On the steroids extracted from soft corals against the NS3/4A protease of hepatitis C virus.

The Hepatitis C virus (HCV) causes a variety of liver diseases, making it a global health issue that affects millions of people in the world. The NS3/4A protease has been considered a common target for anti-HCV treatments using direct-acting antiviral agents and their derivatives. Of the natural products that have been proposed for novel therapeutic product alternatives, the soft coral compounds are found to contain steroids with various bioactive properties for effective HCV treatments.

Hotspot analysis of COVID-19 infection in Tokyo based on influx patterns.

We analyse the relationship between population influx and the effective reproduction number in the 23 wards of Tokyo during the COVID-19 pandemic to estimate hotspots of infection. We identify some patterns of population influx via factor analysis and estimate specific areas as infection-related hotspots by focusing on influx patterns that are highly correlated with the effective reproduction number. As a result, several influx patterns are assumed to be directly related to the subsequent spread of the infection.

Structural dynamics of a designed peptide pore under an external electric field.

Membrane potential is essential in biological signaling and homeostasis maintained by voltage-sensitive membrane proteins. Molecular dynamics (MD) simulations incorporating membrane potentials have been extensively used to study the structures and functions of ion channels and protein pores. They can also be beneficial in designing and characterizing artificial ion channels and pores, which will guide further amino acid sequence optimization through comparison between the predicted models and experimental data.

Approaching coupled-cluster accuracy for molecular electronic structures with multi-task learning.

Machine learning plays an important role in quantum chemistry, providing fast-to-evaluate predictive models for various properties of molecules; however, most existing machine learning models for molecular electronic properties use density functional theory (DFT) databases as ground truth in training, and their prediction accuracy cannot surpass that of DFT. In this work we developed a unified machine learning method for electronic structures of organic molecules using the gold-standard CCSD(T) calculations as training data. Tested on hydrocarbon molecules, our model outperforms DFT with several widely used hybrid and double-hybrid functionals in terms of both computational cost and prediction accuracy of various quantum chemical properties.

Receptor-independent regulation of Gα13 by alpha-1-antitrypsin C-terminal peptides.

Alpha-1-antitrypsin (AAT), a circulating serine protease inhibitor, is an acute inflammatory response protein with anti-inflammatory functions. The C-terminal peptides of AAT are found in various tissues and have been proposed as putative bioactive peptides with multiple functions, but its mechanism of action remains unclear. We previously reported that a mouse AAT C-terminal peptide of 35 amino acids (mAAT-C) penetrates plasma membrane and associates guanine nucleotide-binding protein subunit alpha 13 (Gα13).

Steering perovskite precursor solutions for multijunction photovoltaics.

Multijunction photovoltaics (PVs) are gaining prominence owing to their superior capability of achieving power conversion efficiencies (PCEs) beyond the radiative limit of single-junction cells, where improving narrow bandgap tin-lead perovskites is critical for thin-film devices. With a focus on understanding the chemistry of tin-lead perovskite precursor solutions, we herein find that Sn(II) species dominate interactions with precursors and additives and uncover the exclusive role of carboxylic acid in regulating solution colloidal properties and film crystallisation, and ammonium in improving film optoelectronic properties. Materials that combine these two function groups, amino acid salts, considerably improve the semiconducting quality and homogeneity of perovskite films, surpassing the effect of the individual functional groups when introduced as part of separate molecules.

Investigating self-supervised image denoising with denaturation.

Self-supervised learning for image denoising problems in the presence of denaturation for noisy data is a crucial approach in machine learning. However, theoretical understanding of the performance of the approach that uses denatured data is lacking. To provide better understanding of the approach, in this paper, we analyze a self-supervised denoising algorithm that uses denatured data in depth through theoretical analysis and numerical experiments.

SciAgents: Automating Scientific Discovery Through Bioinspired Multi-Agent Intelligent Graph Reasoning.

