Pairwise Energy Research Articles

Histidine in Proteins: pH-Dependent Interplay between π-π, Cation-π, and CH-π Interactions.

Histidine (His) stands out as the most versatile natural amino acid due to its side chain's facile propensity to protonate at physiological pH, leading to a transition from aromatic to cationic characteristics and thereby enabling diverse biomolecular interactions. In this study, our objective was to quantify the energetics and geometries of pairwise interactions involving His at varying pH levels. Through quantum chemical calculations, we discovered that His exhibits robust participation in both π-π and cation-π interactions, underscoring its ability to adopt a π or cationic nature, akin to other common residues. Of particular note, we found that the affinity of protonated His for aromatic residues (via cation-π interactions) is greater than the affinity of neutral His for either cationic residues (also via cation-π interactions) or aromatic residues (via π-π interactions). Furthermore, His frequently engages in CH-π interactions, and notably, depending on its protonation state, we found that some instances of hydrogen bonding by His exhibit greater stability than is typical for interamino acid hydrogen bonds. The strength of the pH-dependent pairwise energies of His with aromatic residues is supported by the abundance of pairwise interactions with His of low and high predicted pKa values. Overall, our findings illustrate the contribution of His interactions to protein stability and its potential involvement in conformational changes despite its relatively low abundance in proteins.

Supramolecular architectures in multicomponent crystals of imidazole-based drugs and trithiocyanuric acid.

The structures of three multicomponent crystals formed with imidazole-based drugs, namely metronidazole, ketoconazole and miconazole, in conjunction with trithiocyanuric acid are characterized. Each of the obtained adducts represents a different category of crystalline molecular forms: a cocrystal, a salt and a cocrystal of salt. The structural analysis revealed that in all cases, the N-H...N hydrogen bond is responsible for the formation of acid-base pairs, regardless of whether proton transfer occurs or not, and these molecular pairs are combined to form unique supramolecular motifs by centrosymmetric N-H...S interactions between acid molecules. The complex intermolecular forces acting in characteristic patterns are discussed from the geometric and energetic perspectives, involving Hirshfeld surface analysis, pairwise energy estimation, and natural bond orbital calculations.

Interactions and pattern formation in a macroscopic magnetocapillary SALR system of mermaid cereal

When particles are deposited at a fluid interface they tend to aggregate by capillary attraction to minimize the overall potential energy of the system. In this work, we embed floating millimetric disks with permanent magnets to introduce a competing repulsion effect and study their pattern formation in equilibrium. The pairwise energy landscape of two disks is described by a short-range attraction and long-range repulsion (SALR) interaction potential, previously documented in a number of microscopic condensed matter systems. Such competing interactions enable a variety of pairwise equilibrium states, including the possibility of a local minimum energy corresponding to a finite disk spacing. Two-dimensional (2D) experiments and simulations in confined geometries demonstrate that as the areal packing fraction is increased, the dilute repulsion-dominated lattice state becomes unstable to the spontaneous formation of localized clusters, which eventually merge into a system-spanning striped pattern. Finally, we demonstrate that the equilibrium pattern can be externally manipulated by the application of a supplemental vertical magnetic force that remotely enhances the effective capillary attraction.

Semiclassical approaches to perturbative time-convolution and time-convolutionless quantum master equations for electronic transitions in multistate systems.

Understanding the dynamics of photoinduced processes in complex systems is crucial for the development of advanced energy-conversion materials. In this study, we investigate the nonadiabatic dynamics using time-convolution (TC) and time-convolutionless (TCL) quantum master equations (QMEs) based on treating electronic couplings as perturbation within the framework of multistate harmonic (MSH) models. The MSH model Hamiltonians are mapped from all-atom simulations such that all pairwise reorganization energies are consistently incorporated, leading to a heterogeneous environment that couples to the multiple electronic states differently. Our exploration encompasses the photoinduced charge transfer dynamics in organic photovoltaic carotenoid-porphyrin-C60 triad dissolved in liquid solution and the excitation energy transfer (EET) dynamics in photosynthetic Fenna-Matthews-Olson complexes. By systematically comparing the perturbative TC and TCL QME approaches with exact quantum-mechanical and various semiclassical approximate kernels, we demonstrate their efficacy and accuracy in capturing the essential features of photoinduced dynamics. Our calculations show that TC QMEs generally yield more accurate results than TCL QMEs, especially in EET, although both methods offer versatile approaches adaptable across different systems. In addition, we investigate various semiclassical approximations featuring the Wigner-transformed and classical nuclear densities as well as the governing dynamics during the quantum coherence period, highlighting the trade-off between accuracy and computational cost. This work provides valuable insights into the applicability and performance of TC and TCL QME approaches via the MSH model, offering guidance for realistic applications to condensed-phase systems on the atomistic level.

