Journal of Chemical Theory and Computation最新文献

英文中文

Projection-Based DMRG-in-DFT Embedding Corrected by Nonadditive Exchange-Correlation

IF 5.5 1区化学 Q2 CHEMISTRY, PHYSICAL

Journal of Chemical Theory and Computation

Pub Date : 2026-02-09 DOI: 10.1021/acs.jctc.5c01930

Enzo Monino,Daria Drwal,Pavel Beran,Michał Hapka,Libor Veis,Katarzyna Pernal

The projection-based wave function in density functional theory (WF-in-DFT) embedding enables an efficient description of both the energetics and properties of large and complex chemical systems, with accuracy exceeding that of pure DFT. Recently, we have proposed using the density matrix renormalization group (DMRG) as the WF method for molecules containing strongly correlated fragments [Beran, P. J. Phys. Chem. Lett. 2023, 14, 716–722]. In this work, we demonstrate that the accuracy of the DMRG-in-DFT approach is primarily limited by the approximate treatment of the coupling between the active component and its environment through nonadditive exchange-correlation functionals. To address this issue, we combine exact exchange to reduce the nonadditive exchange error with a multireference adiabatic connection (AC) scheme to recover nonadditive correlation. The performance of the improved DMRG-in-DFT embedding is illustrated on two prototypical strongly correlated systems: the dissociation of the H20 chain and the cleavage of a triple CN bond in propionitrile.

引用次数: 0

Marcus Theory and The Condon Approximation Revisited II: The Horror of Triplet Energy Transfer

IF 5.5 1区化学 Q2 CHEMISTRY, PHYSICAL

Journal of Chemical Theory and Computation

Pub Date : 2026-02-09 DOI: 10.1021/acs.jctc.5c01734

Jennifer R. DeRosa,Tian Qiu,D. Vale Cofer-Shabica,Joseph E. Subotnik

We investigate the applicability of the Condon approximation (i.e., the notion that the diabatic coupling is invariant to geometry) in the context of both electron transfer (ET) and triplet energy transfer (TET) and compare the two cases. Although it is well appreciated that diabatic couplings usually arise from the interactions of electronic wave function tails, we show that ET tails are very different from TET tails. Using a simple model problem, our analysis explains in detail why the rates of TET decays with twice the rate of ET, while also leading to the hypothesis that the smaller diabatic couplings found for TET (versus ET) should imply more sensitivity to non-Condon fluctuations. As an example, for the classic sets of molecules investigated by Closs, we show that the Condon approximation is indeed less applicable for TET than for ET.

引用次数: 0

MemConverter: An Iterative Pipeline for Reprogramming Protein Localization in Membrane or Aqueous Solution

IF 5.5 1区化学 Q2 CHEMISTRY, PHYSICAL

Journal of Chemical Theory and Computation

Pub Date : 2026-02-08 DOI: 10.1021/acs.jctc.5c01859

Jun Li,Haozhe Guo,Chen Song

We propose a pipeline, MemConverter, for the conversion of soluble proteins to membrane proteins and vice versa, based on the prediction of membrane contact probability (MCP). By fine-tuning ProteinMPNN with a membrane protein data set to create MemProtMPNN, and integrating it with iterative structure refinement using AlphaFold2, our approach enables precise reprogramming of protein surface properties. The pipeline utilizes MCP-guided sequence fusion to direct the evolution of protein sequences toward the desired membrane or soluble environments. The pipeline demonstrates superior performance compared to existing methods, and molecular dynamics simulations validate that the designed proteins exhibit stable membrane integration or enhanced solubility, depending on the target localization. This pipeline introduces a new computational tool for engineering proteins to be localized in membranes or aqueous solutions.

引用次数: 0

Performance of Universal Machine-Learned Potentials with Explicit Long-Range Interactions in Biomolecular Simulations. 生物分子模拟中具有显式远程相互作用的通用机器学习势的性能。

IF 5.5 1区化学 Q2 CHEMISTRY, PHYSICAL

Journal of Chemical Theory and Computation

Pub Date : 2026-02-05 DOI: 10.1021/acs.jctc.5c01828

Viktor Zaverkin, Matheus Ferraz, Francesco Alesiani, Mathias Niepert

Universal machine-learned potentials promise transferable accuracy across compositional and vibrational degrees of freedom, yet their application to biomolecular simulations remains underexplored. This work systematically evaluates equivariant message-passing architectures trained on the SPICE-v2 data set with and without explicit long-range dispersion and electrostatics. We assess the impact of model size, training data composition, and electrostatic treatment across in- and out-of-distribution benchmark data sets, as well as molecular simulations of bulk liquid water, aqueous NaCl solutions, and biomolecules, including alanine tripeptide, the mini-protein Trp-cage, and Crambin. While larger models improve accuracy on benchmark data sets, this trend does not consistently extend to properties obtained from simulations. Predicted properties also depend on the composition of the training data set. Long-range electrostatics show no systematic impact across systems. However, for Trp-cage, their inclusion yields increased conformational variability. Our results suggest that imbalanced data sets and immature evaluation practices currently challenge the applicability of universal machine-learned potentials to biomolecular simulations.

