Journal of Chemical Theory and Computation最新文献_第2页

Method to Compute the Interaction Energy of a Molecule in Ground and Excited States with a Discrete Environment: The Case of Uracil in Water.

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-02-28 DOI: 10.1021/acs.jctc.4c01375

Claudio Amovilli, Franca Maria Floris

{"title":"Method to Compute the Interaction Energy of a Molecule in Ground and Excited States with a Discrete Environment: The Case of Uracil in Water.","authors":"Claudio Amovilli, Franca Maria Floris","doi":"10.1021/acs.jctc.4c01375","DOIUrl":"https://doi.org/10.1021/acs.jctc.4c01375","url":null,"abstract":"In this work, we present a method that is able to compute the interaction energy of a system of interest, in the ground or excited state, with an arbitrary number of water molecules representing the environment. As a test case, we take uracil. We considered five clusters containing 1, 12, 24, 26, and 37 water molecules. The method is a first step toward a more general approach to determining the interaction energy between a molecule, treated at a high level of theory, and a complex molecular environment that can be described as an explicit solvent model. Ground and excited electronic states of uracil were optimized in free space at the variational quantum Monte Carlo (QMC) level. In this way, we sampled electronic configurations that are used to compute all the contributions to the interaction energy with the environment. Excitation energies from the ground state were computed at the diffusion Monte Carlo (DMC) level. Numerical results are in agreement with available literature data on the solvatochromic effect on the n → π* and π → π* vertical transitions of uracil in water. Our method provides specific contributions arising from Pauli repulsion, electrostatic, polarization, and dispersion interactions.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143530882","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}

引用次数: 0

DESC: An Automated Strategy to Efficiently Account for Dynamic Environment Effects in Solution. DESC：在解决方案中有效考虑动态环境影响的自动策略。

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-02-28 DOI: 10.1021/acs.jctc.5c00002

Albert Masip-Sánchez, Josep M Poblet, Xavier López

{"title":"DESC: An Automated Strategy to Efficiently Account for Dynamic Environment Effects in Solution.","authors":"Albert Masip-Sánchez, Josep M Poblet, Xavier López","doi":"10.1021/acs.jctc.5c00002","DOIUrl":"https://doi.org/10.1021/acs.jctc.5c00002","url":null,"abstract":"The properties and dynamic behavior of molecules in liquid solutions depend critically on the solvent and other species, or cosolutes, including electrolytes (if present), especially when molecular association or pairing occurs. In Quantum Mechanical (QM) calculations, the electronic structure of molecules in liquid solution is typically obtained with implicit solvent models (ISMs). However, ISMs cannot differentiate between, for example, cation types (e.g., Cs+ versus nBu4N+), leading to limited accuracy in capturing possible solute-specific interactions. Addressing this issue in QM calculations often requires an explicit treatment of the cosolute, typically a counterion, a challenging approach due to the definition of representative cosolute positions, numerical convergence, and high computational cost for bulky species. A new computational strategy called Dynamic Environment in Solution by Clustering (DESC) is herein presented, which leverages classical Molecular Dynamics (MD) data to feed QM calculations, enabling the inclusion of counterion-specific effects with greater detail and efficiency than ISMs. DESC is particularly advantageous in cases where ion pairing/aggregation is significant, offering chemically representative QM results at a small fraction of the computational cost associated with the explicit inclusion of counterions in the model. This work presents MD data on polyoxometalate-counterion-solvent systems, introduces the philosophy behind DESC and its operational details, and applies it to polyoxometalate solutions and other relevant systems, comparing outcomes with benchmark QM/ISM calculations.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143522088","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}

引用次数: 0

Parallel Multicoordinate Descent Methods for Full Configuration Interaction.

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-02-28 DOI: 10.1021/acs.jctc.4c01530

Yuejia Zhang, Weiguo Gao, Yingzhou Li

引用次数: 0

Multiscale Force Field Model Based on a Graph Neural Network for Complex Chemical Systems.

