The Journal of Physical Chemistry B最新文献

{"title":"Conformational Transition and Recognition Mechanism of Eukaryotic Riboswitches Powered by Thiamine Pyrophosphate Analogues: An Elucidation through Multiple Short Molecular Dynamics Simulations and Markov Model","authors":"Jianzhong Chen*,&nbsp;, ,&nbsp;Jian Wang,&nbsp;, ,&nbsp;Wei Wang,&nbsp;, ,&nbsp;Wanchun Yang,&nbsp;, ,&nbsp;Lu Zhao,&nbsp;, and ,&nbsp;Jing Su,&nbsp;","doi":"10.1021/acs.jpcb.5c04050","DOIUrl":"10.1021/acs.jpcb.5c04050","url":null,"abstract":"<p >Understanding the ligand-mediated conformational changes in eukaryotic riboswitches is crucial for elucidating their functional roles. In this study, multiple short molecular dynamics simulations, followed by Markov model analysis, were conducted to investigate how the binding of ligands such as three thiamine pyrophosphate analogues (TPP, PYI, and D2X) influences the conformational transitions of eukaryotic riboswitches. Our findings indicate that the presence of these ligands induces a greater number of conformational states and alters the relative orientation of ligands to key nucleotides, thereby impacting ligand-riboswitch recognition. The ligands TPP, PYI, and D2X were found to exert distinct effects on the conformations of specific structural regions, including P1, P4, P5, and L3 and junctions J23 and J45. This suggests that the dynamic nature of the riboswitch of eukaryotic riboswitches is highly dependent on the conformational responses within these regions, also supported by our principal component analysis. Additionally, changes in π–π interactions of ligands with nucleotides G30 and A31, hydrogen bonds formed between ligands and nucleotide, as well as those of a magnesium ion (Mg²⁺) with nucleotides G48, G66, and ligands, may play a significant role in mediating the conformational transitions of eukaryotic riboswitches. Overall, this research is expected to provide valuable theoretical insights into the functions and target roles of riboswitches.</p>","PeriodicalId":60,"journal":{"name":"The Journal of Physical Chemistry B","volume":"129 40","pages":"10256–10271"},"PeriodicalIF":2.9,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145147101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multiscale Analysis of Lubricating Grease: Molecular Self-Assembly, Shear Behavior, and Machine Learning-Assisted Viscosity Prediction","authors":"Dongjie Liu,&nbsp;, ,&nbsp;Jingyi Wang,&nbsp;, ,&nbsp;Zilu Liu,&nbsp;, ,&nbsp;Wenjun Yuan,&nbsp;, ,&nbsp;Jinjia Wei,&nbsp;, and ,&nbsp;Fei Chen*,&nbsp;","doi":"10.1021/acs.jpcb.5c05894","DOIUrl":"10.1021/acs.jpcb.5c05894","url":null,"abstract":"<p >Lubricating grease is a semisolid material widely used in various mechanical systems, composed of base oil, thickeners, and additives. The network structures formed by thickeners offer grease special rheological properties. The viscosity of grease, a key indicator of its lubricating performance, is affected by the combined influence of temperature, shear rate, and thickener ratio. In this research, via molecular dynamics simulations and quantum chemistry calculations, combined with machine learning methods, we first demonstrate the self-assembly behavior of the three-dimensional network structure of lithium-based lubricating grease and identify three structural components crucial for network formation: COO^––Li⁺–COO^–, COO^––Li⁺–OH, and OH–OH. Electrostatic interactions mainly drive the self-assembly of thickeners, with hydrogen bonds also playing a role. Nonequilibrium molecular dynamics simulations are conducted to calculate viscosities under different shear rates, temperatures, and thickener ratios. The results show significant shear thinning with increasing shear rate and temperature, and the viscosity increases with increasing thickener ratios. Machine learning algorithms are applied to predict grease viscosities, with ensemble models using the boosting method providing the most accurate prediction performance (coefficients of determination over 0.985). Feature importance and Shapley additive explanation analysis indicate that the order of feature importance is shear rate &gt; temperature &gt; thickener ratio, in which shear rate and temperature have negative effects on the predicted values , whereas thickener ratio has a positive effect. This research offers molecular insights into the formation of lithium-based grease networks, helps us understand its rheological behavior, which is affected by multiple factors, and provides guidance for designing lubricating grease.