arXiv subjects

Achille Giacometti

Publications and source records attributed to Achille Giacometti.

At least 37 records · Page 2Linked to original sources

arXiv2023

A geometrical framework for thinking about proteins

We present a model, based on symmetry and geometry, for proteins. Using elementary ideas from mathematics and physics, we derive the geometries of discrete helices and sheets. We postulate a compatible solvent-mediated emergent pairwise attraction that assembles these building blocks, while respecting their individual symmetries. Instead of seeking to mimic the complexity of proteins, we look for a simple abstraction of reality that yet captures the essence of proteins. We employ analytic calculations and detailed Monte Carlo simulations to explore some consequences of our theory. The predictions of our approach are in accord with experimental data. Our framework provides a rationalization for understanding the common characteristics of proteins. Our results show that the free energy landscape of a globular protein is pre-sculpted at the backbone level, sequences and functionalities evolve in the fixed backdrop of the folds determined by geometry and symmetry, and that protein structures are unique in being simultaneously characterized by stability, diversity, and sensitivity.

cond-mat.soft↗

arXiv2023

II. Geometrical framework for thinking about globular proteins: the power of poking

Recently, we presented a framework for understanding protein structure based on the idea that simple constructs of holding hands or touching of objects can be used to rationalize the common characteristics of globular proteins. We developed a consistent approach for understanding the formation of the two key common building blocks of helices and sheets as well as the compatible assembly of secondary structures into the tertiary structure through the notion of poking pairwise interactions. Here we benchmark our predictions with a detailed analysis of structural data of over 4000 proteins from the Protein Data Bank. We also present the results of detailed computer simulations of a simplified model demonstrating a pre-sculpted free energy landscape, determined by geometry and symmetry, comprising numerous minima corresponding to putative native state structures. We explore the consequences of our model. Our results suggest that symmetry and geometry are a powerful guide to capture the simplicity underlying protein complexity.

cond-mat.soft↗

arXiv2023

Solvent quality and solvent polarity in polypeptides

Using molecular dynamics and thermodynamic integration, we report on the solvation process in water and in cyclohexane of seven polypeptides (GLY, ALA, ILE, ASN, LYS, ARG, GLU). The polypeptides are selected to cover the full hydrophobic scale while varying their chain length from tri- to undeca-homopeptides provide indications on possible non-additivity effects as well as the role of the peptide backbone in the overall stability of the polypeptides. The use of different solvents and different polypeptides allows us to investigate the relation between solvent quality -- the capacity of a given solvent to fold a given biopolymer often described on a scale ranging from "good" to "poor", and solvent polarity -- related to the specific interactions of any solvent with respect to a reference solvent. Undeca-glycine is found to be the only polypeptides to have a proper stable collapse in water (polar solvent), with the other hydrophobic polypetides displaying in water repeated folding and unfolding events and with polar polypeptides presenting a even more complex behavior. By contrast, all polypeptides but none are found to keep an extended conformation in cyclohexane, irrespective of their polarity. All considered polypeptides are also found to have a favorable solvation free energy independently of the solvent polarity and their intrinsic hydrophobicity, clearly highlighting the prominent stabilizing role of the peptide backbone, with the solvation process largely enthalpically dominated in polar polypeptides and partially entropically driven for hydrophobic polypeptides. Our study thus reveals the complexity of the solvation process of polypeptides defying the common view " like dissolves like", with the solute polarity playing the most prominent role. The absence of a mirror symmetry upon the inversion of polarities of both the solvent and the polypeptides is confirmed.

cond-mat.soft↗

arXiv2022

The Thermodynamic Origins of Chiral Twist in Monolayer Assemblies of Hard Rod-like Colloids

The propagation of chirality across scales is a common but poorly understood phenomenon in soft matter. In this work, we use computer simulations to study chiral monolayer assemblies formed by hard rod-like colloidal particles in the presence of non-adsorbing polymer and characterize the thermodynamic driving forces responsible for the twisting. Simulations show that straight (achiral) rods assemble into monolayers with a spontaneous twist that is either left- or right-handed, while helical (chiral) rods lead to assemblies with preferential chiral features that depend on their handedness and curliness. The onset of chirality in these monolayers can be traced back to small clusters formed at the initial stage of the self-assembly. In these microscopic monolayers, entropy drives twisting in ways that differ from the assumptions on which existing continuum theory is built. Depending on the geometry of the constituent rods, the preferred chiral twist can be driven by entropy gain of the polymers, or of the rods, or both. In addition, the variation of the polymer entropy with twist depends on changes in both the surface area and the volume of the monolayer. Rod fluctuations perpendicular to the monolayer also play an important role in stabilising the twisting.

