An Empirical Biasing Force Constant to Minimize Overfitting in Cryo-EM Flexible Fitting Refinement.

Reliable modeling of protein structures from a cryo-EM density map is one of the central issues in structural biology. Typically, the constructed model is refined using a flexible fitting method combined with molecular dynamics, where a biasing potential is introduced to guide the protein structure toward the density map. However, the appropriate force constant for the biasing potential is generally unknown a priori.

Multi-horizon prediction of tropical cyclone intensity and its interpretability with temporal fusion transformer.

Predicting tropical cyclone (TC) intensity is challenging, involving numerous variables and uncertainty, especially for TC with rapid intensification (RI). One of the frequently used operational methods for such a case relies on statistical-dynamical models subjected to several limitations stemming from linear regression approximation to a complex TC system. This study proposes a new approach using a Temporal Fusion Transformer (TFT) to overcome the limitations attributed to the conventional models.

Non-collinear ferroelectric H2O ice VIII.

We present a non-collinear ferroelectric phase of ice VIII (space group Iba2). This non-collinear ferroelectric phase should be an important base together with the anti-ferroelectric (I41/amd) and the ferroelectric (P42nm) ices to describe the structure of disordered dense H2O ice (ice VII). The enthalpy of Iba2 is slightly larger than that of I41/amd and slightly smaller than that of P42nm (by < 1 mRy/molecule).

The distortion-push mechanism for the γ subunit rotation in F-ATPase.

F-ATPase comprises the stator ring consisting of αβ subunits and the rotor γ subunit. The γ subunit rotation mechanism has been extensively investigated by biochemical analyses, structural studies, single-molecule measurements, and computational studies. Recent cryoelectron microscopy (cryo-EM) structures of F-ATPase from the thermophilic bacterium PS3 (TF) provide us with further possibilities for a better understanding of the γ-rotation mechanisms.

A dilemma study of the traffic flow system emerged due to the lane-change by follower's tailgating effect.

In this study, an artificial traffic system, which is generated on a computer by utilizing the computational technique, has been developed by establishing brilliant lane-changing criteria for the Cellular Automata (CA) traffic model to figure out adequate strategies for cooperative driving that can be implemented in actual traffic systems for optimum use of existing road facilities. We investigate the flow efficiency and social dilemma, which embody the tension between the demanded road facility and the existing road facility, that emerged due to the defector drivers in a traffic flow system, who are highly aggressive in driving and impose threatening/pushing effects on their preceding while they are tailgating. The evolutionary game theory, which is one of the most efficient tools in the decision-making process, has been utilized to identify the Social Efficiency Deficit (SED), which means the dilemma strength of those games.

Structural Analysis and Molecular Dynamics Simulations of Urease From Ureaplasma parvum.

Ureaplasma is one of the smallest pathogenic bacteria, generating approximately 95% of its adenosine triphosphate (ATP) solely through urease. Studies on Ureaplasma parvum, a species of Ureaplasma, have confirmed that adding urease inhibitors inhibits bacterial growth. The K and V of the urease-mediated reaction were estimated to be 4.

Conversion of an agonistic anti-TNFR2 biparatopic antibody into an antagonist by insertion of peptide linkers into the hinge region.

Biparatopic antibodies (BpAbs) bind two different antigen epitopes to form characteristic immunocomplexes. Many BpAbs have been developed for enhanced crosslinking to induce signal transduction or cell internalization, whereas few have been reported with smaller immunocomplexes to suppress unwanted signaling. Here, we developed a strategy to induce 1:1 immunocomplex formation to maximize antagonistic function.

F-DATA: A Fugaku Workload Dataset for Job-centric Predictive Modelling in HPC Systems.

In the last decades, High Performance Computing (HPC) systems have accelerated scientific discoveries and innovations across different domains, from epidemic studies to climate science. For sustainable development of HPC systems, it is fundamental to address their environmental impact regarding carbon footprint emission and energy requirement, while ensuring high system throughput. Analyzing and predicting HPC job execution characteristics is instrumental in developing workload management strategies to simultaneously optimize the system throughput and minimize the environmental impact.