</p>","PeriodicalId":60,"journal":{"name":"The Journal of Physical Chemistry B","volume":"129 40","pages":"10603–10620"},"PeriodicalIF":2.9,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145147221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring Protic and Aprotic Solvent Effects on the Molecular Properties of Furfurals in Ionic Liquids","authors":"Sweta Jha,&nbsp; and ,&nbsp;Praveenkumar Sappidi*,&nbsp;","doi":"10.1021/acs.jpcb.5c03227","DOIUrl":"10.1021/acs.jpcb.5c03227","url":null,"abstract":"<p >Furfurals serve as a pivotal, suitable biomass-derived platform chemicals for producing assorted value-added chemicals, biofuels, and biochemicals. Ionic liquids (ILs) are used to form various furfurals from lignocellulosic biomass (LCB). However, different forms of furfurals interact differently with imidazolium-based ionic liquids (IMILs), making their separation from the ILs difficult. In this study, we perform molecular dynamics simulations to investigate the performance of different furfurals in the presence of 1-butyl-3-methylimidazolium tetrafluoroborate [BMIM][BF₄], the protic solvent formic acid (FA), and the aprotic solvent hexamethylphosphoramide (HMPA). We consider seven different furfurals with distinct physiochemical properties, such as 2,5-bis(hydroxymethyl)furan (2BHF), 2,5-diformylfuran (2DFF), 2,5-dimethylfuran (2DMF), 2-methylfuran (2MF), furan-2,5-carboxylic acid (FCA), 2-furoic acid (FUA), and furan (FUR). We performed various structural, dynamic, and detailed thermodynamic analyses to understand their fundamental molecular behavior. In-depth atomic-level insights indicate that furfurals exhibit significant interaction with the solvent HMPA compared to FA. Based on the solvation free energy (Δ<i>G</i>_solv) and partition coefficient (log <i>P</i>) values, HMPA enhances the extraction ability of furfurals from the ILs. Overall, the results presented in this article provide guidance on furfural interaction behavior in the presence of protic and aprotic solvents for effective extraction.</p>","PeriodicalId":60,"journal":{"name":"The Journal of Physical Chemistry B","volume":"129 40","pages":"10392–10406"},"PeriodicalIF":2.9,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145147190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Statistical Physics-Based Approaches to Model the Function and Complexation of Disordered Proteins","authors":"Austin Haider,&nbsp;, ,&nbsp;Kari Gaalswyk,&nbsp;, ,&nbsp;Lilianna Houston,&nbsp;, ,&nbsp;Nicholas J. Ose,&nbsp;, ,&nbsp;S. Banu Ozkan*,&nbsp;, and ,&nbsp;Kingshuk Ghosh*,&nbsp;","doi":"10.1021/acs.jpcb.5c05422","DOIUrl":"10.1021/acs.jpcb.5c05422","url":null,"abstract":"<p >Functional classification of intrinsically disordered proteins (IDP) is a challenge due to their low sequence homology and lack of stable tertiary structure. We embrace this challenge to classify a model system of two IDPs─NCBD and CID─that have coevolved and for which both ancestral and extant sequences are available, along with quantitative binding data. One of these sequences, NCBD, exhibits partial secondary structure, while the other (CID) remains highly disordered and is highly charged. We classify these sequences using statistical physics-derived sequence-dependent interaction maps that predict distance maps (ensemble average distances between arbitrary residue pairs). We also use sequence-specific dynamic profiles for further comparison. Our findings show that CID proteins can be classified into two major groups due to two distinct types of patterns in their electrostatic interaction maps. Classification of CIDs using nonelectrostatic patterning yields diverging predictions, illustrating the importance of accurately modeling long-range electrostatic interactions. Conversely, the classification of NCBD sequences generally reaches a consensus when physics-based noncharge patterning metrics are applied, along with the dynamical profiles. Furthermore, we used these sequence-dependent metrics and dynamical profiles to quantitatively model the binding affinities between the two IDPs. Surprisingly, we find that multiple physics-based sequence metrics quantitatively recapitulate the binding affinities between CID and NCBD variants, linking sequence composition and patterning to their emergent function. This integrated framework provides a generalizable strategy for classifying IDPs and predicting complexation behavior, offering new avenues for probing sequence–function relationships in disordered protein systems.