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引用次数: 0

Reduced Density Matrix and Cumulant Approximations of Quantum Linear Response. 量子线性响应的约化密度矩阵和累积量近似。

IF 5.5 1区化学 Q2 CHEMISTRY, PHYSICAL

Journal of Chemical Theory and Computation

Pub Date : 2026-02-05 DOI: 10.1021/acs.jctc.5c01353

Theo Juncker von Buchwald, Erik Rosendahl Kjellgren, Jacob Kongsted, Stephan P A Sauer, Sonia Coriani, Karl Michael Ziems

Linear response (LR) is an important tool in the computational chemist's toolbox. It is therefore unsurprising that the emergence of quantum computers has led to a quantum counterpart known as quantum LR (qLR). However, the current quantum era of near-term intermediate-scale quantum (NISQ) computers is dominated by noise, short decoherence times, and slow measurement speeds. It is therefore of interest to find approximations that can greatly reduce the quantum workload while only slightly impacting the quality of a method. In an effort to achieve this, we approximate the naive qLR with the singles and doubles (qLRSD) method, by either directly approximating the reduced density matrices (RDMs) or indirectly through their respective reduced density cumulants (RDCs). We present an analysis of the measurement costs associated with qLR using RDMs and report qLR results for model hydrogen ladder systems; for varying active space sizes in OCS, SeH₂, and H₂S; and for symmetrically stretched H₂O and BeH₂. Discouragingly, while approximations to the 4-body RDMs and RDCs seem to produce good results for systems at the equilibrium geometry and for some types of core excitations, they both tend to fail when the system exhibits strong correlation. All approximations to the 3-body RDMs and/or RDCs severely affect the results and cannot be applied.

线性响应（LR）是计算化学家工具箱中的一个重要工具。因此，量子计算机的出现导致了量子对应物量子LR （qLR）的出现也就不足为奇了。然而，当前的量子时代，短期的中等规模量子（NISQ）计算机被噪声、短退相干时间和缓慢的测量速度所主导。因此，找到可以大大减少量子工作负载，同时只略微影响方法质量的近似值是很有意义的。为了实现这一目标，我们用单双元（qLRSD）方法近似朴素qLR，通过直接近似约简密度矩阵（rdm）或间接通过其各自的约简密度累积量（rdc）。我们使用rdm分析了与qLR相关的测量成本，并报告了模型氢阶梯系统的qLR结果；用于OCS、SeH2和H2S中不同的活性空间大小；以及对称拉伸的H2O和BeH2。令人沮丧的是，虽然对四体rdm和rdc的近似似乎对平衡几何和某些类型的核心激励的系统产生良好的结果，但当系统表现出强相关性时，它们往往都失败。所有对三体rdm和/或rdc的近似都严重影响结果，不能应用。

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引用次数: 0

Transition State Theory for Dissociation of Dynamic Bonding Networks 动态键网络解离的过渡态理论

IF 5.5 1区化学 Q2 CHEMISTRY, PHYSICAL

Journal of Chemical Theory and Computation

Pub Date : 2026-02-04 DOI: 10.1021/acs.jctc.5c01797

Eric V. Anslyn,Dmitrii E. Makarov

Cell adhesion, molecular recognition, biomolecular folding and unfolding, dynamic cross-linking in soft materials, and many other phenomena involve formation or dissociation of multiple chemical bonds. Here, we study the overall time scale required to break or form N bonds. Strictly speaking, this time scale depends on the initial conditions, e.g., the number and which bonds are formed/broken, and its estimation requires kinetic details about forming and breaking of each individual bond influenced by the larger network of other bonds. We show, however, that a simple estimate, analogous to transition-state theory in chemical kinetics, accurately predicts the mean first passage time to form or break all the bonds in terms of single-bond properties and thermodynamic properties of the network. As the thermodynamics of bond networks can often be described by well-studied statistical-mechanical models, such as the Ising model and its extensions, our theory provides a link between the global dynamics and thermodynamics of multibond arrays and networks.