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-02-27 DOI: 10.1021/acs.jctc.4c01449

Zhaoxin Xie, Yanheng Li, Yijie Xia, Jun Zhang, Sihao Yuan, Cheng Fan, Yi Isaac Yang, Yi Qin Gao

{"title":"Multiscale Force Field Model Based on a Graph Neural Network for Complex Chemical Systems.","authors":"Zhaoxin Xie, Yanheng Li, Yijie Xia, Jun Zhang, Sihao Yuan, Cheng Fan, Yi Isaac Yang, Yi Qin Gao","doi":"10.1021/acs.jctc.4c01449","DOIUrl":"https://doi.org/10.1021/acs.jctc.4c01449","url":null,"abstract":"Inspired by the QM/MM methodology, the ML/MM approach introduces a new opportunity for multiscale simulation, improving the balance between accuracy and computational efficiency. Benefited from the rapid advancements in molecular embedding methods, density functional theory level quantum mechanical (QM) calculations within the QM/MM framework can be accelerated by several orders of magnitude through the application of machine learning (ML) potential energy surfaces. As a problem inherited from the QM/MM methodology, challenges exist in designing the interactions between machine learning and molecular mechanics (MM) regions. In this study, electrostatic interactions between machine learning and MM atoms are treated by using a graphical neural network based on stationary perturbation theory. In this protocol, we process coordinates and MM charges to yield electrostatic energy and forces, resulting in a high-performance electrostatic embedding ML/MM architecture. The accuracy of the ML/MM energy was validated in aqueous solutions of alanine dipeptide and allyl vinyl ether (AVE). We investigated the transferability of parameters trained from AVE in a single solvent to various other solvents, including water, methanol, dimethyl sulfoxide, toluene, ionic liquids, and water-toluene interface environments. We then established a solvent-free protocol for data set preparation. Comparison of the free energy landscapes of the Claisen rearrangement of AVE in different solvation environments showed the catalytic effect of aqueous solutions, consistent with experiments.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143514039","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}

引用次数: 0

Dual-Level Parametrically Managed Neural Network Method for Learning a Potential Energy Surface for Efficient Dynamics. 学习高效动力学势能面的双层参数管理神经网络方法

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-02-27 DOI: 10.1021/acs.jctc.4c01546

Suman Bhaumik, Dayou Zhang, Yinan Shu, Donald G Truhlar

{"title":"Dual-Level Parametrically Managed Neural Network Method for Learning a Potential Energy Surface for Efficient Dynamics.","authors":"Suman Bhaumik, Dayou Zhang, Yinan Shu, Donald G Truhlar","doi":"10.1021/acs.jctc.4c01546","DOIUrl":"https://doi.org/10.1021/acs.jctc.4c01546","url":null,"abstract":"A general difficulty with machine-learned potential energy surfaces is their unreliability in regions with little or no training data. The goal of the present work is to remedy this by a low-cost method for incorporating well understood features of potential energy surfaces into an efficient data-driven machine learning algorithm. Our focus is on regions where conventional surface fitting does not need large amounts of accurate data, in particular, geometries with large separations of subsystems-where it is well recognized that the potential should reach its asymptotic form-and geometries with very close atoms-where the potential should be repulsive enough to prevent trajectories from reaching classically inaccessible regions but need not be highly quantitative. The new method involves a neural network (NN) with a parametrically managed activation function (PMAF) and two levels of electronic structure, a higher level (HL) and a lower level (LL). The resulting NN is called a dual-level parametrically managed neural network (DL-PMNN). For the present example, the HL is an accurate density functional method (CF22D/may-cc-pVTZ), and the LL is an inexpensive density functional method (MPW1K/MIDIY). We use the LL to ensure correct behavior of the potential at large and small distances; the goal is to reach HL accuracy for dynamics without making HL calculations in regions where the LL can guide the fit. To illustrate the new method, we fit the potential energy surface for dissociation of the S-H bond of ortho-fluorothiophenol in the ground electronic state, and we show that the method yields a good fit and efficient trajectory calculations without crashes.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143522090","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}

引用次数: 0

Neural-Network-Based Selective Configuration Interaction Approach to Molecular Electronic Structure.