</p>","PeriodicalId":60,"journal":{"name":"The Journal of Physical Chemistry B","volume":"129 40","pages":"10285–10297"},"PeriodicalIF":2.9,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145147269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Structure–Property Relationship between Hard Segments of Shape Memory Polyurethane Copolymers and Interchain Hydrogen Bonds: A Comprehensive Theoretical Study","authors":"Yuliia Didovets,&nbsp; and ,&nbsp;Mateusz Z. Brela*,&nbsp;","doi":"10.1021/acs.jpcb.5c03305","DOIUrl":"10.1021/acs.jpcb.5c03305","url":null,"abstract":"<p >Shape memory polymers have received increased interest from the scientific community, because of their extraordinary properties. Interchain hydrogen bonds play an important role in the shape memory property of polyurethane copolymers. This paper provides a comprehensive description of the interchain interactions’ network of Hard Segments within shape memory polyurethane copolymers. Model systems included Hard Segments of different chemical compositions, mainly based on hexamethylene diisocyanate (HDI), dicyclohexylmethane-4,4′-diisocyanate (HMDI), toluene-2,4-diisocyanate (TDI), and diphenylmethane-4,4′-diisocyanate (MDI). <i>Ab initio</i> molecular dynamics was used to describe the reorganization of interchain hydrogen bonds, while the character and strength of hydrogen bonds were determined with the help of interaction energy decomposition (ETS) as well as analysis of the IR spectrum data. HDI- and MDI-based Hard Segments showed the formation of interchain hydrogen bonds of the highest strength, while the TDI-based Hard Segments formed the weakest interactions. The HMDI-based Hard Segments showed medium performance. The paper also demonstrates a direct relationship between the character of interchain hydrogen bonds of the studied hard-segmented models and thermal and mechanical experimental properties of polyurethane copolymers containing corresponding fragments.</p>","PeriodicalId":60,"journal":{"name":"The Journal of Physical Chemistry B","volume":"129 40","pages":"10504–10520"},"PeriodicalIF":2.9,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.jpcb.5c03305","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145147294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-Throughput Virtual Screening of Protein-Catalyzed Capture Agents for Novel Hydrogel-Nanoparticle Fentanyl Sensors","authors":"Armin Shayesteh Zadeh,&nbsp;, ,&nbsp;Alexander J. Winton,&nbsp;, ,&nbsp;Joseph M. Palomba,&nbsp;, and ,&nbsp;Andrew L. Ferguson*,&nbsp;","doi":"10.1021/acs.jpcb.5c04790","DOIUrl":"10.1021/acs.jpcb.5c04790","url":null,"abstract":"<p >Fast, portable, and reliable detection of chemical and biological compounds is an important challenge in many safety and healthcare applications. Chemical sensors based on photonic crystals that use protein-catalyzed capture (PCC) agents as molecular sensors are promising tools for the portable detection of chemical and biological compounds. We present the development and deployment of a high-throughput virtual screening protocol to computationally identify PCC candidates that maximize the binding sensitivity and selectivity for fentanyl. The approach integrates enhanced sampling molecular dynamics free-energy calculations, Gaussian process regression surrogate models, and Bayesian optimization to efficiently navigate the design space of over 1 million PCC candidates, resolve the sensitivity–selectivity Pareto frontier, and identify the top-performing PCC candidates. We analyze the molecular interactions between our top candidates and fentanyl target to propose design rules for high-performance PCC agents to be used for experimental testing and, ultimately, incorporation into next-generation hydrogel–nanoparticle-based chemical sensing devices.