细胞粘附，分子识别，生物分子折叠和展开，软材料中的动态交联以及许多其他现象涉及多个化学键的形成或解离。在这里，我们研究了打破或形成N键所需的总体时间尺度。严格地说，这个时间尺度取决于初始条件，例如，形成/断裂的键的数量和哪些键，它的估计需要受其他更大的键网络影响的每个单独键的形成和断裂的动力学细节。然而，我们表明，一个简单的估计，类似于化学动力学中的过渡状态理论，准确地预测了在单键性质和网络的热力学性质方面形成或打破所有键的平均首次通过时间。由于键网络的热力学通常可以通过充分研究的统计力学模型来描述，例如Ising模型及其扩展，我们的理论提供了多键阵列和网络的全局动力学和热力学之间的联系。

引用次数: 0

Kinetic Monte Carlo Framework for Coupled Degradation and Dehydration of Anion Exchange Membranes 阴离子交换膜耦合降解脱水的动力学蒙特卡罗框架

IF 5.5 1区化学 Q2 CHEMISTRY, PHYSICAL

Journal of Chemical Theory and Computation

Pub Date : 2026-02-04 DOI: 10.1021/acs.jctc.5c02063

Esteban D. Gadea,Shakkira Erimban,Ignacio J. Bombau,Damian A. Scherlis,John J. Karnes,Valeria Molinero

Kinetic Monte Carlo (kMC) simulations, augmented with temporal-acceleration schemes, can efficiently handle stiff reaction-transport networks when fast processes rapidly relax to quasi-equilibrium on a fixed lattice. However, in glassy anion-exchange membranes (AEM), rare and irreversible chemical degradation events continuously reshape the nanoscale morphology, and the associated hydration and transport degrees of freedom remain far from a well-defined local equilibrium. This combination of evolving state space and nonequilibrated fast dynamics lies outside the scope of existing kMC acceleration frameworks. To address this challenge, we introduce an auxiliary-particle kinetic Monte Carlo (AP-kMC) scheme. In AP-kMC, short-lived mobile particles spawned at degradation sites execute hop, water-elimination, and decay moves, enforcing rapid local relaxation of the hydration structure while preserving the stochastic rules of kMC. Parameterized with molecular-dynamics morphologies and experimental solution degradation kinetics, AP-kMC reproduces the evolution of ion-exchange capacity, water uptake, and conductivity, and reveals a feedback loop in which poorly hydrated sites degrade first and each degradation event induces further local dehydration. The resulting thinning and fragmentation of water channels cause loss of hydrophilic percolation and abrupt conductivity collapse well before complete charge loss. AP-kMC thus reframes AEM durability as a coupled degradation–drying–percolation problem and provides a transferable strategy to simulate reactive, out-of-equilibrium polymer electrolytes where local solvation controls reactivity.

动力学蒙特卡罗（kMC）模拟，增加了时间加速方案，可以有效地处理刚性反应-输运网络，当快速过程在固定晶格上迅速放松到准平衡状态时。然而，在玻璃阴离子交换膜（AEM）中，罕见且不可逆的化学降解事件不断重塑纳米级形态，相关的水化和运输自由度仍远未达到明确的局部平衡。这种演化状态空间和非平衡快速动力学的结合超出了现有kMC加速框架的范围。为了解决这一挑战，我们引入了辅助粒子动力学蒙特卡罗（AP-kMC）方案。在AP-kMC中，在降解位点产生的短寿命移动颗粒执行跳跃、水消除和衰变运动，在保持kMC随机规则的同时，强制水化结构的局部快速松弛。通过分子动力学形态学和实验溶液降解动力学参数化，AP-kMC再现了离子交换能力、吸水率和电导率的演变，并揭示了一个反馈回路，在这个反馈回路中，水化程度较低的部位首先降解，每次降解事件都会引起进一步的局部脱水。由此导致的水通道变薄和破碎导致亲水性渗透的损失和电导率的突然崩溃，甚至在完全电荷损失之前。因此，AP-kMC将AEM耐久性重新定义为一个耦合的降解-干燥-渗透问题，并提供了一种可转移的策略来模拟反应性，非平衡聚合物电解质，其中局部溶剂化控制反应性。

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引用次数: 0

A Hardware-Feasible Quantum Machine Learning Framework for Structure-Based Virtual Screening 一种硬件可行的基于结构的虚拟筛选量子机器学习框架

