arXiv subjects

Fabio Cecconi

Publications and source records attributed to Fabio Cecconi.

At least 19 recordsLinked to original sources

arXiv2025

Active Gaussian Network Model: a non-equilibrium description of protein fluctuations and allosteric behavior

Understanding the link between structure and function in proteins is fundamental in molecular biology and proteomics. A central question in this context is whether allostery - where the binding of a molecule at one site affects the activity of a distant site - emerges as a further manifestation of the intricate interplay between structure, function, and intrinsic dynamics. This study explores how allosteric regulation is modified when intrinsic protein dynamics operate under out-of-equilibrium conditions. To this purpose, we introduce a simple nonequilibrium model of protein dynamics, inspired by active matter systems, by generalizing the widely employed Gaussian Network Model (GNM) to incorporate non-thermal effects. Our approach underscores the advantage of framing allostery as a causal process by using, as a benchmark system, the second PDZ domain of the human phosphatase hPT1E that mediates protein-protein interactions. We employ causal indicators, such as response functions and transfer entropy, to identify the network of PDZ2 residues through which the allosteric signal propagates across the protein structure. These indicators reveal specific regions that align well with experimental observations. Furthermore, our results suggest that deviations from purely thermal fluctuations can significantly influence allosteric communication by introducing distinct timescales and memory effects. This influence is particularly relevant when the allosteric response unfolds on timescales incompatible with relaxation to equilibrium. Accordingly, non-thermal fluctuations may become essential for accurately describing protein responses to ligand binding and developing a comprehensive understanding of allosteric regulation.

cond-mat.stat-mech↗

arXiv2024

Conceptual and practical approaches for investigating irreversible processes

Current research in statistical mechanics mostly concerns the investigation of out-of-equilibrium, irreversible processes, which are ubiquitous in nature and still far from being theoretically understood. Even the precise characterization of irreversibility is the object of an open debate: while in the context of Hamiltonian systems the one-century-old proposal by M. Smoluchowski looks still valid (a process appears irreversible when the initial state has a recurrence time that is long compared to the time of observation [1]), in dissipative systems, particularly in the case of stochastic processes, the problem is more involved, and quantifying the "degree of irreversibility" is a pragmatic need. The most employed strategies rely on the estimation of entropy production: this quantity, although mathematically well-defined, is often difficult to compute, especially when analyzing experimental data. Moreover, being a global observable, entropy production fails to capture specific aspects of irreversibility in extended systems, such as the role of different currents and their spatial development. This review aims to address various conceptual and technical challenges encountered in the analysis of irreversibility, including the role of the coarse-graining procedure and the treatment of data in the absence of complete information. The discussion will be mostly based on simple models, analytically treatable, and supplemented by examples of complex, more realistic non-equilibrium systems.

cond-mat.stat-mech↗

arXiv2024

Response of Worm-like Chains to Traveling-Wave Active Forces

We present a simplified theory for semiflexible flagella under the action of a traveling-wave perturbation that emulates the organized active forces generated by molecular motors, capable of inducing beating patterns to the filament. By modeling the flagellum as a worm-like chain (WLC), we explore the interplay (competition) between the externally applied perturbation and the intrinsic bending rigidity of the filament. Our analysis aims to understand how this interplay can lead to a selection of conformations with the spatiotemporal behavior resembling the beating dynamics of axonemes such as those in sperm tails, in Chlamydomonas cilia, or eukaryotic flagella in general. Through a systematic analysis of the WLC's response to traveling-wave perturbations, we try to identify the key parameters that mostly influence the flagellar motion and shape its beating-like profiles.

cond-mat.soft↗

arXiv2022

Extracting causation from millennial-scale climate fluctuations in the last 800 kyr

