ResiDEM: Analytical Tool for Isomorphous Difference Electron Density Maps Utilizing Dynamic Residue Identification via Density Clustering.

Time-resolved serial femtosecond crystallography (TR-SFX) of biological molecules captures the time-evolved dynamics of the residual motions across crystal structures, enabling the visualization of structural changes in response to chemical and physical stimuli to elucidate the relationship between the structure and function of the system under study. However, interpretations of residual motions can be complex to deconvolute because of various factors such as the system's size, temporal and spatial complexity, and allosteric behavior away from active sites. Relying solely on electron density map visualization can also pose a challenge in differentiating between useful and irrelevant data.

Metal-ligand delocalization of iron and cobalt porphyrin complexes in aqueous solutions probed by soft X-ray absorption spectroscopy.

Metal-ligand delocalization of metal porphyrin complexes in aqueous solutions was investigated by analyzing the electronic structure of both the metal and ligand sides using soft X-ray absorption spectroscopy (XAS) at the metal L-edges and nitrogen K-edge, respectively. In the N K-edge XAS spectra of the ligands, the energies of the CN π* peaks of cobalt protoporphyrin IX (CoPPIX) are higher than iron protoporphyrin IX (FePPIX). The energy difference between the two lowest peaks in the XAS spectrum of CoPPIX is also larger than that of FePPIX.

Thermal Energy Transport through Nonbonded Native Contacts in Protein.

Within the protein interior, where we observe various types of interactions, nonuniform flow of thermal energy occurs along the polypeptide chain and through nonbonded native contacts, leading to inhomogeneous transport efficiencies from one site to another. The folded native protein serves not merely as thermal transfer medium but, more importantly, as sophisticated molecular nanomachines in cells. Therefore, we are particularly interested in what sort of "communication" is mediated through native contacts in the folded proteins and how such features are quantitatively depicted in terms of local transport coefficients of heat currents.

Insight into the photodegradation of methylisothiazolinone and benzoisothiazolinone in aquatic environments.

Methylisothiazolinone (MIT) and Benzisothiazolinone (BIT) are two widely used non-oxidizing biocides of isothiazolinones. Their production and usage volume have sharply increased since the pandemic of COVID-19, inevitably leading to more release into water environment. However, their photochemical behaviors in water environment are still unclear.

Exploiting the Correlation between the 1s, 2s, and 2p Energies for the Prediction of Core-Level Binding Energies of Si, P, S, and Cl species.

The binding energies (BEs) of the 1s, 2s, and 2p core electrons of third-period elements (Si, P, S, Cl) were calculated using Hartree-Fock (HF) and B3LYP, BH&HLYP, and LC-BOP ΔSCF, and the shifted KS ΔSCF methods. Linear relationships between two BEs were derived and compared with the Auger parameter. The derived lines are essentially parallel, with only the intercepts differing.

New potential selective estrogen receptor modulators in traditional Chinese medicine for treating menopausal syndrome.

Women go through several predictable conditions and symptoms during menopause that are caused by age, changes in sex hormone levels, and other factors. Conventional menopause hormone therapy has raised serious concerns about the increased risks of cancers, blood clots, depression, etc. Selective estrogen receptor modulators (SERMs) that can be both agonists and antagonists of estrogen receptors in a tissue-specific manner are being developed to reduce the health concerns associated with menopause hormone therapy.

Computational evolution of social norms in well-mixed and group-structured populations.

Models of indirect reciprocity study how social norms promote cooperation. In these models, cooperative individuals build up a positive reputation, which in turn helps them in their future interactions. The exact reputational benefits of cooperation depend on the norm in place, which may change over time.

Long-range Corrected Density Functional Theory Including a Two-Gaussian Hartree-Fock Operator for High Accuracy Core-excitation Energy Calculations of Both the Second- and Third-Row Atoms (LC2gau-core-BOP).

