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Electrodeposition is a fundamental process in electrochemistry, and has applications in numerous industries, such as corrosion protection, decorative finishing, energy storage, catalysis, and electronics. While there is a long history of…

Materials Science · Physics 2025-06-02 Shayantan Chaudhuri , Reinhard J. Maurer

Protein engineering seeks to identify protein sequences with optimized properties. When guided by machine learning, protein sequence generation methods can draw on prior knowledge and experimental efforts to improve this process. In this…

Quantitative Methods · Quantitative Biology 2021-05-28 Zachary Wu , Kadina E. Johnston , Frances H. Arnold , Kevin K. Yang

Protein structure prediction models are now capable of generating accurate 3D structural hypotheses from sequence alone. However, they routinely fail to capture the conformational diversity of dynamic biomolecular complexes, often requiring…

Machine Learning · Computer Science 2025-12-02 Rishwanth Raghu , Axel Levy , Gordon Wetzstein , Ellen D. Zhong

An all-atom model of proteins is used to show that the same sequence of amino acids can have many alternative structures, that are very distant from, and that can be as stable as, the corresponding native structure. Such alternative…

Biological Physics · Physics 2008-02-11 Leonor Cruzeiro

We introduce a new model of proteins, which extends and enhances the traditional graphical representation by associating a combinatorial object called a fatgraph to any protein based upon its intrinsic geometry. Fatgraphs can easily be…

Biomolecules · Quantitative Biology 2009-05-30 R. C. Penner , Michael Knudsen , Carsten Wiuf , Joergen Ellegaard Andersen

As protein informatics advances rapidly, the demand for enhanced predictive accuracy, structural analysis, and functional understanding has intensified. Transformer models, as powerful deep learning architectures, have demonstrated…

Machine Learning · Computer Science 2025-05-28 Xiaowen Ling , Zhiqiang Li , Yanbin Wang , Zhuhong You

Using techniques borrowed from statistical physics and neural networks, we determine the parameters, associated with a scoring function, that are chosen optimally to ensure complete success in threading tests in a training set of proteins.…

Soft Condensed Matter · Physics 2009-11-07 Iksoo Chang , Marek Cieplak , Ruxandra I. Dima , Amos Maritan , Jayanth R. Banavar

In this work we consider the advantages and challenges of using free-standing two-dimensional electron gases (2DEG) as active components in atom chips for manipulating ultracold ensembles of alkali atoms. We calculate trapping parameters…

Quantum Gases · Physics 2018-01-26 G. A. Sinuco-Leon , Peter Krueger , T. M. Fromhold

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…

Soft Condensed Matter · Physics 2023-06-21 Jayanth R. Banavar , Achille Giacometti , Trinh X. Hoang , Amos Maritan , Tatjana Škrbić

Proteinoids -- thermal proteins -- are produced by heating amino acids to their melting point and initiation of polymerisation to produce polymeric chains. Proteinoids swell in aqueous solution into hollow microspheres. The proteinoid…

Emerging Technologies · Computer Science 2021-06-03 Andrew Adamatzky

Denoising diffusion models have shown great potential in multiple research areas. Existing diffusion-based generative methods on de novo 3D molecule generation face two major challenges. Since majority heavy atoms in molecules allow…

Machine Learning · Computer Science 2024-04-23 Can Xu , Haosen Wang , Weigang Wang , Pengfei Zheng , Hongyang Chen

Molecular Dynamics (MD) simulations are fundamental computational tools for the study of proteins and their free energy landscapes. However, sampling protein conformational changes through MD simulations is challenging due to the relatively…

Biomolecules · Quantitative Biology 2023-07-20 Diego E. Kleiman , Hassan Nadeem , Diwakar Shukla

Interactions between biomolecules, electrons and protons are essential to many fundamental processes sustaining life. It is therefore of interest to build mathematical models of these bioelectrical processes not only to enhance…

Molecular Networks · Quantitative Biology 2020-12-08 Peter J. Gawthrop , Michael Pan

We report a theoretical/computational approach for modeling the current-voltage characteristics of sensing proteins. The modeling is applied to a couple of transmembrane proteins, bacteriorhodopsin and proteorhodopsin, sensitive to visible…

Biological Physics · Physics 2014-02-04 E Alfinito , J Pousset , L Reggiani

Proteins are macromolecules that mediate a significant fraction of the cellular processes that underlie life. An important task in bioengineering is designing proteins with specific 3D structures and chemical properties which enable…

Quantitative Methods · Quantitative Biology 2022-05-31 Namrata Anand , Tudor Achim

Introduced more than fifty years ago, dynamic light scattering is routinely used to determine the size distribution of colloidal suspensions, as well as of macromolecules in solution, such as proteins, nucleic acids, and their complexes.…

Objective: Bioimpedance measurements are mostly performed utilizing gel electrodes to decrease the occurring electrode-skin impedance. Since in many measurement environments this kind of electrode is not appropriate, the usability of dry…

Medical Physics · Physics 2019-10-14 Roman Kusche , Steffen Kaufmann , Martin Ryschka

Imaging single proteins has been a long-standing ambition for advancing various fields in natural science, as for instance structural biology, biophysics and molecular nanotechnology. In particular, revealing the distinct conformations of…

Electronic energy transfer in photosynthesis occurs over a range of time scales and under a variety of intermolecular coupling conditions. Recent work has shown that electronic coupling between chromophores can lead to coherent oscillations…

Despite the significant increase in computational power, molecular modeling of protein structure using classical all-atom approaches remains inefficient, at least for most of the protein targets in the focus of biomedical research. Perhaps…

Biomolecules · Quantitative Biology 2016-11-01 Sebastian Kmiecik , Andrzej Kolinski