Structural Analysis of 3,5-Bistrifluoromethylhydrocinnamic Acid

The crystal structure of 3,5-bistrifluoromethylhydrocinnamic acid [systematic name: 3-[3,5-bis(trifluoromethyl)phenyl]propanoic acid], C11H8F6O2, has been determined and described. The structure was subject to the Hirshfeld surface-analysis and CE-B3LYP interaction-energies calculations. The title compound crystallises in the monoclinic P21/c space group with one molecule in the asymmetric unit. The propanoic acid side chain of the studied molecule has a bent conformation. The key supramolecular motif in the crystal structure is a centrosymmetric O–H∙∙∙O hydrogen-bonded dimer (R22(8) in the graph set notation). According to CE-B3LYP, the molecules involved in this motif exhibit the strongest pairwise interaction total energy (Etot = −67.9 kJ/mol). On the other hand, there are seven other interacting molecular pairs with significant Etot values in the range of −17 to −28 kJ/mol. In these, the energy is dominated by the dispersive contribution. A survey of the Cambridge Structural Database revealed that in other 3-phenylpropanoic acid structures, the middle dihedral angle of the propanoic acid side chain is always in the trans conformation. This contrasts the current structure where this dihedral angle is in the gauche conformation. According to the Density Functional Theory calculations in the gas phase (at the B3LYP/aug-cc-pvDZ level), the presence of the two CF3 groups (strong electron-withdrawing character) increases the population of the gauche conformers by a substituent electronic effect, and this may be a minor factor contributing to the appearance of this conformation observed in the solid state.

Multiscale Computational Framework for the Liquid-Liquid Phase Separation of Intrinsically Disordered Proteins.

The reversible assembly of intrinsically disordered proteins (IDPs) to form membraneless organelles (MLOs) is a fundamental process involved in the spatiotemporal regulation in living cells. MLOs formed via liquid-liquid phase separation (LLPS) serve as molecule-enhancing hubs to regulate cell functions. Owing to the complexity and dynamic nature of the protein assembly via a network of weak inter- and intra-molecular interactions, it is challenging to describe and predict the LLPS behavior. We have developed a multiscale computational model for IDPs, using the fused in sarcoma (FUS) protein and its variants as illustrative examples. To simplify the description of protein, FUS is represented as a linear chain of stickers interspaced by spacers, as inspired by the associative polymer theory. Low-complexity aromatic-rich kinked segments (LARKS) available in FUS were identified using LARKSdb and represented as "stickers". The pairwise potential energies of each pair of stickers and their β-sheet-forming propensity were estimated via molecular docking and all atomistic molecular dynamics (AA-MD) simulations. Subsequently, FUS chains were randomly positioned in a cubic lattice as coarse-grained (CG) beads, with the bead assignment based on the Kuhn length estimation of stickers and spacers. Stochastic FUS movements were modeled by Monte Carlo (MC) simulations. In addition to the Metropolis algorithm, discretized pair potential distributions between stickers were considered in the move acceptance criteria. The chosen pair potential represents one of the possible binding energy states, with its probability determined by the frequency of the binding energy distribution histogram. The fluctuations of averaged radial distribution functions (RDFs) in successive MC trial move intervals of equilibrated lattice MC simulations were used to indicate the dynamic nature of assembly/disassembly of the protein chains. This multiscale computational framework provides an economical and efficient way of predicting and describing the LLPS behavior of IDPs.

Connecting microscopic and mesoscopic mechanics in model structural glasses.

We present a novel formalism to characterize elastic heterogeneities in amorphous solids. In particular, we derive high-order strain-energy expansions for pairwise energies under athermal quasistatic dynamics. We then use the presented formalism to study the statistical properties of pairwise expansion coefficients and their link with the statistics of soft, quasilocalized modes, for a wide range of formation histories in both two- and three-dimensional systems. We further exploit the presented framework to access local yield stress maps by performing a non-linear stress-strain expansion within a cavity embedded in a frozen matrix. We show that our "bond micromechanics" compare well with the original "frozen matrix" method, with the caveat of overestimating large stress activations. We additionally show how local yield rules can be used as an input for a scalar elasto-plastic model (EPM) to predict the stress response of materials ranging from ductile to brittle. Finally, we highlight some of the limits of simple mesoscale models in capturing the aging dynamics of post-yielding systems. Intriguingly, we observe subdiffusive and diffusive shear band growths for particle-based simulations and EPMs, respectively.

