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A reduced protein model with five to six atoms per amino acid and five amino acid types is developed and tested on a three-helix-bundle protein, a 46-amino acid fragment from staphylococcal protein A. The model does not rely on the widely…

Soft Condensed Matter · Physics 2007-05-23 Giorgio Favrin , Anders Irbäck , Stefan Wallin

Proteins are miniature machines whose function depends on their three-dimensional (3D) structure. Determining this structure computationally remains an unsolved grand challenge. A major bottleneck involves selecting the most accurate…

Quantitative Methods · Quantitative Biology 2020-11-30 Stephan Eismann , Patricia Suriana , Bowen Jing , Raphael J. L. Townshend , Ron O. Dror

Protein-protein interactions (protein functionalities) are mediated by water, which compacts individual proteins and promotes close and temporarily stable large-area protein-protein interfaces. In their classic paper Kyte and Doolittle (KD)…

Soft Condensed Matter · Physics 2009-11-13 Alexander E. Kister , James C. Phillips

Using a coarse-grained model, self-organized assembly of proteins (e.g. CorA and its inner segment iCorA) is studied by examining quantities such as contact profile, radius of gyration, and structure factor as a function of protein…

Atomistic force fields that are tuned to describe folded proteins predict overly compact structures for intrinsically disordered proteins (IDPs). To correct this, improvements in force fields to better model IDPs are usually paired with…

Chemical Physics · Physics 2024-04-12 Rohan S. Adhikari , Dilipkumar N. Asthagiri , Walter G. Chapman

The prediction of the three-dimensional native structure of proteins from the knowledge of their amino acid sequence, known as the protein folding problem, is one of the most important yet unsolved issues of modern science. Since the…

Biological Physics · Physics 2008-11-24 Pablo Echenique

The study of protein mass transport via atomistic simulation requires time and length scales beyond the computational capabilities of modern computer systems. The raspberry model for colloidal particles in combination with the mesoscopic…

Soft Condensed Matter · Physics 2017-04-28 Vincent Ustach , Roland Faller

A fast and accurate grid-based method with low memory requirement is presented to calculate volume characteristics in molecular systems. The distribution of volume and packing density is characterized in globular proteins, where void space…

Biological Physics · Physics 2018-10-23 Jenny Farmer , Sheridan B. Green , Donald J. Jacobs

The biological activity and functional specificity of proteins depend on their native three-dimensional structures determined by inter- and intra-molecular interactions. In this paper, we investigate the geometrical factor of protein…

Biological Physics · Physics 2012-03-02 Ming-Chya Wu , Mai Suan Li , Wen-Jong Ma , Maksim Kouza , Chin-Kun Hu

We present a technique for obtaining an effective packing fraction for discontinuous shear thickening suspensions near a critical point. It uses a measurable quantity that diverges at the critical point -- in this case the inverse of the…

Soft Condensed Matter · Physics 2019-04-17 Rijan Maharjan , Eric Brown

We present two methods for computing the dynamic structure factor for warm dense hydrogen without invoking either the Born-Oppenheimer approximation or the Chihara decomposition, by employing a wave-packet description that resolves the…

A kinetic model for the nucleation mechanism of protein folding is proposed. A protein is modeled as a heteropolymer consisting of hydrophobic and hydrophilic beads with equal constant bond lengths and bond angles. The total energy of the…

Biological Physics · Physics 2007-05-23 Yuri S. Djikaev

We present a new numerical scheme to study systems of non-convex, irregular, and punctured particles in an efficient manner. We employ this method to analyze regular packings of odd-shaped bodies, not only from a nanoparticle but also both…

Soft Condensed Matter · Physics 2015-05-28 Joost de Graaf , René van Roij , Marjolein Dijkstra

Determining the 3D structures of proteins is essential in understanding their behavior in the cellular environment. Computational methods of predicting protein structures have advanced, but assessing prediction accuracy remains a challenge.…

Biomolecules · Quantitative Biology 2024-07-29 Musa Azeem , Homayoun Valafar

Through extensive Monte Carlo simulations, we systematically study the effect of chain stiffness on the packing ability of linear polymers composed of hard spheres in extremely confined monolayers, corresponding effectively to 2D films.…

We develop a transfer matrix formalism to visualize the framing of discrete piecewise linear curves in three dimensional space. Our approach is based on the concept of an intrinsically discrete curve, which enables us to more effectively…

Biomolecules · Quantitative Biology 2015-05-27 Shuangwei Hu , Martin Lundgren , Antti J. Niemi

Novel numerical techniques, validated by an analysis of barnase and chymotrypsin inhibitor, are used to elucidate the paramount role played by the geometry of the protein backbone in steering the folding to the correct native state. It is…

Statistical Mechanics · Physics 2009-10-31 Cristian Micheletti , Jayanth R. Banavar , Amos Maritan , Flavio Seno

We present a method for discovering dense packings of general convex hard particles and apply it to study the dense packing behavior of a one-parameter family of particles with tetrahedral symmetry representing a deformation of the ideal…

Soft Condensed Matter · Physics 2013-01-28 Yoav Kallus , Veit Elser

The formation of quasi-spherical cages from protein building blocks is a remarkable self-assembly process in many natural systems, where a small number of elementary building blocks are assembled to build a highly symmetric icosahedral…

Random packings and their properties are a popular and active field of research. Numerical algorithms that can efficiently generate them are useful tools in their study. This paper focuses on random packings produced according to the random…

Computational Physics · Physics 2019-12-25 Michał Cieśla , Piotr Kubala , Ge Zhang
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