cond-mat.soft↗

arXiv2021

Proteins -- a celebration of consilience

Proteins are the common constituents of all living cells. They are molecular machines that interact with each other as well as with other cell products and carry out a dizzying array of functions with distinction. These interactions follow from their native state structures and therefore understanding sequence-structure relationships is of fundamental importance. What is quite remarkable about proteins is that their understanding necessarily straddles several disciplines. The importance of geometry in defining protein native state structure, the constraints placed on protein behavior by mathematics and physics, the need for proteins to obey the laws of quantum chemistry, and the rich role of evolution and biology all come together in defining protein science. Here we review ideas from the literature and present an interdisciplinary framework that aims to marry ideas from Plato and Darwin and demonstrates an astonishing consilience between disciplines in describing proteins. We discuss the consequences of this framework on protein behavior.

q-bio.BM↗

arXiv2021

Marginally compact phase and ordered ground states in a model polymer with side spheres

We present the results of a quantitative study of the phase behavior of a model polymer chain with side spheres using two independent computer simulation techniques. We find that the mere addition of side spheres results in key modifications of standard polymer behavior. One obtains a novel marginally compact phase at low temperatures, the structures in this phase are reduced in dimensionality and are ordered, they include strands assembled into sheets and a variety of helices, and at least one of the transitions on lowering the temperature to access these ordered states is found to be first order. Our model serves to partially bridge conventional polymer phases with biomolecular phases.

cond-mat.soft↗

arXiv2021

Spontaneous dimensional reduction and novel ground state degeneracy in a simple chain model

Chain molecules play a key role in the polymer field and in living cells. Our focus is on a new homopolymer model of a linear chain molecule subject to an attractive self-interaction promoting compactness. We analyze the model using simple analytic arguments complemented by extensive computer simulations. We find several striking results: there is a first order transition from a high temperature random coil phase to a highly unusual low temperature phase; the modular ground states exhibit significant degeneracy; the ground state structures exhibit spontaneous dimensional reduction and have a two-layer structure; and the ground states are assembled from secondary motifs of helices and strands connected by tight loops. We discuss the similarities and notable differences between the ground state structures (we call these PoSSuM -- Planar Structures with Secondary Motifs) in the novel phase and protein native state structures.

cond-mat.stat-mech↗

arXiv2021

Phase behaviour of hard cylinders

Using isobaric Monte Carlo simulations, we map out the entire phase diagram of a system of hard cylindrical particles of length $L$ and diameter $D$, using an improved algorithm to identify the overlap condition between two cylinders. Both the prolate $L/D>1$ and the oblate $L/D<1$ phase diagrams are reported with no solution of continuity. In the prolate $L/D>1$ case, we find intermediate nematic \textrm{N} and smectic \textrm{SmA} phases in addition to a low density isotropic \textrm{I} and a high density crystal \textrm{X} phase, with \textrm{I-N-SmA} and \textrm{I-SmA-X} triple points. An apparent columnar phase \textrm{C} is shown to be metastable as in the case of spherocylinders. In the oblate $L/D<1$ case, we find stable intermediate cubatic \textrm{Cub}, nematic \textrm{N}, and columnar \textrm{C} phases with \textrm{I-N-Cub}, \textrm{N-Cub-C}, and \textrm{I-Cub-C} triple points. Comparison with previous numerical and analytical studies is discussed. The present study, accounting for the explicit cylindrical shape, paves the way to more sophisticated models with important biological applications, such as viruses and nucleosomes.

cond-mat.soft↗

arXiv2021

Local sequence-structure relationships in proteins

We seek to understand the interplay between amino acid sequence and local structure in proteins. Are some amino acids unique in their ability to fit harmoniously into certain local structures? What is the role of sequence in sculpting the putative native state folds from myriad possible conformations? In order to address these questions, we represent the local structure of each C-alpha atom of a protein by just two angles, theta and mu, and we analyze a set of more than 4000 protein structures from the PDB. We use a hierarchical clustering scheme to divide the 20 amino acids into six distinct groups based on their similarity to each other in fitting local structural space. We present the results of a detailed analysis of patterns of amino acid specificity in adopting local structural conformations and show that the sequence-structure correlation is not very strong compared to a random assignment of sequence to structure. Yet, our analysis may be useful to determine an effective scoring rubric for quantifying the match of an amino acid to its putative local structure.

q-bio.BM↗

arXiv2021

Building blocks of protein structures -- Physics meets Biology

The native state structures of globular proteins are stable and well-packed indicating that self-interactions are favored over protein-solvent interactions under folding conditions. We use this as a guiding principle to derive the geometry of the building blocks of protein structures, alpha-helices and strands assembled into beta-sheets, with no adjustable parameters, no amino acid sequence information, and no chemistry. There is an almost perfect fit between the dictates of mathematics and physics and the rules of quantum chemistry. Our theory establishes an energy landscape that channels protein evolution by providing sequence-independent platforms for elaborating sequence-dependent functional diversity. Our work highlights the vital role of discreteness in life and has implications for the creation of artificial life and on the nature of life elsewhere in the cosmos.

q-bio.BM↗

arXiv2020

Can the roles of polar and non-polar moieties be reversed in non-polar solvents?