Pairwise Additivity and Three-Body Contributions for Density Functional Theory-Based Protein-Ligand Interaction Energies.

The prediction of protein-ligand binding energies is crucial in computer-assisted drug design. This property can be calculated in a straightforward fashion as the difference in the energies between a binding site-ligand complex and the separated binding site and ligand. Often, though, there is value in knowing how different amino acid residues in the protein binding site interact with the ligand. In this case, the interaction energy can be calculated as the sum of pairwise energies between each amino acid residue in the binding site and the ligand, and the sum of these energies is often equated with the total interaction energy. The validity of this pairwise additivity approximation can be assessed by experimental evidence, such as double-mutant cycles. In this work, we test the pairwise additivity approximation on the sulfotransferase-l-DOPA complex for 16 density functional theory (DFT) methods with varying degrees of exact (Hartree-Fock) exchange. Several "families" of functionals are studied, including BLYP, B3LYP, and CAM-B3LYP, as well as M06L, M06, and M062X. We also calculate the three-body contributions to interaction energy for the same DFT methods and assess when they are significant. We find that the amount of exact exchange or other nonlocal contributions has a direct influence on how closely the sum of pairwise energies approximates the total interaction energy. We also find that three-body interactions can be significant and that their significance can be predicted with good accuracy.

Electrostatically Mediated Attractive Self-Interactions and Reversible Self-Association of Fc-Fusion Proteins.

Attractive self-interactions and reversible self-association are implicated in many problematic solution behaviors for therapeutic proteins, such as irreversible aggregation, elevated viscosity, phase separation, and opalescence. Protein self-interactions and reversible oligomerization of two Fc-fusion proteins (monovalent and bivalent) and the corresponding fusion partner protein were characterized experimentally with static and dynamic light scattering as a function of pH (5 and 6.5) and ionic strength (10 mM to at least 300 mM). The fusion partner protein and monovalent Fc-fusion each displayed net attractive electrostatic self-interactions at pH 6.5 and net repulsive electrostatic self-interactions at pH 5. Solutions of the bivalent Fc-fusion contained higher molecular weight species that prevented quantification of typical interaction parameters (B22 and kD). All three of the proteins displayed reversible self-association at pH 6.5, where oligomers dissociated with increased ionic strength. Coarse-grained molecular simulations were used to model the self-interactions measured experimentally, assess net self-interactions for the bivalent Fc-fusion, and probe the specific electrostatic interactions between charged amino acids that were involved in attractive electrostatic self-interactions. Mayer-weighted pairwise electrostatic energies from the simulations suggested that attractive electrostatic self-interactions at pH 6.5 for the two Fc-fusion proteins were due to cross-domain interactions between the fusion partner domain(s) and the Fc domain.

A neural network potential based on pairwise resolved atomic forces and energies.

Molecular simulations have become a key tool in molecular and materials design. Machine learning (ML)-based potential energy functions offer the prospect of simulating complex molecular systems efficiently at quantum chemical accuracy. In previous work, we have introduced the ML-based PairF-Net approach to neural network potentials, that adopts a pairwise interatomic scheme to predicting forces within a molecular system. Here, we further develop the PairF-Net model to intrinsically incorporate energy conservation and couple the model to a molecular mechanical (MM) environment within the OpenMM package. The updated PairF-Net model yields energy and force predictions and dynamical distributions in good agreement with the rMD17 dataset of ten small organic molecules in the gas-phase. We further show that these in vacuo ML models of small molecules can be applied to force predictions in aqueous solution via hybrid ML/MM simulations. We present a new benchmark dataset for these ten molecules in solution, obtained from QM/MM simulations, which we denote as rMD17-aq (https://zenodo.org/records/10048644); and assess the ability of PairF-Net to reproduce the molecular energy, atomic forces and dynamical distributions of these solution conformations via ML/MM simulations.

Revealing the Role of Noncovalent Interactions on the Conformation of the Methyl Group in Tricyclic Orthoamide.