In the previous work, LCgau-core-BOP, which includes the short-range interelectronic Gaussian attenuating Hartree-Fock (HF) exchange to the long-range HF exchange, showed high accuracy core-excitation energies from 1s orbitals of the second-row atoms (1s → π*, 1s → σ*, 1s → *, and 1s → Rydberg), but underestimates the core-excitation energies from 1s orbitals of the third-row atoms. To improve this, we added one more Gaussian attenuating HF exchange to LCgau-core-BOP. We named it LC2gau-core-BOP, which achieves a mean absolute error (MAE) of 0.

GENESIS 2.1: High-Performance Molecular Dynamics Software for Enhanced Sampling and Free-Energy Calculations for Atomistic, Coarse-Grained, and Quantum Mechanics/Molecular Mechanics Models.

GENeralized-Ensemble SImulation System (GENESIS) is a molecular dynamics (MD) software developed to simulate the conformational dynamics of a single biomolecule, as well as molecular interactions in large biomolecular assemblies and between multiple biomolecules in cellular environments. To achieve the latter purpose, the earlier versions of GENESIS emphasized high performance in atomistic MD simulations on massively parallel supercomputers, with or without graphics processing units (GPUs). Here, we implemented multiscale MD simulations that include atomistic, coarse-grained, and hybrid quantum mechanics/molecular mechanics (QM/MM) calculations.

Learning QM/MM potential using equivariant multiscale model.

The machine learning (ML) method emerges as an efficient and precise surrogate model for high-level electronic structure theory. Its application has been limited to closed chemical systems without considering external potentials from the surrounding environment. To address this limitation and incorporate the influence of external potentials, polarization effects, and long-range interactions between a chemical system and its environment, the first two terms of the Taylor expansion of an electrostatic operator have been used as extra input to the existing ML model to represent the electrostatic environments.

Decoding the specificity of mA RNA methylation and its implication in cancer therapy.

N6-methyladenosine (mA) is the most abundant endogenous modification in eukaryotic RNAs. It plays important roles in various biological processes and diseases, including cancers. More and more studies have revealed that the deposition of mA is specifically regulated in a context-dependent manner.

Cluster-in-Cluster Approach for Computing MP2-Level Vibrational Infrared Spectra of Large Molecular Clusters.

Constructing the Hessian matrix (HM) for large molecules demands huge computational resources. Here, we report a cluster-in-cluster (CIC) procedure for efficiently evaluating HM and dipole derivatives for large molecular clusters by employing the second-order Møller-Plesset perturbation (MP2) theory. The highlight of the proposal is the separation of the estimations of Hartree-Fock (HF) and post-HF components.

GENESIS CGDYN: large-scale coarse-grained MD simulation with dynamic load balancing for heterogeneous biomolecular systems.

Residue-level coarse-grained (CG) molecular dynamics (MD) simulation is widely used to investigate slow biological processes that involve multiple proteins, nucleic acids, and their complexes. Biomolecules in a large simulation system are distributed non-uniformly, limiting computational efficiency with conventional methods. Here, we develop a hierarchical domain decomposition scheme with dynamic load balancing for heterogeneous biomolecular systems to keep computational efficiency even after drastic changes in particle distribution.

Sorting drug conformers in enzyme active sites: the XTB way.

In the present study, we have used the MEI196 set of interaction energies to investigate low-cost computational chemistry approaches for the calculation of binding between a molecule and its environment. Density functional theory (DFT) methods, when used with the vDZP basis set, yield good agreement with the reference energies. On the other hand, semi-empirical methods are less accurate as expected.

Molecular dynamics in multidimensional space explains how mutations affect the association path of neomycin to a riboswitch.

Riboswitches are messenger RNA (mRNA) fragments binding specific small molecules to regulate gene expression. A synthetic N1 riboswitch, inserted into yeast mRNA controls the translation of a reporter gene in response to neomycin. However, its regulatory activity is sensitive to single-point RNA mutations, even those distant from the neomycin binding site.

LTK mutations responsible for resistance to lorlatinib in non-small cell lung cancer harboring CLIP1-LTK fusion.

