Journal of Chemical Theory and Computation最新文献

{"title":"Lifelong Machine Learning Potentials for Chemical Reaction Network Explorations","authors":"Marco Eckhoff*,&nbsp; and ,&nbsp;Markus Reiher*,&nbsp;","doi":"10.1021/acs.jctc.5c01127","DOIUrl":"10.1021/acs.jctc.5c01127","url":null,"abstract":"<p >Recent developments in computational chemistry facilitate the automated quantum chemical exploration of chemical reaction networks for the in-silico prediction of synthesis pathways, yield, and selectivity. However, the underlying quantum chemical energy calculations require vast computational resources, limiting these explorations severely in practice. Machine learning potentials (MLPs) offer a solution to increase computational efficiency, while retaining the accuracy of reliable first-principles data used for their training. Unfortunately, MLPs will be limited in their generalization ability within chemical (reaction) space, if the underlying training data are not representative for a given application. Within the framework of automated reaction network exploration, where new reactants or reagents composed of any elements from the periodic table can be introduced, this lack of generalizability will be the rule rather than the exception. Here, we therefore evaluate the benefits of the lifelong MLP concept in this context. Lifelong MLPs push their adaptability by efficient continual learning of additional data. We propose an improved learning algorithm for lifelong adaptive data selection yielding efficient integration of new data while previous expertise is preserved. In this way, we can reach chemical accuracy in reaction search trials.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":"21 19","pages":"9641–9656"},"PeriodicalIF":5.5,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.5c01127","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145123818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting Saturation Concentrations of Phase-Separating Proteins via Thermodynamic Integration","authors":"Eduardo Pedraza,&nbsp;, ,&nbsp;Andres R. Tejedor,&nbsp;, ,&nbsp;Alejandro Feito,&nbsp;, ,&nbsp;Francisco Gámez,&nbsp;, ,&nbsp;Rosana Collepardo-Guevara,&nbsp;, ,&nbsp;Eduardo Sanz*,&nbsp;, and ,&nbsp;Jorge R. Espinosa*,&nbsp;","doi":"10.1021/acs.jctc.5c00765","DOIUrl":"10.1021/acs.jctc.5c00765","url":null,"abstract":"<p >Phase separation of proteins and nucleic acids into biomolecular condensates contributes to the regulation of cellular compartmentalization in membrane-less environments. A key parameter controlling the onset of biomolecular condensate formation is the saturation concentration (<i>C</i>_sat)─the threshold concentration above which condensation takes place. While measuring <i>C</i>_sat for protein solutions in vitro is experimentally accessible, determining this quantity in simulations remains challenging due to the extremely low equilibrium concentrations at which many proteins phase separate. This occurs because the gold standard in simulations consists of combining a residue-resolution coarse-grained model with the Direct Coexistence simulation method, which yields poor estimates of the equilibrium concentrations of the dilute phase due to lack of statistics. In this work, we present two independent thermodynamic integration (TI) schemes which, when combined with Direct Coexistence simulations, enable accurate calculation of saturation concentrations and phase diagrams─facilitating direct comparison with experimental measurements across a wide range of conditions. Our methods, combined with the Mpipi-Recharged residue-resolution model, accurately estimate <i>C</i>_sat for a broad range of intrinsically disordered and multidomain proteins, including disease-associated RNA- and DNA-binding proteins involved in the formation of stress granules and P granules, as well as engineered mutants of hnRNPA1. Furthermore, we compare our TI methods against a computationally efficient machine-learning predictor trained to estimate saturation concentrations at room temperature. While both approaches yield realistic predictions, explicit molecular dynamics simulations enable the calculation of complete phase diagrams and provide insight into the molecular mechanisms and interactions driving phase separation. Overall, our approach offers a robust, physically grounded framework for improving and validating coarse-grained models of biomolecular phase behavior, effectively bridging the gap between simulation and experiment.