Large-scale domain dynamics in proteins are found when flexible linkers or hinges connect domains. The related conformational changes are often related to the function of the protein,for example by arranging the active center after substrate binding or allowing transport and release of products. The adaptation of a specific active structure is referred to as ‘induced fit’ and is challenged by models such as ‘conformational sampling’. Newer models about protein unction include some flexibility within the protein structure or even internal dynamics of the protein. As larger domains contribute to the configurational changes, the timescale of the involved motions is slowed down. The role of slow domain dynamics is being increasingly recognized as essential to understanding the function of proteins. Neutron spin echospectroscopy (NSE) is a technique that is able to access the related timescales from 0.1 up to several hundred nanoseconds and simultaneously covers the length scale relevant for protein domain movements of several nanometers distance between domains. Here we focus on these large-scale domain fluctuations and show how the structure and dynamics of proteins can be assessed by small-angle neutron scattering and NSE.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1088/0953-8984/26/50/503103 | DOI Listing |
Phys Rev Lett
December 2024
Xi'an Jiaotong University, School of Microelectronics & State Key Laboratory for Mechanical Behavior of Materials, Xi'an 710049, China.
The bismuth monolayer has recently been experimentally identified as a novel platform for the investigation of two-dimensional single-element ferroelectric system. Here, we model the potential energy surface of a bismuth monolayer by employing a message-passing neural network and achieve an error smaller than 1.2 meV per atom.
View Article and Find Full Text PDFChem Sci
January 2025
Department of Chemical and Biological Physics, Weizmann Institute of Science Rehovot 761001 Israel
Proteins often harness extensive motions of domains and subunits to promote their function. Deciphering how these movements impact activity is key for understanding life's molecular machinery. The enzyme adenylate kinase is an intriguing example for this relationship; it ensures efficient catalysis by large-scale domain motions that lead to the enclosure of the bound substrates ATP and AMP.
View Article and Find Full Text PDFPlast Surg (Oakv)
February 2025
Division of Plastic and Reconstructive Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Patient expectations have been shown to influence postoperative outcomes across surgical specialties. However, the impact of expectations in breast reconstruction is not well understood. The purpose of this project is to perform the first large-scale analysis and classification of BREAST-Q Expectations responses in patients undergoing implant-based reconstruction.
View Article and Find Full Text PDFTraditional numerical reconstruction methods in digital holography (DH) are faced with problems such as inaccurate and time-consuming unwrapping or the need to capture multiple holograms with different diffraction distances. In recent years, deep learning, believed to be a new and effective optimization tool, has been widely used in digital holography. However, most supervised deep learning methods require large-scale paired data, and their preparation is time-consuming and laborious.
View Article and Find Full Text PDFCommun Eng
January 2025
School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China.
Large-scale optimal design problems involving nonlinear differential equations are widely applied in modeling such as craft manufacturing, chemical engineering and energy engineering. Herein we propose a fast and flexible holomorphic embedding-based method to solve nonlinear differential equations quickly, and further apply it to handle the industrial application of reverse osmosis desalination. Without solving nonlinear differential equations at each discrete point by a traditional small-step iteration approach, the proposed method determines the solution through an approximation function or approximant within segmented computational domain independently.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!