Using thermodynamics integration, we study the solvation free energy of 18 amino acid side chain equivalents in solvents with different polarity, ranging from the most polar water to the most non-polar cyclohexane. The amino acid side chain equivalents are obtained from the 20 natural amino acids by replacing the backbone part with a hydrogen atom, and discarding proline and glycine that have special properties. A detailed analysis of the relative solvation free energies suggests how it is possible to achieve a robust and unambiguous hydrophobic scale for the amino acids. By discriminating the relative contributions of the entropic and enthalpic terms, we find strong negative correlations in water and ethanol, associated with the well-known entropy-enthalpy compensation, and a much reduced correlation in cyclohexane. This shows that in general the role of the polar and non-polar moieties cannot be reversed in a non-polar solvent. Our findings are compared with past experimental as well as numerical results, and may shed additional light on the unique role of water as biological solvent.

cond-mat.soft↗

arXiv2020

Computational Pipeline to probe NaV1.7 gain-of-functions variants in neuropathic painful syndromes

Applications of machine learning and graph theory techniques to neuroscience have witnessed an increased interest in the last decade due to the large data availability and unprecedented technology developments. Their employment to investigate the effect of mutational changes in genes encoding for proteins modulating the membrane of excitable cells, whose biological correlates are assessed at electrophysiological level, could provide useful predictive clues. We apply this concept to the analysis of variants in sodium channel NaV1.7 subunit found in patients with chronic painful syndromes, by the implementation of a dedicated computational pipeline empowering different and complementary techniques including homology modeling, network theory, and machine learning. By testing three templates of different origin and sequence identities, we provide an optimal condition for its use. Our findings reveal the usefulness of our computational pipeline in supporting the selection of candidates for cell electrophysiology assay and with potential clinical applications.

cond-mat.soft↗

arXiv2020

An integrated DEM-FEM approach to study breakage in packing of glass cartridges on a conveyor belt

The use of glass for pharmaceutical new applications such as high-technology drugs, requires the strictest container inertness. A common theme of paramount importance in glass container integrity preservation is the detailed mechanism driving the sudden failure due the crack propagation. Using a combination of Discrete Element Method (DEM) and Finite Element Method (FEM), a stress map for glass cartridges packed into an accumulation table and transported by a conveyor belt at a fixed velocity is obtained under realistic conditions. The DEM calculation provides a full description of the dynamics of the cartridges, as approximated by an equivalent sphere, as well as the statistics of the multiple collisions. The FEM calculation exploits this input to provide the maximum principal stress of different pairs as a function of time. Our analysis shows that, during their transportation on the conveyor belt, the cartridges are subject to several shocks of varying intensities. Under these conditions, a crack may originate inside the cartridge in the area of maximal tensile stress, and propagate outward. Estimated stresses are found in good agreement with real systems.

cond-mat.soft↗

arXiv2019

Chain stiffness bridges conventional polymer and bio-molecular phases}

Chain molecules play important roles in industry and in living cells. Our focus here is on distinct ways of modeling the stiffness inherent in a chain molecule. We consider three types of stiffnesses -- one yielding an energy penalty for local bends (energetic stiffness) and the other two forbidding certain classes of chain conformations (entropic stiffness). Using detailed Wang-Landau microcanonical Monte Carlo simulations, we study the interplay between the nature of the stiffness and the ground state conformation of a self-attracting chain. We find a wide range of ground state conformations including a coil, a globule, a toroid, rods, helices, zig-zag strands resembling $β$-sheets, as well as knotted conformations allowing us to bridge conventional polymer phases and biomolecular phases. An analytical mapping is derived between the persistence lengths stemming from energetic and entropic stiffness. Our study shows unambiguously that different stiffness play different physical roles and have very distinct effects on the nature of the ground state of the conformation of a chain, even if they lead to identical persistence lengths.

cond-mat.soft↗

arXiv2019

Local symmetry determines the phases of linear chains: a simple model for the self-assembly of peptide