Exploring Binding Sites on Proteins for Function Prediction Using the PoSSuM Databases.

Protein function is strongly associated with molecules with which it can interact. Using information on the accumulated complex structures of proteins and their ligands is expected to be useful for the prediction of biological functions and for drug discovery and development. To take advantage of these opportunities, we have constructed and released the PoSSuM database, with compiled similarity search results for known and putative binding sites, based on three-dimensional structures of proteins.

In Silico Prediction and Selection of Exon-Skipping Antisense Oligonucleotide Sequences Using eSkip-Finder.

In the early drug development using antisense oligonucleotides (ASOs) for exon-skipping treatment, researchers identify a region with high exon-skipping efficacy for a specific target exon, through experimental screening of ASOs. To streamline this process and reduce experimental effort, various in silico tools, including those for RNA structure modeling and prediction of skipping efficacy, have been developed. Among these tools, eSkip-Finder, a web-based server, has been developed to enhance the prediction capability of in silico skipping efficacy.

Effective deep learning aided vehicle classification approach using Seismic Data.

Intelligent transportation systems (ITSs) significantly enhance traffic safety and management globally. A critical component of these systems is vehicle classification (VC), which supports vital applications such as congestion control, traffic monitoring, accident avoidance, etc. Traditional classification algorithms rely heavily on visual or sensor-based data (e.

Assisting calculation of vibrational circular dichroism spectra by molecular tailoring approach.

Theoretical investigation of the vibrational circular dichroism (VCD) spectrum requires computationally demanding construction of Hessian matrix elements along with atomic polar- and atomic axial-tensors. The fragmentation-based method, molecular tailoring approach (MTA) [Sahu et al., Acc.

Chemistry beyond the scale of exact diagonalization on a quantum-centric supercomputer.

A universal quantum computer can simulate diverse quantum systems, with electronic structure for chemistry offering challenging problems for practical use cases around the hundred-qubit mark. Although current quantum processors have reached this size, deep circuits and a large number of measurements lead to prohibitive runtimes for quantum computers in isolation. Here, we demonstrate the use of classical distributed computing to offload all but an intrinsically quantum component of a workflow for electronic structure simulations.

Theoretical Study of 1s, 2s, and 2p Core Electron Binding Energies of Third-Period Elements Calculated by the ΔSCF Method, Koopmans' Theorem, and Slater's Transition State Theory within the Framework of Hartree-Fock and Kohn-Sham Theory.

The binding energies (BEs) of the 1s, 2s, and 2p core electrons of third-period elements were calculated using the ΔSCF method, Koopmans' theorem, and Slater's transition state theory (STS), within the frameworks of Hartree-Fock (HF) and Kohn-Sham (KS) theory, employing B3LYP and LC2gau-core-BOP (LC2gau) functionals. The total self-consistent field (SCF) energy difference (ΔSCF) between neutral and cationic states was obtained by solving the SCF equations with fractional occupation numbers. Energy functionals were plotted as a function of continuously varying occupation numbers, and the validity of Koopmans' theorem and STS theory was assessed by analyzing the derivative of the energy functional with respect to occupation number.

Self-Supervised WiFi-Based Identity Recognition in Multi-User Smart Environments.

The deployment of autonomous AI agents in smart environments has accelerated the need for accurate and privacy-preserving human identification. Traditional vision-based solutions, while effective in capturing spatial and contextual information, often face challenges related to high deployment costs, privacy concerns, and susceptibility to environmental variations. To address these limitations, we propose , a novel AI-driven human identification system that leverages WiFi-based wireless sensing and contrastive learning techniques.

Nonlinear Optical Response in Kagome Lattice with Inversion Symmetry Breaking.

The kagome lattice is a fundamental model structure in condensed matter physics and materials science featuring symmetry-protected flat bands, saddle points, and Dirac points. This structure has emerged as an ideal platform for exploring various quantum physics. By combining effective model analysis and first-principles calculations, we propose that the synergy among inversion symmetry breaking, flat bands, and saddle point-related van Hove singularities within the kagome lattice holds significant potential for generating the strong second-order nonlinear optical response.

ColBuilder: flexible structure generation of crosslinked collagen fibrils.