Tricyclic orthoamides are valuable molecules with wide-ranging applications, including organic synthesis and molecular recognition. Their structural properties make them intriguing, particularly the eclipsed all-trans conformer, which is typically less stable than the alternated conformation and is a rare phenomenon in organic chemistry. However, it gains stability in crystalline and hydrated settings, challenging the existing theoretical explanations. This study investigates which factors make eclipsed conformers more stable using experimentally reported anhydrous (ATO) and hydrated (HTO) crystal structures. Employing the quantum theory of atoms in molecules, noncovalent interaction index, and pairwise energy decomposition analysis, we delve into the noncovalent interaction environment surrounding the molecule of interest. In ATO, dispersive interactions dominate, whereas in HTO, both dispersive and electrostatic contributions are observed due to the presence of water molecules. Anchored to the lone pairs of the nitrogen atom in the orthoamide tricycle, water molecules prompt the methyl group's eclipsing through intermolecular and intramolecular interactions. This work resolves the long-standing conflict behind why tricyclic orthoamide has an eclipsed conformation by establishing the stabilization factors. These insights have implications for crystal engineering and design, enhancing our understanding of structural behavior in both crystalline and hydrated environments.

IAMY-RECMFF: Identifying amyloidgenic peptides by using residue pairwise energy content matrix and features fusion algorithm.

Various diseases, including Huntington's disease, Alzheimer's disease, and Parkinson's disease, have been reported to be linked to amyloid. Therefore, it is crucial to distinguish amyloid from non-amyloid proteins or peptides. While experimental approaches are typically preferred, they are costly and time-consuming. In this study, we have developed a machine learning framework called iAMY-RECMFF to discriminate amyloidgenic from non-amyloidgenic peptides. In our model, we first encoded the peptide sequences using the residue pairwise energy content matrix. We then utilized Pearson's correlation coefficient and distance correlation to extract useful information from this matrix. Additionally, we employed an improved similarity network fusion algorithm to integrate features from different perspectives. The Fisher approach was adopted to select the optimal feature subset. Finally, the selected features were inputted into a support vector machine for identifying amyloidgenic peptides. Experimental results demonstrate that our proposed method significantly improves the identification of amyloidgenic peptides compared to existing predictors. This suggests that our method may serve as a powerful tool in identifying amyloidgenic peptides. To facilitate academic use, the dataset and codes used in the current study are accessible at https://figshare.com/articles/online_resource/iAMY-RECMFF/22816916.

Phase Separation and Ion Diffusion in Ionic Liquid, Organic Solvent, and Lithium Salt Electrolyte Mixtures.

The highly desirable characteristics of ternary mixtures of ionic liquids, organic solvents, and metal salts make them a promising candidate for use in various electrothermal energy storage and conversion systems. In this study, using large-scale classical molecular dynamics simulations, we looked into 10 different ternary electrolyte mixtures using combinations of [EMIM]+, [BMIM]+, and [OMIM]+ cations with [NO3]-, [BF4]-, [PF6]-, [ClO4]-, [TFO]-, and [NTf2]- anions, tetraglyme, and Li salt to study the effect of ionic liquid composition on the phase behavior of ternary electrolyte mixtures. We uncovered that in these electrolytes, phase separation is mainly a function of pairwise binding energy of the constituents of the mixture. To corroborate this theory, several simulations are performed at various temperatures ranging from 260 to 500 K for each mixture, followed by calculating the binding energy of ionic liquid pairs using density functional theory. Our results verify that the transition temperature for the phase separation of each system is indeed a function of the pairwise binding energy of its ionic liquid pairs. It is also found that in some cases, the diffusion coefficient of the Li+ ions decreased even with the increase in the temperature, an effect that is attributed to the presence of condensed ionic domains in the electrolyte. This study provides a new insight for the design of multicomponent electrolyte mixtures for a wide range of energy applications.

Effective mechanical potential of cell-Cell interaction explains three-dimensional morphologies during early embryogenesis.