We discuss the relation between the emergence of new phases with broken symmetry within the framework of simple models of biopolymers. We start with a classic model for a chain molecule of spherical beads tethered together, with the steric constraint that non-consecutive beads cannot overlap, and with a pairwise attractive square well potential accounting for the hydrophobic effect and promoting compaction. We then discuss the consequences of the successive breaking of spurious symmetries. First, we allow the partial interpenetration of consecutive beads. In addition to the standard high temperature coil phase and the low temperature collapsed phase, this results in a new class of marginally compact ground states comprising conformations reminiscent of $α$-helices and $β$-sheets, the building blocks of the native states of globular proteins. We then discuss the effect of a further symmetry breaking of the cylindrical symmetry on attaching a side-sphere to the backbone beads along the negative normal of the chain, to mimic the presence of side chains in real proteins. This leads to the emergence of a novel phase within the previously obtained marginally compact phase, with the appearance of more complex secondary structure assemblies. The potential importance of this new phase in the \textit{de novo} design of self-assembled peptides is highlighted.

cond-mat.soft↗

arXiv2018

The elixir phase of chain molecule

A phase of matter is a familiar notion for inanimate physical matter. The nature of a phase of matter transcends the microscopic material properties. For example, materials in the liquid phase have certain common properties independent of the chemistry of the constituents: liquids take the shape of the container; they flow; and they can be poured -- alcohol, oil and water as well as a Lennard-Jones computer model exhibit similar behavior when poised in the liquid phase. Here we identify a hitherto unstudied `phase' of matter, the elixir phase, in a simple model of a polymeric chain whose backbone has the correct local cylindrical symmetry induced by the tangent to the chain. The elixir phase appears on breaking the cylindrical symmetry by adding side spheres along the negative normal direction, as in proteins. This phase, nestled between other phases, has multiple ground states made up of building blocks of helices and almost planar sheets akin to protein native folds. We discuss the similarities of this `phase' of a finite size system to the liquid crystal and spin glass phases. Our findings are relevant for understanding proteins; the creation of novel bio-inspired nano-machines; and also may have implications for life elsewhere in the cosmos.

cond-mat.soft↗

arXiv2018

Excitation Energy Transport with Noise and Disorder in a Model of the Selectivity Filter of an Ion Channel

Selectivity filter is a gate in ion channels which are responsible for the selection and fast conduction of particular ions across the membrane (with high throughput rates of $10^8$ ions/sec and a high 1:$10^4$ discrimination rate between ions). It is made of four strands as the backbone, and each strand is composed of sequences of five amino acids connected by peptide units H-N-C=O in which the main molecules in the backbone that interact with ions in the filter are carbonyl (C=O) groups that mimic the transient interactions of ion with binding sites during ion conduction. It has been suggested that quantum coherence and possible emergence of resonances in the backbone carbonyl groups may play a role in mediating ion conduction and selectivity in the filter. Here, we investigate the influence of noise and disorder on the efficiency of excitation energy transfer (EET) in a linear harmonic chain of $N=5$ sites with dipole-dipole couplings as a simple model for one P-loop strand of the selectivity filter backbone in biological ion channels. We include noise and disorder inherent in real biological systems by including spatial disorder in the chain, and random noise within a weak coupling quantum master equation approach. Our results show that disorder in the backbone considerably reduces EET, but the addition of noise helps to recover high EET for a wide range of system parameters. Our analysis may help for better understanding of the coordination of ions in the filter as well as the fast and efficient functioning of the selectivity filters in ion channels.

physics.bio-ph↗

arXiv2018

Universal effects of solvent species on the stabilized structure of a protein

We investigate the effects of solvent specificities on the stability of the native structure (NS) of a protein on the basis of our free-energy function (FEF). We use CPB-bromodomain (CBP-BD) and apoplastocyanin (apoPC) as representatives of the protein universe and water, methanol, ethanol, and cyclohexane as solvents. The NSs of CBP-BD and apoPC consist of 66$\%$ $α$-helices and of 35$\%$ $β$-sheets and 4$\%$ $α$-helices, respectively. In order to assess the structural stability of a given protein immersed in each solvent, we contrast the FEF of its NS against that of a number of artificially created, misfolded decoys possessing the same amino-acid sequence but significantly different topology and $α$-helix and $β$-sheet contents. We find that for both CBP-BD and apoPC, the energetic component dominates in methanol, ethanol, and cyclohexane, with the most stable structures in these solvents sharing the same characteristics described as an association of a-helices. In water, the entropic component is as strong as or even stronger than the energetic one, with a large gain of translational, configurational entropy of water becoming crucially important, so that the relative contents of $α$-helix and $β$-sheet and the content of total secondary structures are carefully selected to achieve sufficiently close packing of side chains. Our analysis, which requires minimal computational effort, can be applied to any protein immersed in any solvent and provides robust predictions that are quite consistent with the experimental observations for proteins in different solvent environments, thus paving the way toward a more detailed understanding of the folding process.

cond-mat.soft↗