains, which had previously been applied to the study of allosteric motion.

Statistical physics of self-replication.

Self-replication is a capacity common to every species of living thing, and simple physical intuition dictates that such a process must invariably be fueled by the production of entropy. Here, we undertake to make this intuition rigorous and quantitative by deriving a lower bound for the amount of heat that is produced during a process of self-replication in a system coupled to a thermal bath. We find that the minimum value for the physically allowed rate of heat production is determined by the growth rate, internal entropy, and durability of the replicator, and we discuss the implications of this finding for bacterial cell division, as well as for the pre-biotic emergence of self-replicating nucleic acids.

Confinement to organelle-associated inclusion structures mediates asymmetric inheritance of aggregated protein in budding yeast.

The division of the S. cerevisiae budding yeast, which produces one mother cell and one daughter cell, is asymmetric with respect to aging. Remarkably, the asymmetry of yeast aging coincides with asymmetric inheritance of damaged and aggregated proteins by the mother cell.

Allostery in protein domains reflects a balance of steric and hydrophobic effects.

Allosteric conformational change underlies biological function in many proteins. Allostery refers to a conformational event in which one region of a protein undergoes structural rearrangement in response to a stimulus applied to a different region of the same protein. Here, I show for a variety of proteins that a simple, phenomenological model of the dependence of protein conformation on hydrophobic burial energy allows one to compute low-energy conformational fluctuations for a given sequence by using linear programming to find optimized combinations of sequence-specific hydrophobic burial modes that satisfy steric constraints.

Role of solvation effects in protein denaturation: from thermodynamics to single molecules and back.

Protein stability often is studied in vitro through the use of urea and guanidinium chloride, chemical cosolvents that disrupt protein native structure. Much controversy still surrounds the underlying mechanism by which these molecules denature proteins. Here we review current thinking on various aspects of chemical denaturation.

Polyglutamine shows a urea-like affinity for unfolded cytosolic protein.

Noting that the glutamine (Q) amino acid side-chain bears a striking resemblance to urea, the chemical denaturant, we argue on biophysical grounds that polyQ chains should possess a potent denaturant activity. Using live-cell confocal microscopy, we demonstrate that the surface of a polyQ inclusion denatures cytosolic proteins by binding and trapping them in an immobilized ring. We also show the reverse effect: that elevated local concentrations of unfolded protein in the cytosol can drive the co-localization and accumulation of short polyQ tracts that normally do not aggregate.

Charge, hydrophobicity, and confined water: putting past simulations into a simple theoretical framework.

Water permeates all life, and mediates forces that are essential to the process of macromolecular self-assembly. Predicting these forces in a given biological context is challenging, since water organizes itself differently next to charged and hydrophobic surfaces, both of which are typically at play on the nanoscale in vivo. In this work, we present a simple statistical mechanical model for the forces water mediates between different confining surfaces, and demonstrate that the model qualitatively unifies a wide range of phenomena known in the simulation literature, including several cases of protein folding under confinement.