Configurational entropy change is a central constituent of the free energy change in noncovalent interactions between biomolecules. Due to both experimental and computational limitations, however, the impact of individual contributions to configurational entropy change remains underexplored. Here, we develop a novel, fully analytical framework to dissect the configurational entropy change of binding into contributions coming from molecular internal and external degrees of freedom. Importantly, this framework accounts for all coupled and uncoupled contributions in the absence of an external field. We employ our parallel implementation of the maximum information spanning tree algorithm to provide a comprehensive numerical analysis of the importance of the individual contributions to configurational entropy change on an extensive set of molecular dynamics simulations of protein binding processes. Contrary to commonly accepted assumptions, we show that different coupling terms contribute significantly to the overall configurational entropy change. Finally, while the magnitude of individual terms may be largely unpredictable a priori, the total configurational entropy change can be well approximated by rescaling the sum of uncoupled contributions from internal degrees of freedom only, providing support for NMR-based approaches for configurational entropy change estimation.
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http://dx.doi.org/10.1021/acs.jctc.8b01254 | DOI Listing |
Entropy (Basel)
January 2025
Electronics Engineering Department (DEEL), Energy, Power and Integrated Circuits (EPIC), Escola d'Enginyeria de Barcelona Est (EEBE), Universitat Politècnica de Catalunya-BarcelonaTech (UPC), Av. d'Eduard Maristany, 16 Edifici A Campus Besòs, 08029 Barcelona, Spain.
The present study examines the relationship between thermal and configurational entropy in two resistors in parallel and in series. The objective is to introduce entropy in electric circuit analysis by considering the impact of system geometry on energy conversion in the circuit. Thermal entropy is derived from thermodynamics, whereas configurational entropy is derived from network modelling.
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January 2025
College of Computing and Data Science, Nanyang Technological University in Singapore, Singapore 639798, Singapore.
Vertical Federated Learning (VFL) is a promising category of Federated Learning that enables collaborative model training among distributed parties with data privacy protection. Due to its unique training architecture, a key challenge of VFL is high communication cost due to transmitting intermediate results between the Active Party and Passive Parties. Current communication-efficient VFL methods rely on using stale results without meticulous selection, which can impair model accuracy, particularly in noisy data environments.
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December 2024
Independent Researcher, Leesburg, VA 20176, USA.
Vopson and Lepadatu recently proposed the Second Law of Infodynamics. The law states that while the total entropy increases, information entropy declines over time. They state that the law has applications over a wide range of disciplines, but they leave many key questions unanswered.
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December 2024
Departamento de Física, Universidad Técnica Federico Santa María, Av. España 1680, Valparaíso 2390123, Chile.
In this work, we study the magnetocaloric effect (MCE) in a working substance corresponding to a square lattice of spins with possible orientations, known as the "-state clock model". When the -state clock model has Q≥5 possible configurations, it presents the famous Berezinskii-Kosterlitz-Thouless (BKT) phase associated with vortex states. We calculate the thermodynamic quantities using Monte Carlo simulations for even numbers, ranging from Q=2 to Q=8 spin orientations per site in a lattice.
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January 2025
Henan Provincial Key Laboratory of Nanocomposites and Applications, Institute of Nanostructured Functional Materials, Huanghe Science and Technology College, Zhengzhou, Henan 450006, China.
Due to the high configuration entropy, unique atomic arrangement, and electronic structures, high-entropy materials are being actively pursued as bifunctional catalysts for both the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) in rechargeable zinc-air batteries (ZABs). However, a relevant strategy to enhance the catalytic activity of high-entropy materials is still lacking. Herein, a hole doping strategy has been employed to enable the high-entropy perovskite La(CrMnFeCoNi)O to effectively catalyze the ORR and OER.
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