</p>","PeriodicalId":60,"journal":{"name":"The Journal of Physical Chemistry B","volume":"129 40","pages":"10568–10583"},"PeriodicalIF":2.9,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145147150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Surprising Role of Urea in Promoting CO2 Hydrate Formation: Enhanced Molecular Diffusivity via Weakening of the Hydrogen-Bond Network","authors":"Jun-Wei Hsu,&nbsp;, ,&nbsp;David T. Wu,&nbsp;, and ,&nbsp;Shiang-Tai Lin*,&nbsp;","doi":"10.1021/acs.jpcb.5c04817","DOIUrl":"10.1021/acs.jpcb.5c04817","url":null,"abstract":"<p >Urea is known to act as a kinetic promoter for CO₂ hydrate formation by reducing the nucleation induction time. Recent molecular simulation studies suggest that urea facilitates CO₂ hydrate growth by lowering the mass transfer resistance of CO₂ in water, as evidenced by increased diffusivity of both CO₂ and water. However, the enhancement of water diffusivity is counterintuitive, given urea’s relatively large size, strong affinity for water, and its tendency to increase the fraction of hydrate-like water structures─conditions typically associated with reduced mobility. To resolve this apparent contradiction, we employ molecular dynamics simulations to examine how urea modifies the hydrogen-bonding network of water, considering both structural and energetic aspects. Our results reveal that urea subtly disrupts the water hydrogen-bond network by competing for bonding sites. The resulting urea–water and adjacent water–water hydrogen bonds are weaker than those in bulk water–water interactions, leading to a locally weakened hydrogen-bond network. This reduction in hydrogen-bond strength lowers the energetic barrier for water diffusion, thereby enhancing molecular mobility. These findings reconcile the seemingly paradoxical increase in both water diffusivity and hydrate-like structuring in the presence of urea, offering new insight into how small organic solutes modulate water structure and dynamics in hydrate-forming environments.</p>","PeriodicalId":60,"journal":{"name":"The Journal of Physical Chemistry B","volume":"129 40","pages":"10440–10450"},"PeriodicalIF":2.9,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.jpcb.5c04817","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145147235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of Ligands on the Ion–Ion Selectivity of Ligand-Appended-Pillar[n]arene Channels","authors":"Tyler J. Duncan,&nbsp;, ,&nbsp;Harnoor Singh Sachar,&nbsp;, ,&nbsp;Siqi Wang,&nbsp;, ,&nbsp;Harekrushna Behera,&nbsp;, ,&nbsp;Manish Kumar,&nbsp;, and ,&nbsp;Venkat Ganesan*,&nbsp;","doi":"10.1021/acs.jpcb.5c03872","DOIUrl":"10.1021/acs.jpcb.5c03872","url":null,"abstract":"<p >Ligand-appended pillar[5]arene (LAP) channels are emerging as a promising platform for ion-selective membranes. In this study, we investigated the ion selectivities of three LAP channels functionalized with distinct ligands: diglycolamine, carbamoylmethyl phosphine oxide, and propionamide phosphonic acid. These ligands were chosen based on their demonstrated affinities for lanthanides in solvent extraction studies. We examined the selectivity of each channel toward a series of monovalent, divalent, and trivalent ions: Li⁺, Na⁺, K⁺, Mg²⁺, Ca²⁺, La³⁺, Eu³⁺, and Yb³⁺. To quantify ion–channel interactions and the energetics of translocation, we computed the potential of mean force (PMF) profiles for each ion. These PMFs were subsequently recast into permeability coefficients, enabling a direct evaluation of ion permselectivity. Our results reveal distinct selectivity patterns governed by the chemical nature of the appended ligands. The diglycolamine-functionalized channel exhibits strong interactions with monovalent ions, leading to replication of the Li⁺ bulk hydration shell within the channel. This promotes preferential transport Li⁺ ions while effectively excluding divalent and trivalent species. In contrast, the carbamoylmethyl phosphine oxide-functionalized channel displays a reduced selectivity between monovalent ions while similarly exhibiting an effective rejection of divalent and trivalent ions. This arises from steric hindrance around channel-lining oxygens imposed by the ligand’s bulky phenyl groups which limits heavy ion coordination and promotes retention of hydration shells effectively increasing effective ion size. The propionamide phosphonic acid-functionalized channel exhibits a different trend, favoring ions with lower hydration free energies, with K⁺ ions showing enhanced permeation. These findings highlight the critical role of ligand–ion interactions in modulating ion selectivity within LAP channels. In particular, the strong coordination exhibited by diglycolamine and propionamide phosphonic acid ligands significantly influences the ion transport energetics and selectivity profiles.