Journal of Chemical Theory and Computation最新文献

{"title":"Orbital-Free Density Functional Theory for Periodic Solids: Construction of the Pauli Potential.","authors":"Sangita Majumdar, Zekun Shi, Giovanni Vignale","doi":"10.1021/acs.jctc.5c00442","DOIUrl":"https://doi.org/10.1021/acs.jctc.5c00442","url":null,"abstract":"<p><p>The practical success of density functional theory (DFT) is largely credited to the Kohn-Sham approach, which enables the exact calculation of the noninteracting electron kinetic energy via an auxiliary noninteracting system. Yet, the realization of DFT's full potential awaits the discovery of a direct link between the electron density, <i>n</i>, and the noninteracting kinetic energy, <i>T</i>_<i>S</i>[<i>n</i>]. In this work, we address two key challenges toward this objective. First, we introduce a new algorithm for directly solving the constrained minimization problem yielding <i>T</i>_<i>S</i>[<i>n</i>] for periodic densities─a class of densities that, in spite of its central importance for materials science, has received limited attention in the literature. Second, we present a numerical procedure that allows us to calculate the functional derivative of <i>T</i>_<i>S</i>[<i>n</i>] with respect to the density at a constant electron number, also known as the Kohn-Sham potential <i>V</i>_<i>S</i>[<i>n</i>](<b>r</b>). Lastly, the algorithm is augmented with a subroutine that computes the \"derivative discontinuity\", i.e., the spatially uniform jump in <i>V</i>_<i>S</i>[<i>n</i>](<b>r</b>) which occurs upon increasing or decreasing the total number of electrons. This feature allows us to distinguish between \"insulating\" and \"conducting\" densities for noninteracting electrons. The code integrates key methodological innovations such as the use of an adaptive basis set (\"equidensity orbitals\") for wave function expansion and the QR decomposition to accelerate the implementation of the orthogonality constraint. Notably, we derive a closed-form expression for the Pauli potential in one dimension, expressed solely in terms of the input density without relying on Kohn-Sham eigenvalues and eigenfunctions. We validate this method on one-dimensional periodic densities, achieving results within \"chemical accuracy\".</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144186072","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":"FC2DES: Modeling 2D Electronic Spectroscopy for Harmonic Hamiltonians.","authors":"Lucas Allan, Tim J Zuehlsdorff","doi":"10.1021/acs.jctc.5c00349","DOIUrl":"https://doi.org/10.1021/acs.jctc.5c00349","url":null,"abstract":"<p><p>Two-dimensional electronic spectroscopy (2DES) can provide detailed insight into the energy transfer and relaxation dynamics of chromophores by directly measuring the nonlinear response function of the system. However, experiments are often difficult to interpret, and the development of computationally affordable approaches to simulate experimental signals is desirable. For linear spectroscopy, optical spectra of small to medium-sized molecules can be efficiently calculated in the Franck-Condon approach. Approximating the nuclear degrees of freedom as harmonic around the ground- and excited-state minima, closed-form expressions for the exact finite-temperature linear response function can be derived using known solutions for the propagation operator between normal mode coordinate sets, fully accounting for Duschinsky mode-mixing effects. In the present work, we demonstrate that a similar approach can be utilized to yield analogous closed-form expression for the finite-temperature nonlinear (third-order) response function of harmonic nuclear Hamiltonians. The resulting approach, named FC2DES, is implemented on graphics processing units, allowing efficient computations of 2DES signals for medium-sized molecules containing hundreds of normal modes. Benchmark comparisons against the widely used cumulant method for computing 2DES signals are performed on small model systems, as well as the nile red molecule. We highlight the advantages of the FC2DES approach, especially in systems with moderate Duschinsky mode mixing and for long delay times in the nonlinear response function, where low-order cumulant approximations are shown to fail.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144180458","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":"Multi-Level Coupled-Cluster Description of Crystal Lattice Energies.","authors":"Krystyna Syty, Grzegorz Czekało, Khanh Ngoc Pham, Marcin Modrzejewski","doi":"10.1021/acs.jctc.5c00428","DOIUrl":"https://doi.org/10.1021/acs.jctc.5c00428","url":null,"abstract":"<p><p>The many-body expansion (MBE) of the lattice energy enables an ab initio description of molecular solids using correlated wave function approximations. However, the practical application of MBE requires computing the large number of <i>n</i>-body contributions efficiently. To this end, we employ a multi-level coupled-cluster approach which adapts the approximation level based on interaction type and intermolecular distance. The high-level method, including connected triple excitations, is applied only to monomer relaxation and dimer interactions roughly within the first and second coordination shells. Long-range dimers and trimers are treated using a simplified coupled-cluster description based on the random-phase approximation (RPA). A key feature is an energy correction which mitigates the underbinding error of the base RPA. Convergence to the bulk limit is accelerated by the addition of the periodic Hartree-Fock correction. The proposed approach is validated against recent diffusion Monte Carlo reference data for the X23 data set, achieving a mean absolute error of 3.1 kJ/mol, i.e., chemical accuracy for absolute lattice energies.