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-02-27 DOI: 10.1021/acs.jctc.4c01479

Yorick L A Schmerwitz, Louis Thirion, Gianluca Levi, Elvar Ö Jónsson, Pavlo Bilous, Hannes Jónsson, Philipp Hansmann

{"title":"Neural-Network-Based Selective Configuration Interaction Approach to Molecular Electronic Structure.","authors":"Yorick L A Schmerwitz, Louis Thirion, Gianluca Levi, Elvar Ö Jónsson, Pavlo Bilous, Hannes Jónsson, Philipp Hansmann","doi":"10.1021/acs.jctc.4c01479","DOIUrl":"10.1021/acs.jctc.4c01479","url":null,"abstract":"By combining Hartree-Fock with a neural-network-supported quantum-cluster solver proposed recently in the context of solid-state lattice models, we formulate a scheme for selective neural-network configuration interaction (NNCI) calculations and implement it with various options for the type of basis set and boundary conditions. The method's performance is evaluated in studies of several small molecules as a step toward calculations of larger systems. In particular, the correlation energy in the N2 molecule is compared with published full CI calculations that included nearly 1010 Slater determinants, and the results are reproduced with only 4 × 105 determinants using NNCI. A clear advantage is seen from increasing the set of orbitals included rather than approaching full CI for a smaller set. The method's high efficiency and implementation in a condensed matter simulation software expands the applicability of CI calculations to a wider range of problems, even extended systems through an embedding approach.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143514070","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}

引用次数: 0

Automatic Generation of Even-Tempered Auxiliary Basis Sets with Shared Exponents for Density Fitting.

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-02-27 DOI: 10.1021/acs.jctc.4c01555

Manuel Díaz-Tinoco, Roberto Flores-Moreno, Bernardo A Zúñiga-Gutiérrez, Andreas M Köster

{"title":"Automatic Generation of Even-Tempered Auxiliary Basis Sets with Shared Exponents for Density Fitting.","authors":"Manuel Díaz-Tinoco, Roberto Flores-Moreno, Bernardo A Zúñiga-Gutiérrez, Andreas M Köster","doi":"10.1021/acs.jctc.4c01555","DOIUrl":"https://doi.org/10.1021/acs.jctc.4c01555","url":null,"abstract":"A new algorithm for the automatic generation of auxiliary basis sets for the variational density fitting (DF) of two-electron Coulomb repulsion and Fock exchange energies is presented. It generates even-tempered primitive Hermite Gaussian auxiliary basis sets with shared exponents according to the underlying orbital basis set. To this end, the auxiliary basis sets, denoted GEN-X2, GEN-X3 and GEN-X4, span the product space of the primary orbital basis set for each element. The accuracy of the GEN-Xn (n = 2, 3 and 4) auxiliary basis sets was tested with the DZVP, 6-31G** and def2-TZVPP orbital basis sets for elements from H to Kr employing a large set of small molecules representing (nearly) each element in its common oxidation states. DF errors below 1 kcal/mol were reached for all systems. Whereas this fitting precision is reached in DF PBE calculations already with the smallest GEN-X2 auxiliary basis set for all test systems corresponding DF Hartree-Fock calculations require GEN-X3 and GEN-X4 for molecules containing second and third row elements (including transition metals), respectively. Most satisfying, in all cases the DF error signs reflect the theoretical variational bounds of the Coulomb and Fock fitting. The computational efficiency of the GEN-Xn auxiliary basis sets was benchmarked by single-point energy calculations of hydrogen saturated MFI zeolite cutouts with up to 1408 atoms.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143522086","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}

引用次数: 0

Markov-Type State Models to Describe Non-Markovian Dynamics.