The detection of cause-effect relationships from the analysis of paleoclimatic records is a crucial step to disentangle the main mechanisms at work in the climate system. Here, we show that the approach based on the generalized Fluctuation-Dissipation Relation, complemented by the analysis of the Transfer Entropy, allows the causal links to be identified between temperature, CO2 concentration and astronomical forcing during the glacial cycles of the last 800 kyr based on Antarctic ice core records. When considering the whole spectrum of time scales, the results of the analysis suggest that temperature drives CO2 concentration, or that are both driven by the common astronomical forcing. However, considering only millennial-scale fluctuations, the results reveal the presence of more complex causal links, indicating that CO2 variations contribute to driving the changes of temperature on such time scales. The results also evidence a slow temporal variability in the strength of the millennial-scale causal links between temperature and CO2 concentration.

physics.ao-ph↗

arXiv2022

Probability distribution functions of sub- and super-diffusive systems

We study the anomalous transport in systems of random walks (RW's) on comb-like lattices with fractal sidebranches, showing subdiffusion, and in a system of Brownian particles driven by a random shear along the x-direction, showing a superdiffusive behavior. In particular, we discuss whether scaling and universality are present or not in the shapes of the particle distribution along the preferential transport direction (x-axis).

cond-mat.stat-mech↗

arXiv2021

Correlated escape of active particles across a potential barrier

We study the dynamics of one-dimensional active particles confined in a double-well potential, focusing on the escape properties of the system, such as the mean escape time from a well. We first consider a single-particle both in near and far-from-equilibrium regimes by varying the persistence time of the active force and the swim velocity. A non-monotonic behavior of the mean escape time is observed with the persistence time of the activity, revealing the existence of an optimal choice of the parameters favoring the escape process. For small persistence times, a Kramers-like formula with an effective potential obtained within the Unified Colored Noise Approximation is shown to hold. Instead, for large persistence times, we developed a simple theoretical argument based on the first passage theory which explains the linear dependence on the escape time with the persistence of the active force. In the second part of the work, we consider the escape of two active particles mutually repelling. Interestingly, the subtle interplay of active and repulsive forces may lead to a correlation between particles favoring the simultaneous jump across the barrier. This mechanism cannot be observed in the escape process of two passive particles. Finally, we find that, in the small-persistence regime, the repulsion favors the escape, like in passive systems, in agreement with our theoretical predictions, while for large persistence times, the repulsive and active forces produce an effective attraction which hinders the barrier crossing.

cond-mat.stat-mech↗

arXiv2020

Activity-controlled clogging and unclogging of micro-channels

We propose a mechanism to control the formation of stable obstructions in two-dimensional micro-channels of variable sections taking advantage of the peculiar clustering property of active systems. Under the activation of the self-propulsion by external stimuli, the system behaves as a switch according to the following principle: by turning-on the self-propulsion the particles become active and even at very low densities stick to the walls and form growing layers eventually blocking the channel bottleneck, while the obstruction dissolves when the self-propulsion is turned off. We construct the phase diagram distinguishing clogged and open states in terms of density and bottleneck width. The study of the average clogging time, as a function of density and bottleneck width, reveals the marked efficiency of the active clogging that swiftly responds to the self-propulsion turning on. The resulting picture shows a profound difference with respect to the clogging obtained through the slow diffusive dynamics of attractive passive Brownian disks. This numerical work suggests a novel method to use particles with externally tunable self-propulsion to create or destroy plugs in micro-channels.

cond-mat.soft↗

arXiv2020

Understanding causation via correlations and linear response theory

In spite of the (correct) common-wisdom statement correlation does not imply causation, a proper employ of time correlations and of fluctuation-response theory allows to understand the causal relations between the variables of a multi-dimensional linear Markov process. It is shown that the fluctuation-response formalism can be used both to find the direct causal links between the variables of a system and to introduce a degree of causation, cumulative in time, whose physical interpretation is straightforward. Although for generic non-linear dynamics there is no simple exact relationship between correlations and response functions, the described protocol can still give a useful proxy also in presence of weak nonlinear terms.