Mechanical forces are critical for the emergence of diverse three-dimensional morphologies of multicellular systems. However, it remains unclear what kind of mechanical parameters at cellular level substantially contribute to tissue morphologies. This is largely due to technical limitations of live measurements of cellular forces. Here we developed a framework for inferring and modeling mechanical forces of cell-cell interactions. First, by analogy to coarse-grained models in molecular and colloidal sciences, we approximated cells as particles, where mean forces (i.e. effective forces) of pairwise cell-cell interactions are considered. Then, the forces were statistically inferred by fitting the mathematical model to cell tracking data. This method was validated by using synthetic cell tracking data resembling various in vivo situations. Application of our method to the cells in the early embryos of mice and the nematode Caenorhabditis elegans revealed that cell-cell interaction forces can be written as a pairwise potential energy in a manner dependent on cell-cell distances. Importantly, the profiles of the pairwise potentials were quantitatively different among species and embryonic stages, and the quantitative differences correctly described the differences of their morphological features such as spherical vs. distorted cell aggregates, and tightly vs. non-tightly assembled aggregates. We conclude that the effective pairwise potential of cell-cell interactions is a live measurable parameter whose quantitative differences can be a parameter describing three-dimensional tissue morphologies.

Supramolecular characterisation of salts of 4-(2-methoxyphenyl)piperazin-1-ium and 4-phenylpiperazin-1-ium cations with simple-organic anions; a closer look at the binding energies of cation-anion pairs formed by charge-assisted (+)N−H···O(-) and (+)N−H···O hydrogen bonds

Six new salts prepared by acid-base reactions containing 4-(2-methoxyphenyl)piperazin-1-ium cation (2-MeOPP) with simple organic-acid anions, namely pentafluorobenzoate, (I); (2R,3R)-tartrate dihydrate, (II); succinate trihydrate, (III); or 4-phenylpiperazin-1-ium cation (PP) with 4-chlorobenzoate monohydrate, (IV); 3-chlorobenzoate monohydrate, (V) and succinate (VI) have been structurally characterised using single-crystal X-ray diffraction. Crystal-packing architectures have been described in the context of the supramolecular assemblies they form. The most important structural motifs are generated through hydrogen bonds between 2-MeOPP or PP cations and associated anions, assisted by their charges. To quantify these charge-assisted hydrogen bonds: (+)N−H····O(-) and (+)N−H····O, the binding energies of the ionic pairs have been calculated and compared. We considered a set of 72 ionic pairs of the structures analysed in this article and those published previously by our groups. As a result, we have plotted lines of trends found for DFT-binding energies vs normalised H···O proton···acceptor distances, and correlation between normalised geometrical parameters for aromatic and aliphatic anions. A comparison between DFT-energies and model pairwise energies (CE-B3LYP) has also been made.

Gefitinib derivatives and drug-resistance: A perspective from molecular dynamics simulations

Epidermal-growth factor receptor (EGFR) is a transmembrane tyrosine kinase (TK) with a significant role in cell survival. EGFR is upregulated in various cancer cells and known as a druggable target. Gefitinib is a first-line TK inhibitor used against metastatic non-small cell lung cancer (NSCLC). Despite initial clinical response, a conserved therapeutic effect could not be achieved due to the occurrence of resistance mechanisms. Point mutations in EGFR genes are one of the major causes of rendered tumor sensitivity. To aid in the development of more efficient TKIs, chemical structures of prevailing drugs and their target binding patterns are very important. The aim of the present study was to propose synthetically-accessible gefitinib congeners with enhanced binding fitness to clinically frequent EGFR mutants. Docking simulations of intended molecules identified 1-(4-(3-chloro-4-fluorophenylamino)-7-methoxyquinazolin-6-yl)-3-(oxazolidin-2-ylmethyl) thiourea (23) as a top-binder structure inside G719S, T790 M, L858R and T790 M/L858R-EGFR active sites. Superior docked complexes were subjected to the entire 400 ns molecular dynamics (MD) simulations. Analysis of data revealed the stability of mutant enzymes upon binding to molecule 23. All mutant complexes with the exception of a T790 M/L858R-EGFR, were majorly stabilized through cooperative hydrophobic contacts. Pairwise analysis of H-bonds proved Met793 as the conserved residue with stable H-bond participations as hydrogen bond donor (Frequency 63–96%). Amino acid decomposition analysis confirmed the probable role of Met793 in complex stabilization. Estimated binding free energies indicated the proper accommodation of molecule 23 inside target active sites. Pairwise energy decompositions of stable binding modes revealed the energetic contribution of key residues. Although wet lab experiments are required to unravel the mechanistic details of mEGFR inhibition, MD results provide structural basis for those events that are difficult to address experimentally. The outputs of the current study may assist to design small molecules with high potency to mEGFRs.