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":"21 19","pages":"9919–9934"},"PeriodicalIF":5.5,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145084561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Molecular Mechanism of ATP Hydrolysis Catalyzed by p97: A QM/MM Study","authors":"Judit Katalin Szántó,&nbsp;, ,&nbsp;Andreas Hulm,&nbsp;, and ,&nbsp;Christian Ochsenfeld*,&nbsp;","doi":"10.1021/acs.jctc.5c00928","DOIUrl":"10.1021/acs.jctc.5c00928","url":null,"abstract":"<p >A computational study of p97/VCP ATPase using hybrid quantum mechanics/molecular mechanics (QM/MM) simulations is presented that explores the conformational landscape of the active site and hydrolysis-competent states of the crystallographic water molecules. Our investigation focuses on the reaction mechanism, particularly the events of the rate-determining first reaction step, which we study using extensive sampling with the path well-tempered metadynamics extended-system adaptive biasing force (WTM-eABF) enhanced sampling method. We identify the highly conserved glutamate (Glu305) from the Walker B motif as a catalytic base that activates the lytic water molecule for nucleophilic attack on the γ-phosphate in the first reaction step, while the final product is formed in a second step that involves proton transfer and rearrangements in the Mg²⁺ coordination sphere. We show that phosphate bond formation and breakage occur concertedly in the first reaction step. The findings gained through versatile QM/MM approaches are validated against recent cryo-EM and NMR data for the post-hydrolysis protein state, elucidating the role of amino acids from conserved motifs across the AAA+ protein family. To the best of our knowledge, this is the first <i>in silico</i> exploration of ATP hydrolysis in p97/VCP or any other AAA+ protein.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":"21 19","pages":"9459–9469"},"PeriodicalIF":5.5,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.5c00928","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145089799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Programmable Spiral Wave Dynamics: Instability Cascades Driven by Temporal Modulation in a Reaction-Diffusion System.","authors":"Tarpan Maiti,Achal Jadhav,Pushpita Ghosh","doi":"10.1021/acs.jctc.5c01230","DOIUrl":"https://doi.org/10.1021/acs.jctc.5c01230","url":null,"abstract":"Spiral waves are iconic structures and are striking hallmarks of self-organization in chemical and biological systems. While their instabilities under spatial inhomogeneities have been widely studied, the response of spirals to temporal modulations particularly near the Turing threshold yet away from Hopf bifurcation, remains underexplored. In this study, we reveal how periodic forcing of a kinetic parameter in the Chlorine Dioxide-Iodine-Malonic Acid model unlocks a diverse and tunable landscape of spiral wave instabilities in a regime that is spatially stable yet temporally unstable. Starting from a robust single-arm spiral, we observe a cascade of modulation-induced phenomena: breathing spirals, core drift, spiral breakup and turbulence, as well as transitions to oscillating clusters, Ising-front-like patterns, and spatially uniform bulk oscillations. Remarkably, we identify spiral regeneration with altered arm width and chirality reversal, along with asymmetric spirals and multiphase cluster states arising from amplitude-phase interactions. Our findings are systematically mapped onto a two-dimensional phase diagram, revealing resonance-driven bifurcation cascades. Our results illuminate how simple temporal inputs can steer complex pattern selection in nonlinear media, offering conceptual advances for systems chemistry, chemical wave control, and the design of responsive self-organizing systems.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":"18 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145089817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Periodic Implementation of the Random Phase Approximation with Numerical Atomic Orbitals and Dual Reciprocal Space Grids","authors":"Edoardo Spadetto*,&nbsp;, ,&nbsp;Pier Herman Theodoor Philipsen*,&nbsp;, ,&nbsp;Arno Förster*,&nbsp;, and ,&nbsp;Lucas Visscher*,&nbsp;","doi":"10.1021/acs.jctc.5c00751","DOIUrl":"10.1021/acs.jctc.5c00751","url":null,"abstract":"<p >The random phase approximation (RPA) has emerged as a prominent first-principles method in material science, particularly to study the adsorption and chemisorption of small molecules on surfaces. However, its widespread application is hampered by its relatively high computational cost. Here, we present a well-parallelised implementation of the RPA with localized atomic orbitals and pair-atomic density fitting, which is especially suitable for studying two-dimensional systems. Through a dual <b><i>k</i></b>-grid scheme, we achieve fast and reliable convergence of RPA correlation energies to the thermodynamic limit. We demonstrate the efficacy of our implementation through an application to the adsorption of CO on MgO(001) using PBE input orbitals (RPA@PBE). Our calculated adsorption energy is in excellent agreement with previously published RPA@PBE studies, but, as expected, overestimates the experimentally available adsorption energies as well as recent CCSD(T) results.