Large-Scale FMO-MP2 Calculations of the Spike Protein Droplet Model.

The spike protein of SARS-CoV-2 is a challenging target for theoretical approaches. Here we report a benchmark calculation of the spike protein droplet model by the fragment molecular orbital (FMO) at the second-order Møller-Plesset perturbation (MP2) level on the supercomputer Fugaku. One hundred structure samples from molecular dynamics (MD) simulations were used for both the closed and open forms of this protein (PDB IDs 6XLU and 6XM0 respectively).

Real-time simultaneous visualization of lactate and proton dynamics using a 6-μm-pitch CMOS multichemical image sensor.

Multi-analyte detection and imaging of extracellular chemical signaling molecules are crucial for understanding brain function and molecular pathology. In this work, we present a 6-μm-pitch, CMOS-based multichemical image sensor that enables the simultaneous visualization and spatiotemporal multimodal analysis of the lactate and proton (H) dynamics without any labeling. Using semiconductor lithography, gold electrode patterns functioning as lactate-sensing regions were formed on a potentiometric sensor array.

Towards tailoring hydrophobic interaction with uranyl(VI) oxygen for C-H activation.

Bovine serum albumin (BSA) has a uranyl(VI) binding hotspot where uranium is tightly bound by three carboxylates. Uranyl oxygen is "soaked" into the hydrophobic core of BSA. Isopropyl hydrogen of Val is trapped near UO and upon photoexcitation, C-H bond cleavage is initiated.

Enhancement of energy decomposition analysis in fragment molecular orbital calculations.

Energy decomposition analysis is one of the most attractive features of fragment molecular orbital (FMO) calculations from the point of view of practical applications. Here we report some enhancements for PIEDA in the ABINIT-MP program. One is a separation of the dispersion-type stabilization from the electron correlation energy, traditionally referred to as the "dispersion interaction" (DI).

Regression analysis for predicting the elasticity of liquid crystal elastomers.

It is highly desirable but difficult to understand how microscopic molecular details influence the macroscopic material properties, especially for soft materials with complex molecular architectures. In this study we focus on liquid crystal elastomers (LCEs) and aim at identifying the design variables of their molecular architectures that govern their macroscopic deformations. We apply the regression analysis using machine learning (ML) to a database containing the results of coarse grained molecular dynamics simulations of LCEs with various molecular architectures.

Screening toward the Development of Fingerprints of Atomic Environments Using Bond-Orientational Order Parameters.

A combination of atomic numbers and bond-orientational order parameters is considered a candidate for a simple representation that involves information on both the atomic species and their positional relation. The 504 candidates are applied as the fingerprint of the molecules stored in QM9, a data set of computed geometric, energetic, electronic, and thermodynamic properties for 133 885 stable small organic molecules made up of carbon, hydrogen, oxygen, nitrogen, and fluorine atoms. To screen the fingerprints, a regression analysis of the atomic charges given by Open Babel was performed by supervised machine learning.

CMOS-Based Redox-Type Label-Free ATP Image Sensor for In Vitro Sensitive Imaging of Extracellular ATP.

Adenosine 5'-triphosphate (ATP) plays a crucial role as an extracellular signaling molecule in the central nervous system and is closely related to various nerve diseases. Therefore, label-free imaging of extracellular ATP dynamics and spatiotemporal analysis is crucial for understanding brain function. To decrease the limit of detection (LOD) of imaging extracellular ATP, we fabricated a redox-type label-free ATP image sensor by immobilizing glycerol-kinase (GK), L-α-glycerophosphate oxidase (LGOx), and horseradish peroxidase (HRP) enzymes in a polymer film on a gold electrode-modified potentiometric sensor array with a 37.

Redox Sensor Array with 23.5-μm Resolution for Real-Time Imaging of Hydrogen Peroxide and Glutamate Based on Charge-Transfer-Type Potentiometric Sensor.

Towards clarifying the spatio-temporal neurotransmitter distribution, potentiometric redox sensor arrays with 23.5-µm resolution were fabricated. The sensor array based on a charge-transfer-type potentiometric sensor comprises 128×128 pixels with gold electrodes deposited on the surface of pixels.

Mining of Effective Local Order Parameters to Classify Ice Polymorphs.

Order parameters make it possible to quantify the degree of structural ordering in a material and thus to apply as the reaction coordinates during the free-energy analysis of phase or structure transitions. Furthermore, order parameters are useful in determining the local structures of molecular groups during transition stages. However, identifying or developing local order parameters (LOPs) that are sensitive for specific materials and phases is a non-trivial task.