Motivation: Collagen fibrils are fundamental building blocks of connective tissues, yet generating accurate molecular models of their structure remains challenging due to their hierarchical organization and complex crosslinking patterns.

Results: ColBuilder has been developed to automate the generation of atomistic models of crosslinked collagen fibrils and facilitate the setup of molecular simulations. The tool integrates homology modeling, higher order structure generation and optimization to build complete fibril structures with precise control over sequence composition, crosslinking patterns, and dimensions.

Validation of Long-Range-Corrected LC2gau Functional for Koopmans' Prediction of Core and Valence Ionization Energies with Diverse Data.

Koopmans' theorem, based on Kohn-Sham (KS) orbital energies of current approximate functionals, does not predict well the ionization energies of 1s, 2s, and 2p core electrons in third-period elements due to the self-interaction errors (SIEs). To address this limitation, the LC2gau functional is developed, which we have validated in the present study. With a fixed range-separation parameter (μ) of 0.

Peripheral blood expression impacts mutation penetrance and clinical severity in moyamoya disease.

Background: The p.R4810K founder mutation in the gene confers susceptibility to moyamoya disease (MMD) and non-MMD intracranial artery disease. However, penetrance is incomplete, and the underlying molecular mechanism remains unknown.

Heterogeneous condensates of transcription factors in embryonic stem cells: Molecular simulations.

Biomolecular condensates formed via liquid-liquid phase separation are ubiquitous in cells, especially in the nucleus. While condensates containing one or two kinds of biomolecules have been relatively well characterized, those with more heterogeneous biomolecular components and interactions between biomolecules inside are largely unknown. This study used residue-resolution molecular dynamics simulations to investigate heterogeneous protein assemblies that include four master transcription factors in mammalian embryonic stem cells: Oct4, Sox2, Klf4, and Nanog.

Light and Strange Vector Resonances from Lattice QCD at Physical Quark Masses.

We present the first ab initio calculation at physical quark masses of scattering amplitudes describing the lightest pseudoscalar mesons interacting via the strong force in the vector channel. Using lattice quantum chromodynamics, we postdict the defining parameters for two short-lived resonances, the ρ(770) and K^{*}(892), which manifest as complex energy poles in ππ and Kπ scattering amplitudes, respectively. The calculation proceeds by first computing the finite-volume energy spectrum of the two-hadron systems and then determining the amplitudes from the energies using the Lüscher formalism.

High-performance QM/MM Enhanced Sampling Molecular Dynamics Simulations with GENESIS SPDYN and QSimulate-QM.

A new module for quantum mechanical/molecular mechanical (QM/MM) calculations is implemented in a molecular dynamics (MD) program, SPDYN in GENESIS, interfaced with an electronic structure program, QSimulate-QM. The periodic boundary condition (PBC) in QM/MM simulation is incorporated via QM calculation in real space with duplicated MM charges and particle mesh Ewald (PME) calculation with QM and MM charges. A highly optimized code is implemented in QSimulate-QM, particularly for the density functional tight-binding (DFTB) method, where the interaction between the QM and MM regions is computed utilizing multipole expansions.

Precision spatiotemporal analysis of large-scale compound-protein interactions through molecular dynamics simulation.

Biological systems are composed of and regulated by intricate and diverse biomolecular interactions. Experimental and computational approaches have been developed to elucidate the mechanisms of these interactions; however, owing to cost, time, and accuracy issues, large-scale spatiotemporal analyses of molecular pairs remain challenging. Thus, the molecular recognition mechanisms underlying these diverse interactions remain unclear.

Rational Design Principles for α-Helical Peptide Barrels with Dynamic Conductive Channels.

Despite advances in peptide and protein design, the rational design of membrane-spanning peptides that form conducting channels remains challenging due to our imperfect understanding of the sequence-to-structure relationships that drive membrane insertion, assembly, and conductance. Here, we describe the design and computational and experimental characterization of a series of coiled coil-based peptides that form transmembrane α-helical barrels with conductive channels. Through a combination of rational and computational design, we obtain barrels with 5 to 7 helices, as characterized in detergent micelles.