A key challenge in artificial intelligence (AI) is the creation of systems capable of autonomously advancing scientific understanding by exploring novel domains, identifying complex patterns, and uncovering previously unseen connections in vast scientific data. In this work, SciAgents, an approach that leverages three core concepts is presented: (1) large-scale ontological knowledge graphs to organize and interconnect diverse scientific concepts, (2) a suite of large language models (LLMs) and data retrieval tools, and (3) multi-agent systems with in-situ learning capabilities. Applied to biologically inspired materials, SciAgents reveals hidden interdisciplinary relationships that were previously considered unrelated, achieving a scale, precision, and exploratory power that surpasses human research methods.

Reducing Numerical Precision Requirements in Quantum Chemistry Calculations.

The abundant demand for deep learning compute resources has created a renaissance in low-precision hardware. Going forward, it will be essential for simulation software to run on this new generation of machines without sacrificing scientific fidelity. In this paper, we examine the precision requirements of a representative kernel from quantum chemistry calculations: the calculation of the single-particle density matrix from a given mean-field Hamiltonian (i.

Data Science for Integrated Dynamic Structural Biology-the 21st IUPAB Congress session summary commentary.

The session "Data Science for Integrated Dynamic Structural Biology" was a notable success at the joint congress of the 21st IUPAB and the 62nd BSJ (Biophysics Society of Japan). This session included four invited talks and one contributed talk, which together delved into recent advancements in computational methods integrating physics, experimental data, and bioinformatics to study the structure and dynamic properties of molecular assemblies and their interactions.

Synergistic Activation of TLR7 and 8 Mediated by Reduction of Electrostatic Repulsion.

Toll-like receptors (TLRs) play central roles in innate immune defense against infection by binding to microbial molecules. TLR7 and TLR8 are highly homologous sensors with an RNA ligand preference for single-stranded RNA (ssRNA). Recent works reveal that these TLR sense degradation products of RNA at two distinct binding sites, designated 1st site and 2nd site, rather than long ssRNA.

Tandem Mass Spectrometry of Perfluorocarboxylate Anions: Fragmentation Induced by Reactive Species Formed From Microwave Excited Hydrogen and Water Plasmas.

Rationale: Polyfluoroalkyl substances (PFAS) like perfluorooctanoic acid have persistent environmental and physiological effects. This study investigates the degradation of CFCO (n = 1-7) with neutral radical fragmentation under oxygen attachment dissociation (OAD). Unique fragments absent from collision-induced dissociation (CID) are observed.

Similarity between oxygen evolution in photosystem II and oxygen reduction in cytochrome c oxidase via proton coupled electron transfers. A unified view of the oxygenic life from four electron oxidation-reduction reactions.

Basic concepts and theoretical foundations of broken symmetry (BS) and post BS methods for strongly correlated electron systems (SCES) such as electron-transfer (ET) diradical, multi-center polyradicals with spin frustration are described systematically to elucidate structures, bonding and reactivity of the high-valent transition metal oxo bonds in metalloenzymes: photosystem II (PSII) and cytochrome c oxidase (CcO). BS hybrid DFT (HDFT) and DLPNO coupled-cluster (CC) SD(T) computations are performed to elucidate electronic and spin states of CaMnO cluster in the key step for oxygen evolution, namely S [S with Mn(IV) = O + Tyr161-O radical] state of PSII and P [Fe(IV) = O + HO-Cu(II) + Tyr161-O radical] step for oxygen reduction in CcO. The cycle of water oxidation catalyzed by the CaMnO cluster in PSII and the cycle of oxygen reduction catalyzed by the Cu-Fe-Fe-Cu cluster in CcO are examined on the theoretical grounds, elucidating similar concerted and/or stepwise proton transfer coupled electron transfer (PT-ET) processes for the four-electron oxidation in PSII and four-electron reduction in CcO.

Future projections for mammalian whole-brain simulations based on technological trends in related fields.

Large-scale brain simulation allows us to understand the interaction of vast numbers of neurons having nonlinear dynamics to help understand the information processing mechanisms in the brain. The scale of brain simulations continues to rise as computer performance improves exponentially. However, a simulation of the human whole brain has not yet been achieved as of 2024 due to insufficient computational performance and brain measurement data.

Indirect reciprocity under opinion synchronization.