cond-mat.stat-mech↗

arXiv2020

Diffusion properties of self-propelled particles in cellular flows

We study the dynamics of a self-propelled particle advected by a steady laminar flow. The persistent motion of the self-propelled particle is described by an active Ornstein-Uhlenbeck process. We focus on the diffusivity properties of the particle as a function of persistence time and free-diffusion coefficient, revealing non-monotonic behaviors, with the occurrence of a minimum and steep growth in the regime of large persistence time. In the latter limit, we obtain an analytical prediction for the scaling of the diffusion coefficient with the parameters of the active force. Our study sheds light on the effect of an inhomogeneous environment on the diffusion of active particles, such as living microorganisms and motile phytoplankton in fluids.

cond-mat.stat-mech↗

arXiv2020

How a local active force modifies the structural properties of polymers

We study the dynamics of a polymer, described as a variant of a Rouse chain, driven by an active terminal monomer (head). The local active force induces a transition from a globule-like to an elongated state, as revealed by the study of the end-to-end distance, whose variance is analytically predicted under suitable approximations. The change in the relaxation times of the Rouse-modes produced by the local self-propulsion is consistent with the transition from globule to elongated conformations. Moreover also the bond-bond spatial correlation for the chain head results to be affected and a gradient of over-stretched bonds along the chain is observed. We compare our numerical results both with the phenomenological stiff-polymer theory and several analytical predictions in the Rouse-chain approximation.

cond-mat.stat-mech↗

arXiv2019

Effective equations for reaction coordinates in polymer transport

In the framework of the problem of finding proper reaction coordinates (RCs) for complex systems and their effective evolution equations, we consider the case study of a polymer chain in an external double-well potential, experiencing thermally activated dynamics. Langevin effective equations describing the macroscopic dynamics of the system can be inferred from data by using a data-driven approach, once a suitable set of RCs is chosen. We show that, in this case, the validity of such choice depends on the stiffness of the polymer's bonds: if they are sufficiently rigid, we can employ a reduced description based only on the coordinate of the center of mass; whereas, if the stiffness reduces, the one-variable dynamics is no more Markovian and (at least) a second reaction coordinate has to be taken into account to achieve a realistic dynamical description in terms of memoryless Langevin equations.

cond-mat.stat-mech↗

arXiv2019

Transport of active particles in an open-wedge channel

The transport of independent active Brownian particles within a two-dimensional narrow channel, modeled as an open-wedge, is studied both numerically and theoretically. We show that the active force tends to localize the particles near the walls thus reducing the effect of the entropic force which, instead, is prevailing in the case of passive particles. As a consequence, the exit of active particles from the smaller side of the channel is facilitated with respect to their passive counterpart. By continuously re-injecting particles in the middle of the wedge, we obtain a steady regime whose properties are investigated with and without the presence of an external constant driving field. We characterize the statistics and properties of the exit process from the two opposite sides of the channel, also by making a comparison between the active and passive case. Our study reveals the existence of an optimal value of the persistence time of the active force which is able to guarantee the maximal efficiency in the transport process.

cond-mat.stat-mech↗

arXiv2018

The Role of Data in Model Building and Prediction: A Survey Through Examples

The goal of Science is to understand phenomena and systems in order to predict their development and gain control over them. In the scientific process of knowledge elaboration, a crucial role is played by models which, in the language of quantitative sciences, mean abstract mathematical or algorithmical representations. This short review discusses a few key examples from Physics, taken from dynamical systems theory, biophysics, and statistical mechanics, representing three paradigmatic procedures to build models and predictions from available data. In the case of dynamical systems we show how predictions can be obtained in a virtually model-free framework using the methods of analogues, and we briefly discuss other approaches based on machine learning methods. In cases where the complexity of systems is challenging, like in biophysics, we stress the necessity to include part of the empirical knowledge in the models to gain the minimal amount of realism. Finally, we consider many body systems where many (temporal or spatial) scales are at play and show how to derive from data a dimensional reduction in terms of a Langevin dynamics for their slow components.

