significant challenge in applying machine learning to computational chemistry, particularly considering the growing complexity of contemporary machine learning models, is the scarcity of available experimental data. To address this issue, we introduce an approach that derives molecular features from an intricate neural network-based model and applies them to a simpler conventional machine learning model that is robust to overfitting. This method can be applied to predict various properties of a liquid system, including viscosity or surface tension, based on molecular features drawn from the ab initio calculated free energy of solvation. Furthermore, we propose a modified kernel model that includes Arrhenius temperature dependence to incorporate theoretical principles and diminish extreme nonlinearity in the model. The modified kernel model demonstrated significant improvements in certain scenarios and possible extensions to various theoretical concepts of molecular systems.

The development of artificial metalloenzymes (ArMs) aims to expand the capabilities of enzymatic catalysis, most notably towards new reaction mechanisms. Frequently, ArMs harness metal cofactors that are not naturally found in enzymes and embed these in specifically selected or designed protein scaffolds. ArMs have been developed for a wide range of natural and non-natural reactions, underscoring their potential to revolutionize fields such as biocatalysis or metabolic engineering. At the same time, replicating the catalytic prowess of natural enzymes is a highly challenging task, and several limitations need to be overcome to make ArM catalysis widely applicable. In this Primer, we introduce the state of the art in designing and engineering ArMs, describing best practices and important examples and achievements. Moreover, we consider potential applications of ArMs, as well as outstanding challenges, and discuss how these may be addressed in the coming years.

We investigate dynamical phase transitions in two representative kinetically constrained models: the 1D Fredrickson–Andersen and East Models. A recently developed energy-activity double-bias approach utilizing both s and g fields, conjugated with dynamical activity and trajectory energy, is combined with matrix product state (MPS) methods. It is demonstrated that MPS methods facilitate the numerical approximation of large-deviation statistics of dynamics by determining the eigenvalues of tilted dynamical generators under the influence of double-biasing fields. Specifically, by focusing on the g-field, a nearly “half-filled” state at moderate negative g values is identified, indicating the potential existence of an anomalous phase. Additionally, dynamical quantities under various s, g, and T conditions are obtained via tensor networks, showing good qualitative consistency with mean-field results and our previous extensive numerical simulation results obtained by the path sampling method. Our study introduces novel methodologies for examining decoupled dynamical behaviors that, although energetically active, remain dynamically inactive within the system. This approach offers a fresh perspective on the theoretical framework and computational strategies for studying dynamical phase transitions in kinetically constrained systems.

Transient receptor potential (TRP) ion channels have a crucial role as cellular sensors, mediating diverse physical and chemical stimuli. The formation of heteromeric structures expands the functionality of TRP channels; however, their molecular architecture remains largely unknown. Here we present the cryo-electron microscopy structures of the human TRPC1/TRPC4 heteromer in the apo and antagonist-bound states, both consisting of one TRPC1 subunit and three TRPC4 subunits. The heteromer structure reveals a distinct ion-conduction pathway, including an asymmetrically constricted selectivity filter and an asymmetric lower gate, primarily attributed to the incorporation of TRPC1. Through a structure-guided electrophysiological assay, we show that both the selectivity filter and the lower part of the S6 helix participate in deciding overall preference for permeating monovalent cations. Moreover, we reveal that the introduction of one lysine residue of TRPC1 into the tetrameric central cavity is enough to render one of the most important functional consequences of TRPC heteromerization: reduced calcium permeability. Our results establish a framework for addressing the structure–function relationship of the heteromeric TRP channels.

The selection of electrode material is a critical factor that determines the selectivity of electrochemical organic reactions. However, the fundamental principles governing this relationship are still largely unexplored. Herein, we demonstrate a photoelectrocatalytic (PEC) system as a promising reaction platform for the selective radical–radical coupling reaction owing to the inherent charge-transfer properties of photoelectrocatalysis. As a model reaction, the radical trifluoromethylation of arenes is shown on hematite photoanodes without employing molecular catalysts. The PEC platform exhibited superior mono- to bis-trifluoromethylated product selectivity compared to conventional electrochemical methods utilizing conducting anodes. Electrochemical and density functional theory (DFT) computational studies revealed that controlling the kinetics of anodic oxidation of aromatic substrates is essential for increasing reaction selectivity. Only the PEC configuration could generate sufficiently high-energy charge carriers with controlled kinetics due to the generation of photovoltage and charge-carrier recombination, which are characteristic features of semiconductor photoelectrodes. This study opens a novel approach towards selective electrochemical organic reactions through understanding the intrinsic physicochemical properties of semiconducting materials.