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144172215","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":"Analytical Gradient Theory for Density-Fitted Exact Two-Component Hartree-Fock, State-Specific Complete Active Space Self-Consistent Field, and Second-Order Møller-Plesset Perturbation Theories.","authors":"Jae Woo Park","doi":"10.1021/acs.jctc.5c00405","DOIUrl":"https://doi.org/10.1021/acs.jctc.5c00405","url":null,"abstract":"<p><p>The exact two-component (X2C) relativistic quantum chemistry calculations can be used to describe scalar relativistic effects and spin-orbit couplings at reasonable computational cost. However, they have limited applicability to wave function-based quantum chemistry methods, particularly geometric optimizations and dynamics simulations, owing to the high computational demands of these methods in sizable molecular systems. In this work, we report our implementation of an analytical gradient algorithm with a density-fitting approximation for Hartree-Fock, state-specific complete active space self-consistent field (CASSCF), and second-order Møller-Plesset perturbation theory (MP2) calculations with the X2C one-electron Hamiltonian. This implementation uses a second-order orbital optimization scheme to facilitate convergence in X2C-CASSCF calculations, as well as a response (<i>Z</i>-vector) equation for evaluation of the X2C-MP2 nuclear gradient. We demonstrate the applicability of the algorithm for optimization of the geometry of Ir(ppy)₂(bpy)⁺ and evaluate its computational cost and parallelization (multithreading) efficiency.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144179690","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 Quantum Computational Method for Corrosion Inhibition.","authors":"Naman Jain, Rosa Di Felice","doi":"10.1021/acs.jctc.5c00469","DOIUrl":"https://doi.org/10.1021/acs.jctc.5c00469","url":null,"abstract":"<p><p>We present a hybrid classical-quantum computational pipeline for the determination of adsorption energies of a benzotriazole molecule on an aluminum alloy surface relevant for the transport industry, in particular to address the corrosion problem. The molecular adsorbate and substrate alloy were selected by interrogating molecular and materials databases, in search for desired criteria. The protocol can be generalized to other surfaces with arbitrary orientation and chemical composition, as well as to other molecular adsorbates. It includes three main steps based on mean-field electronic structure calculations, embedding theories and quantum algorithms. The quantum computing step demonstrated here with the variational quantum eigensolver is amenable to any other reliable quantum algorithm for ground-state energy estimation. Excited-state energies can also be taken into account in the quantum computing step, if the target reaction involves excited states.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144172209","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":"Approximation to Second Order N-Electron Valence State Perturbation Theory: Limiting the Wave Function within Singles.","authors":"Yang Guo, Katarzyna Pernal","doi":"10.1021/acs.jctc.5c00582","DOIUrl":"https://doi.org/10.1021/acs.jctc.5c00582","url":null,"abstract":"<p><p>Inspired by the linearized adiabatic connection (AC0) theory, an approximation to second-order N-electron valence state perturbation theory (NEVPT2) has been developed, termed NEVPT within singles (NEVPTS). This approach utilizes amplitudes derived from approximate single-excitation wave functions, requiring only 3rd-order reduced density matrices (RDMs). Consequently, it avoids the computational bottleneck associated with the construction of 4th-order RDMs in NEVPT2. The NEVPTS method demonstrates comparable performance to NEVPT2 in describing potential energy curves for diatomic molecules and singlet-triplet gaps in biradicals, while achieving superior accuracy to AC0 in these applications. For excitation energies of organic molecules, NEVPTS is less accurate than NEVPT2. The overall performance and computational costs of the NEVPTS method lie between those of NEVPT2 and AC0.