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":"21 19","pages":"9347–9363"},"PeriodicalIF":5.5,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.5c00751","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145084518","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding DFT Uncertainties for More Reliable Reactivity Predictions by Advancing the Analysis of Error Sources","authors":"Gergely Laczkó,&nbsp;, ,&nbsp;Imre Pápai*,&nbsp;, and ,&nbsp;Péter R. Nagy*,&nbsp;","doi":"10.1021/acs.jctc.5c00985","DOIUrl":"10.1021/acs.jctc.5c00985","url":null,"abstract":"<p >Decades of advancements and thousands of successful applications have contributed to the reliability of density functional theory (DFT) methods. Especially in main group chemistry, DFT predictions tend to be increasingly more reliable. In this study, we deeply analyze unexpected (ca. 8–13 kcal/mol) DFT disagreements obtained for a few organic reactions using only widely adopted, modern, hybrid, and higher-rung DFT methods. To understand the underlying causes, we move beyond conventional statistics-based benchmarks by combining recent advances in DFT error decomposition with affordable gold-standard references. This approach helps to characterize and disentangle multiple functional and density-based error types and enables us to find functional(s) suitable for broad mechanistic studies in all studied examples. The proposed tools are cost-efficient, readily accessible, and easy to integrate into routine thermochemistry workflows. While the focus is on main group reactions, the approach is also applicable to transition metal, bio-, and surface chemistry to assist more predictive reactivity modeling.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":"21 19","pages":"9483–9497"},"PeriodicalIF":5.5,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.5c00985","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145079070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Recursive Linear Tensor Expansion with Natural Occupation Analysis","authors":"Zeynep Gündoğar*,&nbsp;, ,&nbsp;Mads Greisen Ho̷jlund*,&nbsp;, ,&nbsp;Kasper Green Larsen*,&nbsp;, and ,&nbsp;Ove Christiansen*,&nbsp;","doi":"10.1021/acs.jctc.5c01101","DOIUrl":"10.1021/acs.jctc.5c01101","url":null,"abstract":"<p >We introduce an innovative recursive tensor decomposition method that draws inspiration from quantum chemical theories. This approach integrates ideas such as natural occupation numbers and natural basis, much like natural orbitals, and employs truncations that parallel the excitation-level truncations in the linear expansions of configuration interaction theory. The framework features recursive algorithms that combine linear expansion with natural basis transformations at each step, ensuring convergence to the original tensor. Consequently, a numerical technique is developed that reconstructs the initial tensor with precision within a predetermined tolerance, using only subtensors of limited dimension and a series of matrix transformations. An initial Python implementation has been created for the 3D tensor scenario where 3D tensors are decomposed to be represented using vectors and matrices alone. We illustrate the behavior of the final Recursive Linear Tensor Expansion in Natural basis algorithm in processing random data sets, experimental data sets from diverse sources with both real and complex tensors, and data sets representing both time-independent and time-dependent anharmonic vibrational wave functions of water. Finally, the systematic accuracy control is illustrated for density fitting two-electron repulsion integrals and tested for the second-order correlation energy of molecular nitrogen and benzene.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":"21 19","pages":"9270–9289"},"PeriodicalIF":5.5,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145071789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Generalized Solid Solution Framework for the Gibbs Free Energy Calculation","authors":"Yang Huang,&nbsp; and ,&nbsp;Jingrun Chen*,&nbsp;","doi":"10.1021/acs.jctc.5c00524","DOIUrl":"10.1021/acs.jctc.5c00524","url":null,"abstract":"<p >We propose a generalized solid solution model for calculating configurational contribution to the Gibbs free energy at finite temperatures, incorporating a crystal graph-based on-site energy approach. By leveraging linear graph neural networks, our method unifies pair-based and cluster expansion approaches, enabling broad applicability across crystal structures. Fractional occupation is physically interpreted via mean-field theory, while entropy is modeled using ideal mixing with extended site constraints. To resolve the constants of compositions, we implement three key strategies. First, we employ a softmax-based variable transformation. Second, we introduce a gradient projection method that preserves species composition throughout the optimization process by constraining updates within a subspace that maintains the desired elemental ratios. Finally, a renormalization step is incorporated to correct numerical deviations, ensuring strict adherence to the target composition. We then apply our model to the Mo–Nb–Ta-W quaternary system, achieving an energy model MAE of 1.24 meV. Predicted phase transition temperatures for equal atomic binary alloys align well with expectations, identifying phase separation in MoNb and order–disorder transitions in MoTa, MoW, TaW, NbTa, and NbW. At low temperatures, stable configurations lie below the convex hull of the training data set, demonstrating the model’s predictive accuracy. Further analysis of MoNbTaW reveals transition temperatures at 950 and 400 K, with observed asymmetry in Mo/W sublattices. Finally, we extend our approach to ternary phase diagram predictions using Gibbs free energy interpolation and second-derivative analysis, yielding phase diagrams in agreement with optimized atomic configurations.