The growing demand for flexible, biocompatible, and environmentally friendly power sources for wearable devices has led to an increased interest in alternative technologies. Among them, reverse electrodialysis (RED) stands out as a promising renewable energy technology, harnessing salinity gradients between seawater and river water to generate electricity. Although RED has a high potential as a power source, conventional RED designs face challenges in increasing power density, stability, and versatility particularly when it is miniaturised for portable applications. Owing to its serially stacked structure, RED can only provide very small currents to the external load, as the internal resistance increases proportionally with the number of membranes. Additionally, RED may produce an unstable voltage output because the current cannot bypass blockages or broken circuits through alternative pathways. In this study, we address these challenges by introducing a novel parallel structure, four-way diffusion compact RED (cRED), which enhances the stability while increasing the power density by reducing the total volume. Theoretical properties of various forms of parallel-connected series RED (pRED) and cRED were investigated. cRED can achieve up to twice higher volumetric power density compared to pRED due to its compact structure. Furthermore, cRED exhibits superior voltage stability and current amplification to those of conventional series designs. The advancement enables the utilisation of the miniaturised RED as a power source, preventing waste from conventional batteries where only a small power is required, offering a compact, versatile, and sustainable alternative for renewable energy generation, promising environmentally friendly energy solutions.

Connexin 36 (Cx36) forms interneuronal gap junctions, establishing electrical synapses for rapid synaptic transmission. In disease conditions, inhibiting Cx36 gap junction channels (GJCs) is beneficial, as it prevents abnormal synchronous neuronal firing and apoptotic signal propagation, mitigating seizures and progressive cell death. Here, we present cryo-electron microscopy structures of human Cx36 GJC in complex with known channel inhibitors, such as mefloquine, arachidonic acid, and 1-hexanol. Notably, these inhibitors competitively bind to the binding pocket of the N-terminal helices (NTH), inducing a conformational shift from the pore-lining NTH (PLN) state to the flexible NTH (FN) state. This leads to the obstruction of the channel pore by flat double-layer densities of lipids. These studies elucidate the molecular mechanisms of how Cx36 GJC can be modulated by inhibitors, providing valuable insights into potential therapeutic applications.

Cell–cell interactions orchestrate complex functions in multicellular organisms, forming a regulatory network for diverse biological processes. Their disruption leads to disease states. Recent advancements – including single-cell sequencing and spatial transcriptomics, coupled with powerful bioengineering and molecular tools – have revolutionized our understanding of how cells respond to each other. Notably, spatial transcriptomics allows us to analyze gene expression changes based on cell proximity, offering a unique window into the impact of cell–cell contact. Additionally, computational approaches are being developed to decipher how cell contact governs the symphony of cellular responses. This review explores these cutting-edge approaches, providing valuable insights into deciphering the intricate cellular changes influenced by cell–cell communication.

GPR179, an orphan class C GPCR, is expressed at the dendritic tips of ON-bipolar cells in the retina. It plays a pivotal role in the initial synaptic transmission of visual signals from photoreceptors, and its deficiency is known to be the cause of complete congenital stationary night blindness. Here, we present the cryo-electron microscopy structure of human GPR179. Notably, the transmembrane domain (TMD) of GPR179 forms a homodimer through the TM1/7 interface with a single inter-protomer disulfide bond, adopting a noncanonical dimerization mode. Furthermore, the TMD dimer exhibits architecture well-suited for the highly curved membrane of the dendritic tip and distinct from the flat membrane arrangement observed in other class C GPCR dimers. Our structure reveals unique structural features of GPR179 TMD, setting it apart from other class C GPCRs. These findings provide a foundation for understanding signal transduction through GPR179 in visual processing and offers insights into the underlying causes of ocular diseases.

Nitrogen oxides (NOx) are major environmental pollutants and to neutralize this long-term environmental threat, new catalytic methods are needed. Although there are biological denitrification processes involving four different enzymatic reactions to convert nitrate (NO3−) into dinitrogen (N2), it is unfortunately difficult to apply in industry due to the complexity of the processes. In particular, nitrate is difficult to functionalize because of its chemical stability. Thus, there is no organometallic catalysis to convert nitrate into useful chemicals. Herein, we present a nickel pincer complex that is effective as a bifunctional catalyst to stepwise deoxygenate NO3− by carbonylation and further through C−N coupling. By using this nickel catalysis, nitrate salts can be selectively transformed into various oximes (>20 substrates) with excellent conversion (>90 %). Here, we demonstrate for the first time that the highly inert nitrate ion can be functionalized to produce useful chemicals by a new organonickel catalysis. Our results show that the NOx conversion and utilization (NCU) technology is a successful pathway for environmental restoration coupled with value-added chemical generation.