cond-mat.stat-mech↗

arXiv2018

DCA for genome-wide epistasis analysis: the statistical genetics perspective

Direct Coupling Analysis (DCA) is a now widely used method to leverage statistical information from many similar biological systems to draw meaningful conclusions on each system separately. DCA has been applied with great success to sequences of homologous proteins, and also more recently to whole-genome population-wide sequencing data. We here argue that the use of DCA on the genome scale is contingent on fundamental issues of population genetics. DCA can be expected to yield meaningful results when a population is in the Quasi-Linkage Equilibrium (QLE) phase studied by Kimura and others, but not, for instance, in a phase of Clonal Competition. We discuss how the exponential (Potts model) distributions emerge in QLE, and compare couplings to correlations obtained in a study of about 3,000 genomes of the human pathogen Streptococcus pneumoniae.

q-bio.PE↗

arXiv2018

Frequency-control of protein translocation across an oscillating nanopore

The translocation of a Lipid Binding Protein (LBP) is studied using a phenomenological coarse-grained computational model that simplifies both chain and pore geometry. We investigated via molecular dynamics the interplay between transport and unfolding in the presence of a nanopore whose section oscillates periodically in time with a frequency omega, a motion often referred to as radial breathing mode (RBM). We found that the LPB when mechanically pulled into the vibrating nanopore exhibits a translocation dynamics that in some frequency range is accelerated and shows a frequency locking to the pore dynamics. The main effect of pore vibrations is the suppression of stalling events of the translocation dynamics, hence, a proper frequency tuning allows both regularization and control of the overall transport process. Finally, the interpretation of the simulation results is easily achieved by resorting to a first passage theory of elementary driven-diffusion processes.

cond-mat.soft↗

arXiv2016

Reaction Spreading in Systems With Anomalous Diffusion

We briefly review some aspects of the anomalous diffusion, and its relevance in reactive systems. In particular we consider {\it strong anomalous} diffusion characterized by the moment behaviour $\langle x(t)^q \rangle \sim t^{q ν(q)}$, where $ν(q)$ is a non constant function, and we discuss its consequences. Even in the apparently simple case $ν(2)=1/2$, strong anomalous diffusion may correspond to non trivial features, such as non Gaussian probability distribution and peculiar scaling of large order moments. When a reactive term is added to a normal diffusion process, one has a propagating front with a constant velocity. The presence of anomalous diffusion by itself does not guarantee a changing in the front propagation scenario; a key factor to select linear in time or faster front propagation has been identified in the shape of the probability distribution tail in absence of reaction. In addition, we discuss the reaction spreading on graphs, underlying the major role of the connectivity properties of these structures, characterized by the {\em connectivity dimension}

cond-mat.stat-mech↗

arXiv2015

Driven diffusion against electrostatic or effective energy barrier across Alpha-Hemolysin

We analyze the translocation of a charged particle across an Alpha-Hemolysin (aHL) pore in the framework of a driven diffusion over an extended energy barrier generated by the electrical charges of the aHL. A one-dimensional electrostatic potential is extracted from the full 3D solution of the Poisson's equation. We characterize the particle transport under the action of a constant forcing by studying the statistics of the translocation time. We derive an analytical expression of translocation time average that compares well with the results from Brownian dynamic simulations of driven particles over the electrostatic potential. Moreover, we show that the translocation time distributions can be perfectly described by a simple theory which replaces the true barrier by an equivalent structureless square barrier. Remarkably our approach maintains its accuracy also for low-applied voltage regimes where the usual inverse-Gaussian approximation fails. Finally we discuss how the comparison between the simulated time distributions and their theoretical prediction results to be greatly simplified when using the notion of the empirical Laplace transform technique.

q-bio.BM↗

arXiv2015

The role of the number of degrees of freedom and chaos in macroscopic irreversibility

This article aims at revisiting, with the aid of simple and neat numerical examples, some of the basic features of macroscopic irreversibility, and, thus, of the mechanical foundation of the second principle of thermodynamics as drawn by Boltzmann. Emphasis will be put on the fact that, in systems characterized by a very large number of degrees of freedom, irreversibility is already manifest at a single-trajectory level for the vast majority of the far-from-equilibrium initial conditions - a property often referred to as typicality. We also discuss the importance of the interaction among the microscopic constituents of the system and the irrelevance of chaos to irreversibility, showing that the same irreversible behaviours can be observed both in chaotic and non-chaotic systems.

cond-mat.stat-mech↗