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This review is a tutorial for scientists interested in the problem of protein structure prediction, particularly those interested in using coarse-grained molecular dynamics models that are optimized using lessons learned from the energy…

Biomolecules · Quantitative Biology 2014-01-06 N. P. Schafer , B. L. Kim , W. Zheng , P. G. Wolynes

Proton scattering in some water and tissue equivalent phantom materials was measured to evaluate their simulation accuracy of water and respective human biological tissues. The measurements were performed on the medical facility of the ITEP…

Medical Physics · Physics 2010-11-23 V. N. Vasiliev , V. I. Kostjuchenko , V. G. Khaybullin , S. I. Samarin , A. S. Uglov

Large protein assemblies, such as virus capsids, may be coarse-grained as a set of rigid domains linked by generalized (rotational and stretching) harmonic springs. We present a method to obtain the elastic parameters and overdamped…

Biomolecules · Quantitative Biology 2013-05-29 Stephen D. Hicks , C. L. Henley

A reduced model, which can fold both helix and sheet structures, is proposed to study the problem of protein folding. The goal of this model is to find an unbiased effective potential that has included the effects of water and at the same…

Soft Condensed Matter · Physics 2007-05-23 Nan-yow Chen

Intrinsically Disordered Proteins (IDPs) perform a broad range of biological functions. Their relevance has motivated intense research activity seeking to characterize their sequence/structure/function relationships. However, the…

Grazing-incidence X-ray diffraction (GIXRD) is a scattering technique which allows one to characterize the structure of fluid interfaces down to the molecular scale, including the measurement of the surface tension and of the interface…

Soft Condensed Matter · Physics 2024-04-10 Felix Höfling , Siegfried Dietrich

Theoretical concepts in condensed matter physics are typically verified and also developed by exploiting computer simulations mostly in simple models. Predictions based on these usually isotropic models are often at odds with measurement…

Soft Condensed Matter · Physics 2020-11-13 K. Koperwas , A. Grzybowski , M. Paluch

The lifetime and utilization of a nuclear fusion reactor like ITER depends strongly on its capabilities to mitigate damage during disruptions. While shattered pellet injection (SPI) was chosen as the baseline mitigation method for ITER, the…

Plasma Physics · Physics 2022-09-05 Tobias Peherstorfer

Intrinsically disordered proteins (IDPs) constitute a broad set of proteins with few uniting and many diverging properties. IDPs-and intrinsically disordered regions (IDRs) interspersed between folded domains-are generally characterized as…

Biomolecules · Quantitative Biology 2021-06-03 Kresten Lindorff-Larsen , Birthe B. Kragelund

We report simulation studies of 33 single intrinsically disordered proteins (IDPs) using coarse-grained (CG) bead-spring models where interactions among different amino acids are introduced through a hydropathy matrix and additional…

Soft Condensed Matter · Physics 2023-12-07 Swarnadeep Seth , Brandon Stine , Aniket Bhattacharya

We propose an algorithmic strategy for improving the efficiency of Monte Carlo searches for the low-energy states of proteins. Our strategy is motivated by a model of how proteins alter their shapes. In our model when proteins fold under…

Soft Condensed Matter · Physics 2009-11-07 Michael Cahill , Sean Cahill , Kevin Cahill

We propose to develop mean field theory in combination with Glauber algorithm, to model and interpret protein dynamics and structure formation in small to wide angle x-ray scattering (S/WAXS) experiments. We develop the methodology by…

Biomolecules · Quantitative Biology 2017-12-20 Alexandr Nasedkin , Jan Davidsson , Antti J. Niemi , Xubiao Peng

Many biochemical applications such as molecular property prediction require models to generalize beyond their training domains (environments). Moreover, natural environments in these tasks are structured, defined by complex descriptors such…

Machine Learning · Computer Science 2020-10-08 Wengong Jin , Regina Barzilay , Tommi Jaakkola

Granular media (e.g., cereal grains, plastic resin pellets, and pills) are ubiquitous in robotics-integrated industries, such as agriculture, manufacturing, and pharmaceutical development. This prevalence mandates the accurate and efficient…

Robotics · Computer Science 2020-11-06 Carolyn Matl , Yashraj Narang , Ruzena Bajcsy , Fabio Ramos , Dieter Fox

Biomaterials such as protein or polysaccharide gels are known to behave qualitatively as soft solids and to rupture under an external load. Combining optical and ultrasonic imaging to shear rheology we show that the failure scenario of a…

Soft Condensed Matter · Physics 2014-08-21 Mathieu Leocmach , Christophe Perge , Thibaut Divoux , Sébastien Manneville

The conformational complexity of linear polymers far exceeds that of point-like atoms and molecules. Polymers can bend, twist, even become knotted. Thus they may also display a much richer phase structure than point particles. But it is not…

Biological Physics · Physics 2015-06-16 Andrey Krokhotin , Stam Nicolis , Antti J. Niemi

Liquid cellular compartments spatially segregate from the cytoplasm and can regulate aberrant protein aggregation, a process linked to several medical conditions, including Alzheimer's and Parkinson's diseases. Yet the mechanisms by which…

Biological Physics · Physics 2018-09-11 Christoph A. Weber , Thomas C. T. Michaels , L. Mahadevan

Irradiation-induced void swelling is a critical degradation mechanism for structural materials in nuclear reactors, dictating component operational lifespan and safety. While recent machine learning (ML) approaches have improved the…

Applications · Statistics 2026-03-03 Minhee Kim , Yong Yang

We outline a strategy for quantitatively evaluating the conformational characteristics of self-assembled structures using the techniques of contrast variation small angle neutron scattering. By means of basis function expansion, a case…

Soft Condensed Matter · Physics 2021-10-27 Albert Y. Ho , Guan-Rong Huang , Wei-Ren Chen

Machine-learned coarse-grained (CG) models have the potential for simulating large molecular complexes beyond what is possible with atomistic molecular dynamics. However, training accurate CG models remains a challenge. A widely used…