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Understanding the dynamic nature of protein structures is essential for comprehending their biological functions. While significant progress has been made in predicting static folded structures, modeling protein motions on microsecond to…

We present a collision model for particle-particle and particle-wall interactions in interface-resolved simulations of particle-laden flows. Three types of inter-particle interactions are taken into account: (1) long- and (2) short-range…

Fluid Dynamics · Physics 2021-02-23 Pedro Costa , Bendiks Jan Boersma , Jerry Westerweel , Wim-Paul Breugem

The behavior of the self diffusion constant of Langevin particles interacting via a pairwise interaction is considered. The diffusion constant is calculated approximately within a perturbation theory in the potential strength about the bare…

Soft Condensed Matter · Physics 2009-11-10 D. S. Dean , A. Lefèvre

The phase-separation occurring in a system of mutually interacting proteins that can bind on specific sites of a chromatin fiber is here investigated. This is achieved by means of extensive Molecular Dynamics simulations of a simple polymer…

Soft Condensed Matter · Physics 2020-10-16 Andrea M. Chiariello , Federico Corberi , Mario Salerno

Phase separation plays an role in determining the self-assembly of biological and soft-matter systems. In biological systems, liquid-liquid phase separation inside a cell leads to the formation of various macromolecular aggregates. The…

Soft Condensed Matter · Physics 2024-03-26 Tanmay Biswas , Gerhard Kahl , Gaurav P. Shrivastav

Designing protein-binding proteins with high affinity is critical in biomedical research and biotechnology. Despite recent advancements targeting specific proteins, the ability to create high-affinity binders for arbitrary protein targets…

Machine Learning · Computer Science 2025-11-03 Zhenqiao Song , Tiaoxiao Li , Lei Li , Martin Renqiang Min

The dynamic of complex ordering systems with active rotational degrees of freedom exemplified by protein self-assembly is explored using a machine learning workflow that combines deep learning-based semantic segmentation and rotationally…

Soft Condensed Matter · Physics 2021-04-26 Sergei V. Kalinin , Shuai Zhang , Mani Valleti , Harley Pyles , David Baker , James J. De Yoreo , Maxim Ziatdinov

Proteins are inherently multiscale physical systems whose functional properties emerge from coordinated structural organization across multiple spatial resolutions, ranging from atomic interactions to global fold topology. However, existing…

Machine Learning · Computer Science 2026-05-13 Viet Thanh Duy Nguyen , John K. Johnstone , Truong-Son Hy

We present a thermodynamically consistent mesoscopic model of protein adsorption at liquid-solid interfaces. First describing the equilibrium state under varying protein concentration of the solution and binding conditions, we predict a…

Soft Condensed Matter · Physics 2016-08-31 Gergely J. Szollosi , Imre Derenyi , Janos Voros

We introduce a powerful iterative algorithm to compute protein folding pathways, with realistic all-atom force fields. Using the path integral formalism, we explicitly derive a modified Langevin equation which samples directly the ensemble…

Biological Physics · Physics 2017-05-08 S. Orioli , S. A Beccara , P. Faccioli

Soft materials (e.g., enveloped viruses, liposomes, membranes and supercooled liquids) simultaneously deform or display collective behaviors, while undergoing atomic scale vibrations and collisions. While the multiple space-time character…

Soft Condensed Matter · Physics 2014-01-03 Peter Ortoleva , Abhishek Singharoy , Stephen Pankavich

The possibility of deriving the contact potentials between amino acids from their frequencies of occurence in proteins is discussed in evolutionary terms. This approach allows the use of traditional thermodynamics to describe such…

Biomolecules · Quantitative Biology 2009-11-10 G. Tiana , M. Colombo , D. Provasi , R. A. Broglia

Advances in experimental techniques and in theoretical models have improved our understanding of protein crystallization. But they have also left open questions regarding the protein phase behavior and self-assembly kinetics, such as why…

Soft Condensed Matter · Physics 2014-03-19 Diana Fusco , Patrick Charbonneau

We analyze protein-protein interaction networks for six different species under the framework of random matrix theory. Nearest neighbor spacing distribution of the eigenvalues of adjacency matrices of the largest connected part of these…

Molecular Networks · Quantitative Biology 2014-05-20 Ankit Agrawal , Camellia Sarkar , Sanjiv K. Dwivedi , Nitesh Dhasmana , Sarika Jalan

The phase transition of the one-dimensional, diffusive pair contact process (PCPD) is investigated by N cluster mean-field approximations and high precision simulations. The N=3,4 cluster approximations exhibit smooth transition line to…

Statistical Mechanics · Physics 2009-11-07 Geza Odor

Large ensembles of stochastically evolving interacting particles describe phenomena in diverse fields including statistical physics, neuroscience, biology, and engineering. In such systems, the infinitesimal evolution of each particle…

Probability · Mathematics 2024-01-02 Kavita Ramanan

The intricate three-dimensional geometries of protein tertiary structures underlie protein function and emerge through a folding process from one-dimensional chains of amino acids. The exact spatial sequence and configuration of amino…

Biomolecules · Quantitative Biology 2021-02-24 Nora Molkenthin , Steffen Mühle , Antonia S J S Mey , Marc Timme

Developments in dynamical systems theory provides new support for the macroscale modelling of pdes and other microscale systems such as Lattice Boltzmann, Monte Carlo or Molecular Dynamics simulators. By systematically resolving subgrid…

Numerical Analysis · Mathematics 2012-01-18 A. J. Roberts , Tony MacKenzie , J. E. Bunder

We investigate entanglement between collective operators of two wave-packets of finite spectral bandwidth, in two different approximations of the Multimode Parametric-Down Conversion (MPDC) process: the pairwise and the one-to-all…

Quantum Physics · Physics 2012-10-11 Ana M. Martins

Studies on random packing of bidispersive particles have shown that such systems can capture the underlying behavior of more complex phenomena found in physics and materials engineering. In industry, bidispersive particles are used to allow…

Statistical Mechanics · Physics 2020-10-22 Carlos Handrey Araujo Ferraz
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