IF 5.5 1区化学 Q2 CHEMISTRY, PHYSICAL

Journal of Chemical Theory and Computation

Pub Date : 2026-02-04 DOI: 10.1021/acs.jctc.5c01872

Pei-Kun Yang

In structure-based virtual screening, evaluating the binding free energy of protein–ligand complexes requires accounting for both molecular conformations and spatial transformations, such as shifts and rotations, which can lead to an exponential increase in possible configurations. Classical computing approaches are limited in handling this combinatorial explosion, whereas quantum computing offers a promising alternative due to its inherent parallelism. In this study, we propose a quantum machine learning framework that encodes molecular features into quantum states and processes them through parametrized quantum gates, with all architectural and representational choices deliberately guided by near-term hardware feasibility and an explicit focus on minimal qubit counts, shallow circuit depth, and compact input representations. The model is implemented and optimized in PyTorch, and its predictive performance is examined under three conditions: ideal simulation, finite-shot sampling, and quantum-noise simulation. With six quantum circuit units, the model achieves a root-mean-square deviation of 2.37 kcal/mol and a Pearson correlation coefficient of 0.650. The predictions remain stable with 100,000 measurement shots, demonstrating compatibility with near-term quantum hardware. Although the introduction of noise slightly reduces absolute accuracy, the Pearson correlation coefficient remains stable, indicating that the ranking of ligand affinities is preserved. These results highlight a practical, scalable quantum approach that balances predictive power and robustness, providing a feasible pathway to accelerate virtual screening using moderately deep quantum circuits.

在基于结构的虚拟筛选中，评估蛋白质-配体复合物的结合自由能需要考虑分子构象和空间转换，如移位和旋转，这可能导致可能的构型呈指数增长。经典计算方法在处理这种组合爆炸方面受到限制，而量子计算由于其固有的并行性提供了一个有前途的替代方案。在本研究中，我们提出了一个量子机器学习框架，该框架将分子特征编码为量子态，并通过参数化量子门对其进行处理，所有架构和表征选择都刻意以近期硬件可行性为指导，并明确关注最小量子位计数、浅电路深度和紧凑的输入表示。在PyTorch中对该模型进行了实现和优化，并在理想模拟、有限采样和量子噪声模拟三种条件下对其预测性能进行了测试。采用6个量子电路单元，模型的均方根偏差为2.37 kcal/mol， Pearson相关系数为0.650。这些预测在10万次测量中保持稳定，证明了与近期量子硬件的兼容性。虽然噪声的引入略微降低了绝对精度，但Pearson相关系数保持稳定，表明配体亲和度的排序保持不变。这些结果突出了一种实用的、可扩展的量子方法，它平衡了预测能力和鲁棒性，为使用适度深度量子电路加速虚拟筛选提供了可行的途径。

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引用次数: 0

Multistate Iterative Qubit Coupled Cluster (MS-iQCC): A Quantum-Inspired, State-Averaged Approach to Ground- And Excited-State Energies 多态迭代量子比特耦合簇（MS-iQCC）：一种量子启发的、状态平均的基态和激发态能量方法

IF 5.5 1区化学 Q2 CHEMISTRY, PHYSICAL

Journal of Chemical Theory and Computation

Pub Date : 2026-02-04 DOI: 10.1021/acs.jctc.5c01849

Robert A. Lang,Shashank G. Mehendale,Ilya G. Ryabinkin,Artur F. Izmaylov

We introduce the multistate iterative qubit coupled cluster (MS-iQCC) method, a quantum-inspired algorithm that runs efficiently on classical hardware and is designed to predict both ground and excited electronic states of molecules. Accurate excited-state energetics are essential for interpreting spectroscopy and chemical reactivity, but standard electronic structure methods are either too computationally expensive for larger systems or lose reliability in the presence of strong electron correlation. MS-iQCC addresses this challenge by simultaneously optimizing multiple electronic states in a single, state-averaged procedure that treats ground and excited states on equal footing. This removes the energetic bias that is introduced when excited states are computed one at a time and constrained to remain orthogonal to previously optimized states. The approach supports multireference electronic structure by allowing multideterminantal initial guesses and by adaptively building a compact exponential ansatz from a pool of qubit excitation generators. We apply MS-iQCC to H4, H2O, N2, and C2, including strongly correlated geometries, and observe robust convergence of all targeted state energies to chemically meaningful accuracy across their potential energy surfaces.