Searching for local order parameters to classify water structures at triple points.

The diversity of ice polymorphs is of interest in condensed-matter physics, engineering, astronomy, and biosphere and climate studies. In particular, their triple points are critical to elucidate the formation of each phase and transitions among phases. However, an approach to distinguish their molecular structures is lacking.

Searching local order parameters to classify water structures of ice Ih, Ic, and liquid.

Identifying molecular structures of water and ice helps reveal the chemical nature of liquid and solid water. Real-space geometrical information on molecular systems can be precisely obtained from molecular simulations, but classifying the resulting structure is a non-trivial task. Order parameters are ordinarily introduced to effectively distinguish different structures.

Mining of effective local order parameters for classifying crystal structures: A machine learning study.

Determining local structures of molecular systems helps the scientific and technological understanding of the function of materials. Molecular simulations provide microscopic information on molecular systems, but analyzing the resulting local structures is a non-trivial task. Many kinds of order parameters have been developed for detecting such local structures.

Stabilization Mechanism for a Nonfibrillar Amyloid β Oligomer Based on Formation of a Hydrophobic Core Determined by Dissipative Particle Dynamics.

Neurotoxicity caused by nonfibrillar amyloid β (Aβ) oligomers in the brain is suggested to be associated with the onset of Alzheimer's disease (AD). Elucidating the structural features of Aβ oligomers is critical for promoting drug discovery research for AD. One of the Aβ oligomers, known as Aβ*56, is a dodecamer that impairs memory when injected into healthy rats, suggesting that Aβ*56 may contribute to cognitive deficits in AD patients.

Machine learning-aided analysis for complex local structure of liquid crystal polymers.

Elucidation of mesoscopic structures of molecular systems is of considerable scientific and technological interest for the development and optimization of advanced materials. Molecular dynamics simulations are a promising means of revealing macroscopic physical properties of materials from a microscopic viewpoint, but analysis of the resulting complex mesoscopic structures from microscopic information is a non-trivial and challenging task. In this study, a Machine Learning-aided Local Structure Analyzer (ML-LSA) is developed to classify the complex local mesoscopic structures of molecules that have not only simple atomistic group units but also rigid anisotropic functional groups such as mesogens.

Theoretical analyses on water cluster structures in polymer electrolyte membrane by using dissipative particle dynamics simulations with fragment molecular orbital based effective parameters.

The mesoscopic structures of polymer electrolyte membrane (PEM) affect the performances of fuel cells. Nafion® with the Teflon® backbone has been the most widely used of all PEMs, but sulfonated poly-ether ether-ketone (SPEEK) having an aromatic backbone has drawn interest as an alternative to Nafion. In the present study, a series of dissipative particle dynamics (DPD) simulations were performed to compare Nafion and SPEEK.

Fragment Molecular Orbital Based Parametrization Procedure for Mesoscopic Structure Prediction of Polymeric Materials.

In the analyses of miscibility behaviors of macromolecules and polymers, dissipative particle dynamics (DPD) simulations are generally performed. In these simulations, the so-called χ parameters describing the effective interactions among particles are crucial. It has been known that such parameters can be obtained within the classical or empirical force field frameworks.

Approaches for Controlling the Temperature and Pressure Range in Generalized NPT Ensembles.

Isobaric-multithermal and multibaric-isothermal methods are powerful methods for sampling in a wide energy and/or volume space. A finite temperature or pressure is required to study phase diagrams and many properties of many types of systems. However, it is difficult to control the temperature or pressure range because these systems move randomly in energy or volume space.

Theoretically optimum position of the prosthesis in total hip arthroplasty to fulfill the severe range of motion criteria due to neck impingement.

Background: The purpose of this investigation is to determine the optimum position of the prosthesis in total hip arthroplasty for reducing neck impingement using a mathematical formula.

Methods: We calculated the cup inclination, cup anteversion, and stem antetorsion in cases with various sizes of femoral head (28, 32, 36, and 44 mm in diameter) to fulfill severe range of motion criteria: (1) flexion more than 120°, (2) extension more than 30°, (3) internal rotation at 90° flexion more than 60°, and (4) external rotation at neutral more than 40°.

Results: When the areas to fulfill the severe range of motion criteria were compared by femoral head diameter, the area for 28 mm was extremely small relative to those of 32, 36, and 44 mm.