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":"21 19","pages":"9982–9992"},"PeriodicalIF":5.5,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145071791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Introducing the Coupled-Cluster Theory to the Amorphous World of Liquids and Their Thermodynamic Simulations","authors":"Ctirad Červinka*,&nbsp;","doi":"10.1021/acs.jctc.5c01214","DOIUrl":"10.1021/acs.jctc.5c01214","url":null,"abstract":"<p >Amorphous molecular materials are ubiquitous, spanning drugs, semiconductors, or solvents. Large predictive capabilities of quantum-chemical simulations of structural and thermodynamic properties and phase transitions for such amorphous materials have remained out of reach for a long time due to the related immense computational costs. This work introduces a novel fragment-based ab initio Monte Carlo (FrAMonC) simulation technique to the amorphous realm of molecular liquids and glasses. It aims at enabling thermodynamic simulations for amorphous molecular materials based on direct ab initio sampling and at minimizing the amount of a priori required empirical inputs for such simulations. Focus on individual cohesive interactions within the bulk, and their sampling from multiple first-principles potentials with a many-body expansion scheme enables the use of very accurate electron-structure methods for the most important cohesive features within the material. Even the coupled-cluster theory, the direct use of which is unprecedented for molecular simulations of thermodynamic properties for liquids, then becomes applicable to the description of bulk amorphous materials. Its incorporation in the proposed Monte Carlo simulations promises very high computational accuracy. Bulk-phase equilibrium properties at finite temperatures and pressures, such as density and vaporization enthalpy, as well as response properties such as thermal expansivity and heat capacity that are particularly challenging to predict accurately, are the observables targeted in this work. Superior computational accuracy of the introduced FrAMonC simulations is demonstrated for most target properties (liquid-phase densities, thermal expansivities, and gas–liquid differences in the heat capacities) when compared with established classical or quantum-chemical models that are commonly used to model such properties of bulk liquids.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":"21 19","pages":"9868–9878"},"PeriodicalIF":5.5,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.5c01214","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145079155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Geometric Direct Minimization for Low-Spin Restricted Open-Shell Hartree–Fock Theory","authors":"Hugh G. A. Burton*,&nbsp;","doi":"10.1021/acs.jctc.5c00898","DOIUrl":"10.1021/acs.jctc.5c00898","url":null,"abstract":"<p >It has recently been shown that configuration state functions (CSFs) with local orbitals can provide a compact reference state for low-spin open-shell electronic structures, such as antiferromagnetic states. However, optimizing a low-spin configuration using self-consistent field (SCF) theory has been a long-standing challenge since each orbital must be an eigenfunction of a different Fock operator. We introduce a low-spin restricted open-shell Hartree–Fock (ROHF) algorithm to optimize any CSF at mean-field cost. This algorithm employs quasi-Newton Riemannian optimization on the orbital constraint manifold to provide robust convergence, extending the geometric direct minimization approach to open-shell electronic structures with arbitrary genealogical spin coupling. Numerical calculations on transition metal aquo complexes show improved convergence over existing methodology, while the possibility of local CSF energy minima is demonstrated for iron–sulfur complexes. Finally, open-shell CSFs with different spin coupling patterns are used to qualitatively study the singlet ground state in polyacenes, revealing the onset of polyradical character as the chain length increases.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":"21 19","pages":"9444–9458"},"PeriodicalIF":5.5,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.5c00898","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145074087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}