</p>","PeriodicalId":60,"journal":{"name":"The Journal of Physical Chemistry B","volume":"129 40","pages":"10311–10324"},"PeriodicalIF":2.9,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145135998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Molecular Simulations of Ladderane Lipid Bilayers as Initial Models for Anammox Bacteria","authors":"Vincent Zhao,&nbsp; and ,&nbsp;Jeffery B. Klauda*,&nbsp;","doi":"10.1021/acs.jpcb.5c04432","DOIUrl":"10.1021/acs.jpcb.5c04432","url":null,"abstract":"<p >Ladderanes uniquely distinguish themselves from other lipids by possessing fused cyclobutane and cyclohexane rings down the length of their hydrocarbon tails. Found naturally only in anaerobic ammonium-oxidizing (anammox) bacteria and localized specifically to the anammoxosome, the compartmentalized site of anammox oxidation, the exact function and significance of ladderane containing phospholipids is still unclear. In this study, the all-atom CHARMM36 (C36) lipid force field is used to simulate two pure ladderane phosphatidylcholine bilayers, one containing only [3]-ladderane and the other containing both [3]- and [5]-ladderane. Values for surface areas per lipid (SA/lip), area compressibility, electron density profiles (EDPs), and bilayer thickness were calculated. While our measured values for area compressibility and EDPs are in line with previous simulation work involving ladderanes, our use of updated C36 protocols yielded a higher SA/lip and lower bilayer thickness, suggesting looser bilayer packing and less ordering of lipid tails than previously thought. We also report for the first time calculated values for order parameters, lipid wobble, interdigitation, and electrostatic potential for pure ladderane bilayers. The current model presents a baseline for future modeling of physiologically accurate anammox bacterial membranes and for studying of the function of ladderane lipids.</p>","PeriodicalId":60,"journal":{"name":"The Journal of Physical Chemistry B","volume":"129 40","pages":"10325–10332"},"PeriodicalIF":2.9,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145147176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Toward Improving Multiple Time Step QM/MM Simulations with Δ-Machine Learning","authors":"Reilly Osadchey,&nbsp;, ,&nbsp;Kwangho Nam*,&nbsp;, and ,&nbsp;Qiang Cui*,&nbsp;","doi":"10.1021/acs.jpcb.5c05255","DOIUrl":"10.1021/acs.jpcb.5c05255","url":null,"abstract":"<p >Semiempirical methods are popular for QM/MM simulations of chemical reactions in the condensed phase due to their immense speedup compared to higher-level <i>ab initio</i> or density functional theory (DFT) methods but can be much less accurate depending on the system of interest. Multiple time step (MTS) methods can improve the accuracy of semiempirical QM/MM simulations by using higher-level calculations at less frequent outer time steps, yet accurate results and efficient sampling require the low- and high-level methods to be sufficiently similar. In this work, we show the limitations of standard semiempirical methods (e.g., AM1) for MTS applications. In a condensed-phase reaction of proton transfer from water to methyl phosphate, for which DFT (B3LYP) is used as the high-level method, we can only reach an outer time step of 4, even with the stochastic isokinetic thermostat. We then explore the value of employing Δ-machine learning to enhance the efficiency of MTS QM/MM simulations. As an initial step, we train neural network potentials and Δ-learning corrections to the AM1 method for the corresponding gas-phase reaction. We show that Δ-corrections outperform ML potentials and that the amount of training data has a major impact on the accuracy and transferability of the learned correction. In a gas-phase MTS simulation with appropriate machine-learned Δ-corrections, we can reach an outer integration frequency of 25 for a nearly exact result compared to B3LYP and 30 if we accept an error of 0.3 kcal·mol^–1 for the free energy profile. The study validates and provides guidance to Δ-learning based MTS simulations, setting the stage for future development and realistic applications in the condensed phase.</p>","PeriodicalId":60,"journal":{"name":"The Journal of Physical Chemistry B","volume":"129 40","pages":"10451–10466"},"PeriodicalIF":2.9,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145147281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}