The CLIP1-LTK fusion was recently discovered as a novel oncogenic driver in non-small cell lung cancer (NSCLC). Lorlatinib, a third-generation ALK inhibitor, exhibited a dramatic clinical response in a NSCLC patient harboring CLIP1-LTK fusion. However, it is expected that acquired resistance will inevitably develop, particularly by LTK mutations, as observed in NSCLC induced by oncogenic tyrosine kinases treated with corresponding tyrosine kinase inhibitors (TKIs).

Deciphering the Multi-state Conformational Equilibrium of HDM2 in the Regulation of p53 Binding: Perspectives from Molecular Dynamics Simulation and NMR Analysis.

HDM2 negatively regulates the activity of the tumor suppressor p53. Previous NMR studies have shown that apo-HDM2 interconverts between an "open" state in which the N-terminal "lid" is disordered and a "closed" state in which the lid covers the p53-binding site in the core region. Molecular dynamics (MD) simulation studies have been performed to elucidate the conformational dynamics of HDM2, but the direct relevance of the experimental and computational analyses is unclear.

Quantitative analysis of protein dynamics using a deep learning technique combined with experimental cryo-EM density data and MD simulations.

Protein functions associated with biological activity are precisely regulated by both tertiary structure and dynamic behavior. Thus, elucidating the high-resolution structures and quantitative information on in-solution dynamics is essential for understanding the molecular mechanisms. The main experimental approaches for determining tertiary structures include nuclear magnetic resonance (NMR), X-ray crystallography, and cryogenic electron microscopy (cryo-EM).

A new workflow for the effective curation of membrane permeability data from open ADME information.

Membrane permeability is an in vitro parameter that represents the apparent permeability (Papp) of a compound, and is a key absorption, distribution, metabolism, and excretion parameter in drug development. Although the Caco-2 cell lines are the most used cell lines to measure Papp, other cell lines, such as the Madin-Darby Canine Kidney (MDCK), LLC-Pig Kidney 1 (LLC-PK1), and Ralph Russ Canine Kidney (RRCK) cell lines, can also be used to estimate Papp. Therefore, constructing in silico models for Papp estimation using the MDCK, LLC-PK1, and RRCK cell lines requires collecting extensive amounts of in vitro Papp data.

Similarity scores of vibrational spectra reveal the atomistic structure of pentapeptides in multiple basins.

Vibrational spectroscopy combined with theoretical calculations is a powerful tool for analyzing the interaction and conformation of peptides at the atomistic level. Nonetheless, identifying the structure becomes increasingly difficult as the peptide size grows large. One example is acetyl-SIVSF--methylamide, a capped pentapeptide, whose atomistic structure has remained unknown since its first observation [T.

Pseudo-Luciferase Activity of the SARS-CoV-2 Spike Protein for Luciferin.

Enzymatic reactions that involve a luminescent substrate (luciferin) and enzyme (luciferase) from luminous organisms enable a luminescence detection of target proteins and cells with high specificity, albeit that conventional assay design requires a prelabeling of target molecules with luciferase. Here, we report a luciferase-independent luminescence assay in which the target protein directly catalyzes the oxidative luminescence reaction of luciferin. The SARS-CoV-2 antigen (spike) protein catalyzes the light emission of luciferin, whereas no such catalytic function was observed for salivary proteins.

Positivity preserving density matrix minimization at finite temperatures via square root.

We present a Wave Operator Minimization (WOM) method for calculating the Fermi-Dirac density matrix for electronic structure problems at finite temperature while preserving physicality by construction using the wave operator, i.e., the square root of the density matrix.

Feature extraction of particle morphologies of pharmaceutical excipients from scanning electron microscope images using convolutional neural networks.

Scanning electron microscopy (SEM) images are the most widely used tool for evaluating particle morphology; however, quantitative evaluation using SEM images is time-consuming and often neglected. In this study, we aimed to extract features related to particle morphology of pharmaceutical excipients from SEM images using a convolutional neural network (CNN). SEM images of 67 excipients were acquired and used as models.