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-02-26 DOI: 10.1021/acs.jctc.4c01630

Sofia Sartore, Franziska Teichmann, Gerhard Stock

{"title":"Markov-Type State Models to Describe Non-Markovian Dynamics.","authors":"Sofia Sartore, Franziska Teichmann, Gerhard Stock","doi":"10.1021/acs.jctc.4c01630","DOIUrl":"https://doi.org/10.1021/acs.jctc.4c01630","url":null,"abstract":"When clustering molecular dynamics (MD) trajectories into a few metastable conformational states, the assumption of time scale separation between fast intrastate fluctuations and rarely occurring interstate transitions is often not valid. Hence, when we construct a Markov state model (MSM) from these states, the naive estimation of the macrostate transition matrix via simply counting transitions between the states may lead to significantly too-short implied time scales and thus to too-fast population decays. In this work, we discuss advanced approaches to estimate the transition matrix. Assuming that Markovianity is at least given at the microstate level, we consider the Laplace-transform-based method by Hummer and Szabo, as well as a direct microstate-to-macrostate projection, which by design yields correct macrostate population dynamics. Alternatively, we study the recently proposed quasi-MSM ansatz of Huang and co-workers to solve a generalized master equation, as well as a hybrid method that employs MD at short times and MSM at long times. Adopting a one-dimensional toy model and an all-atom folding trajectory of HP35, we discuss the virtues and shortcomings of the various approaches.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143514035","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}

引用次数: 0

Coarse-Grained Model of Disordered RNA for Simulations of Biomolecular Condensates.

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-02-26 DOI: 10.1021/acs.jctc.4c01646

Ikki Yasuda, Sören von Bülow, Giulio Tesei, Eiji Yamamoto, Kenji Yasuoka, Kresten Lindorff-Larsen

{"title":"Coarse-Grained Model of Disordered RNA for Simulations of Biomolecular Condensates.","authors":"Ikki Yasuda, Sören von Bülow, Giulio Tesei, Eiji Yamamoto, Kenji Yasuoka, Kresten Lindorff-Larsen","doi":"10.1021/acs.jctc.4c01646","DOIUrl":"https://doi.org/10.1021/acs.jctc.4c01646","url":null,"abstract":"Protein-RNA condensates are involved in a range of cellular activities. Coarse-grained molecular models of intrinsically disordered proteins have been developed to shed light on and predict single-chain properties and phase separation. An RNA model compatible with such models for disordered proteins would enable the study of complex biomolecular mixtures involving RNA. Here, we present a sequence-independent coarse-grained, two-beads-per-nucleotide model of disordered, flexible RNA based on a hydropathy scale. We parametrize the model, which we term CALVADOS-RNA, using a combination of bottom-up and top-down approaches to reproduce local RNA geometry and intramolecular interactions based on atomistic simulations and in vitro experiments. The model semiquantitatively captures several aspects of RNA-RNA and RNA-protein interactions. We examined RNA-RNA interactions by comparing calculated and experimental virial coefficients and nonspecific RNA-protein interaction by studying the reentrant phase behavior of protein-RNA mixtures. We demonstrate the utility of the model by simulating the formation of mixed condensates consisting of the disordered region of MED1 and RNA chains and the selective partitioning of disordered regions from transcription factors into these and compare the results to experiments. Despite the simplicity of our model, we show that it captures several key aspects of protein-RNA interactions and may therefore be used as a baseline model to study several aspects of the biophysics and biology of protein-RNA condensates.","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143514028","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}

引用次数: 0

Efficient Quantum Estimation of Hamiltonian Spectra via Shallow Circuits.

IF 5.7 1区化学

Journal of Chemical Theory and Computation Pub Date : 2025-02-26 DOI: 10.1021/acs.jctc.4c01601

Pingyu Zhu, Chao Wu, Yang Wang, Jiacheng Liu, Gongyu Xia, Yan Wang, Qilin Zheng, Miaomiao Yu, Chang Zhao, Yuxing Du, Kaikai Zhang, Kun Wang, Ping Xu

引用次数: 0