Effect of Physically Realistic Potential Energy Form on Spatial Pattern Complexity in a Collective Motion Model

Collective motion models most often use self-propelled particles, which are known to produce organized spatial patterns via their collective interactions. However, there is less work considering the possible organized spatial patterns achievable by non-self-propelled particles (nondriven), i.e., those obeying energy and momentum conservation. Moreover, it is not known how the potential energy interaction between the particles affects the complexity of the patterns. To address this, in this paper, a collective motion model with a pairwise potential energy function that conserved the total energy and momentum of the particles was implemented. The potential energy function was derived by generalizing the Lennard–Jones potential to reduce to gravity-like and billiard-ball-like potentials at the extremes of its parameter range. The particle model was simulated under a number of parameterizations of this generalized potential, and the average complexity of the spatial pattern produced by each was computed. Complexity was measured by tracking the information needed to describe the particle system at different scales (the complexity profile). It was found that the spatial patterns of the particles were the most complex around a specific ratio in the parameters. This parameter ratio described a characteristic shape of the potential energy function that is capable of producing complex spatial patterns. It is suggested that the characteristic shape of the potential energy produces complex behavior by balancing the likelihood for particles to bond. Furthermore, these results demonstrate that complex spatial patterns are possible even in an isolated system.

Gate-based quantum computing for protein design.

Protein design is a technique to engineer proteins by permuting amino acids in the sequence to obtain novel functionalities. However, exploring all possible combinations of amino acids is generally impossible due to the exponential growth of possibilities with the number of designable sites. The present work introduces circuits implementing a pure quantum approach, Grover's algorithm, to solve protein design problems. Our algorithms can adjust to implement any custom pair-wise energy tables and protein structure models. Moreover, the algorithm's oracle is designed to consist of only adder functions. Quantum computer simulators validate the practicality of our circuits, containing up to 234 qubits. However, a smaller circuit is implemented on real quantum devices. Our results show that using [Formula: see text] iterations, the circuits find the correct results among all N possibilities, providing the expected quadratic speed up of Grover's algorithm over classical methods (i.e., [Formula: see text]).

Searching for Suitable Kojic Acid Coformers: From Cocrystals and Salt to Eutectics.

The possibility of obtaining cocrystals of kojic acid with organic coformers has been investigated by both computational and experimental approaches. Cocrystallization attempts have been carried out with about 50 coformers, in different stoichiometric ratios, by solution, slurry, and mechanochemical methods. Cocrystals were obtained with 3-hydroxybenzoic acid, imidazole, 4-pyridone, DABCO, and urotropine, while piperazine yielded a salt with the kojiate anion; cocrystallization with theophylline and 4-aminopyridine resulted in stoichiometric crystalline complexes that could not be described with certainty as cocrystals or salts. In the cases of panthenol, nicotinamide, urea, and salicylic acid the eutectic systems with kojic acid were investigated via differential scanning calorimetry. In all other preparations the resulting materials were constituted of a mixture of the reactants. All compounds were investigated by powder X-ray diffraction; the five cocrystals and the salt were fully characterized via single crystal X-ray diffraction. The stability of the cocrystals and the intermolecular interactions in all characterized compounds have been investigated by computational methods based on the electronic structure and pairwise energy calculations, respectively.

Charging toward decarbonized electrification: Revisiting Beijing's power system

Beijing's power system has experienced a significant transition by eliminating coal-fired power generation and increasing the extent of electrification over the past two decades. This study uses a plant-level dataset, pair-wise energy flow, and customized index decomposition analysis to investigate the driving forces behind Beijing's rapid electrification and carbon mitigation effects. Our assessment approaches can reveal the role of electrification in driving city-level emissions and identify a reasonable timeline to accelerate electrification for cities. We find that electrification-related factors are responsible for 21.8% of carbon emission changes in Beijing between 1995 and 2019. The extent of electrification in Beijing has doubled from 9.5% in 1995 to 19% in 2019, while the carbon intensity of electricity consumption has reduced by 26%. Particularly, the average emission intensity of Beijing's local power generation has dropped from 860 tCO2e/GWh in 2000 to 370 tCO2e/GWh in 2018, which is far below a critical level at which the high penetration of electricity in transportation and housing should be prioritized for decarbonization. Our results confirm that Beijing is in the best position to accelerate electrification to meet its carbon neutrality goals; however, this will increasingly rely on regionally collaborative decarbonization efforts with surrounding regions.