Indirect reciprocity is a key explanation for the exceptional magnitude of cooperation among humans. This literature suggests that a large proportion of human cooperation is driven by social norms and individuals' incentives to maintain a good reputation. This intuition has been formalized with two types of models.

Rotary mechanism of the prokaryotic V motor driven by proton motive force.

ATP synthases play a crucial role in energy production by utilizing the proton motive force (pmf) across the membrane to rotate their membrane-embedded rotor c-ring, and thus driving ATP synthesis in the hydrophilic catalytic hexamer. However, the mechanism of how pmf converts into c-ring rotation remains unclear. This study presents a 2.

Allosteric changes in the conformational landscape of Src kinase upon substrate binding.

Precise regulation of protein kinase activity is crucial in cell functions, and its loss is implicated in various diseases. The kinase activity is regulated by interconverting active and inactive states in the conformational landscape. However, how protein kinases switch conformations in response to different signals such as the binding at distinct sites remains incompletely understood.

Enhancing data standards to advance translation in spinal cord injury.

Data standards are available for spinal cord injury (SCI). The International SCI Data Sets were created in 2002 and there are currently 27 freely available. In 2014 the National Institute of Neurological Disorders and Stroke developed clinical common data elements to promote clinical data sharing in SCI.

Range-dynamical low-rank split-step Fourier method for the parabolic wave equation.

Numerical solutions to the parabolic wave equation are plagued by the curse of dimensionality coupled with the Nyquist criterion. As a remedy, a new range-dynamical low-rank split-step Fourier method is developed. The integration scheme scales sub-linearly with the number of classical degrees of freedom in the transverse directions.

Nuclear Quantum Effects Have a Significant Impact on UV/Vis Absorption Spectra of Chromophores in Water.

Despite the broadly acknowledged importance of solvation effects on measured UV/Vis spectra in the context of solvatochromism or chemical reactions in solution, it is still an open challenge to calculate UV/Vis spectra with predictive accuracy. This is particularly true when it comes to the impact of nuclear quantum effects on these experimental observables. In the present work, we calculate the UV/Vis absorption spectrum of indole in aqueous solution with a combination of a correlated wavefunction method for computing electronic excitation energies and enhanced path integral simulations for rigorous sampling of nuclear configurations including the quantum effects in solution.

RadicalPy: A Tool for Spin Dynamics Simulations.

Radical pairs (electron-hole pairs, polaron pairs) are transient reaction intermediates that are found and exploited in all areas of science, from the hard realm of physics in the form of organic semiconductors, spintronics, quantum computing, and solar cells to the soft domain of chemistry and biology under the guise of chemical reactions in solution, biomimetic systems, and quantum biology. Quantitative analysis of radical pair phenomena has historically been successful by a few select groups. With this in mind, we present an intuitive open-source framework in the Python programming language that provides classical, semiclassical, and quantum simulation methodologies.

Structural basis for hepatitis B virus restriction by a viral receptor homologue.

Macaque restricts hepatitis B virus (HBV) infection because its receptor homologue, NTCP (mNTCP), cannot bind preS1 on viral surface. To reveal how mNTCP loses the viral receptor function, we here solve the cryo-electron microscopy structure of mNTCP. Superposing on the human NTCP (hNTCP)-preS1 complex structure shows that Arg158 of mNTCP causes steric clash to prevent preS1 from embedding onto the bile acid tunnel of NTCP.

Integrated radiation air dose rate maps over the 80 km radius of the Fukushima Daiichi Nuclear Power Plant and the entire Fukushima Prefecture during 2011-2022.

In this study, we created integrated radiation air dose rate maps in the Fukushima region during 2011-2022 using airborne, car-borne, and walk surveys and fixed-location measurements. We applied a Bayesian geostatistical method to the 80 km radius of the Fukushima Daiichi Nuclear Power Plant and the entire Fukushima Prefecture while considering the history of the evacuation zone lifting in Fukushima. The integrated maps in this study fixed the bias to underestimate the air dose rates in forest areas and created integrated maps with a wider area and time series than previous studies.