我们介绍了多态迭代量子比特耦合簇（MS-iQCC）方法，这是一种在经典硬件上高效运行的量子启发算法，旨在预测分子的基态和激发态。准确的激发态能量学对于解释光谱和化学反应性至关重要，但是标准的电子结构方法对于较大的系统来说计算成本太高，或者在存在强电子相关性的情况下失去可靠性。MS-iQCC解决了这一挑战，同时优化多个电子状态在一个单一的，状态平均的程序，对待基态和激发态在平等的基础上。这消除了一次计算一个激发态时引入的能量偏差，并且约束保持与先前优化的状态正交。该方法支持多参考电子结构，允许多确定性初始猜测，并自适应地从量子位激发发生器池中构建紧凑的指数ansatz。我们将MS-iQCC应用于H4， H2O， N2和C2，包括强相关的几何结构，并观察到所有目标状态能量在其势能表面上的鲁棒收敛，具有化学意义的准确性。

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引用次数: 0

Braess’ Paradox in Enzyme Kinetics: Asymmetry from Population Balance without Direct Cooperativity 酶动力学中的Braess悖论：非直接协同性种群平衡的不对称性

IF 5.5 1区化学 Q2 CHEMISTRY, PHYSICAL

Journal of Chemical Theory and Computation

Pub Date : 2026-02-04 DOI: 10.1021/acs.jctc.5c01269

Malte Schäffner,Colin A. Smith,Robert Tampé,Helmut Grubmüller

The ATPase ABCE1, a member of the ubiquitous ATP-Binding Cassette protein superfamily, is essential in eukaryotic and archaeal ribosome recycling. It comprises a pair of homologous nucleotide-binding domains (NBDs), each containing a consensus nucleotide-binding site (NBS), where ATP hydrolysis takes place. Each of these sites can be in either an open or closed conformation. Despite the near symmetry of the two NBDs, and quite unexpectedly, their hydrolysis kinetics are highly asymmetric. While substitution of the catalytic glutamate (E238Q) in NBSI reduced the overall turnover rate of the ATPase by a factor of 2, as one might expect, the corresponding substitution in NBSII (E485Q) shows a so far unexplained 10-fold increase. To address this issue, we used Markov models to study how such a drastic asymmetry can arise. Specifically, we asked whether this observation can be explained without previously proposed direct allosteric interactions, such as electrostatic interactions, between the two NBSs. Indeed, using a Bayesian approach, we found Markov models that quantitatively predict the experimentally observed kinetics, as well as additional steady-state ATP occupancy data, both without such direct allosteric interaction. In particular, our results show that the observed remarkable asymmetry is fully explained by the structure-induced property that opening and closing always involves both NBSs. These models can explain the unexpected fast kinetics of the mutant of NBSII in terms of a drastic population shift due to the mutation, which circumvents a kinetic trap state that slows wild-type kinetics. Our Bayesian Markov approach may help to quantitatively explain similar nonintuitive Braess-type kinetics also in other enzymes where chemical/conformation coupling is essential.

atp酶ABCE1是普遍存在的atp结合盒蛋白超家族的成员，在真核生物和古细菌核糖体循环中起着至关重要的作用。它包括一对同源核苷酸结合域（nbd），每个都包含一个一致的核苷酸结合位点（NBS）， ATP水解发生在这里。每个位点都可以是开放构象或封闭构象。出乎意料的是，尽管这两种nbd接近对称，但它们的水解动力学却是高度不对称的。虽然NBSI中催化谷氨酸（E238Q）的取代使atp酶的总周转率降低了2倍，正如人们所预料的那样，NBSII中相应的取代（E485Q）显示出迄今尚未解释的10倍的增加。为了解决这个问题，我们使用马尔可夫模型来研究这种剧烈的不对称是如何产生的。具体来说，我们想知道，如果没有先前提出的两种nbs之间的直接变构相互作用（如静电相互作用），是否可以解释这一观察结果。事实上，使用贝叶斯方法，我们发现马尔可夫模型可以定量预测实验观察到的动力学，以及额外的稳态ATP占用数据，两者都没有这种直接的变构相互作用。特别是，我们的研究结果表明，观察到的显著不对称性完全可以用结构诱导的性质来解释，即打开和关闭总是涉及两个nbs。这些模型可以解释NBSII突变体意想不到的快速动力学，因为突变引起了急剧的种群转移，从而绕过了减缓野生型动力学的动力学陷阱状态。我们的贝叶斯马尔可夫方法可能有助于定量解释类似的非直观的braess型动力学，也在其他酶的化学/构象耦合是必不可少的。

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