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144172211","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":"MA(R/S)TINI 3: An Enhanced Coarse-Grained Force Field for Accurate Modeling of Cyclic Peptide Self-Assembly and Membrane Interactions.","authors":"Alfonso Cabezón, Rebeca Garcia-Fandino, Ángel Piñeiro","doi":"10.1021/acs.jctc.5c00126","DOIUrl":"https://doi.org/10.1021/acs.jctc.5c00126","url":null,"abstract":"<p><p>Self-assembled nanotubes (SCPNs) formed by alternating chirality α-Cyclic Peptides (d,l-α-CPs) have presented interesting biological applications, such as antimicrobial activity or ion transmembrane transport. Due to difficulties to follow these processes with experimental techniques, Molecular Dynamics (MD) simulations have been commonly used to understand the mechanism that led to their biological activity. However, the high computational cost of atomic resolution simulations makes them unsuitable for simulating dynamic processes involving multiple units like their self-assembly in different environments. In this regard, coarse-grain (CG) models might represent a more feasible option. However, general coarse-grained force fields such as MARTINI do not explicitly account for noncovalent interactions, such as hydrogen bonding, which are essential for secondary structure formation and the self-assembly of proteins and peptides. This problem becomes particularly important when simulating CPs due to the specific directionality of their interactions. In a previous work, it has been proven how MARTINI classical parametrization overestimated the self-assembly of CPs not distinguishing parallel and antiparallel interactions as well as allowing forbidden rotational angles. The so-called MA(R/S)TINI force field fixed the problem by including two extra particles into the backbone bead while preserving the behavior of several CP sequences in the presence of different membrane models. However, this new parametrization presented a much higher CP-CP interaction energy, being another critical issue for self-assembly overestimation. The release of MARTINI 3 expanded the scope of the force field by introducing new particles and labels specifically tailored to improve the representation of noncovalent interactions. Nevertheless, since it uses the same mapping strategy for protein backbones, this new version also failed at capturing the specific directionality of CPs. Taking advantage of the new possibilities offered by MARTINI 3, MA(R/S)TINI has been updated in the present work. This new version uses a new mapping of CPs based on original beads of the force field and releases the restraints previously imposed on the lateral side chains of the CPs. This new parameterization fixes the formerly overestimated interaction energy between CPs in both parallel and antiparallel orientations, while preserving the advantages of the previous version of MA(R/S)TINI. The new parametrization provided in the present work is aimed to facilitate the understanding, design, and optimization of new bioactive CPs based on CG-MD simulations.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144172213","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":"Automated Microsolvation for Minimum Energy Path Construction in Solution.","authors":"Paul L Türtscher, Markus Reiher","doi":"10.1021/acs.jctc.5c00245","DOIUrl":"https://doi.org/10.1021/acs.jctc.5c00245","url":null,"abstract":"<p><p>Describing chemical reactions in solution on a molecular level is a challenging task due to the high mobility of weakly interacting solvent molecules which requires configurational sampling. For instance, polar and protic solvents can interact strongly with solutes and may interfere in reactions. To define and identify representative arrangements of solvent molecules modulating a transition state is a nontrivial task. Here, we propose to monitor their active participation in the decaying normal mode at a transition state, which defines active solvent molecules. Moreover, it is desirable to prepare a low-dimensional microsolvation model in a well-defined, fully automated, high-throughput, and easy-to-deploy fashion, which we propose to derive in a stepwise protocol. First, transition state structures are optimized in a sufficiently solvated quantum-classical hybrid model, which are subjected to a redefinition of a then reduced quantum region. From the reduced model, minimally microsolvated structures are extracted that contain only active solvent molecules. Modeling the remaining solvation effects is deferred to a continuum model. To establish an easy-to-use free-energy model, we combine the standard thermochemical gas-phase model with a correction for the cavity entropy in solution. We assess our microsolvation and free-energy models for methanediol formation from formaldehyde; for the hydration of carbon dioxide (which we consider in a solvent mixture to demonstrate the versatility of our approach); and, finally, for the chlorination of phenol with hypochlorous acid.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144155239","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":"Short-Range Δ-Machine Learning: A Cost-Efficient Strategy to Transfer Chemical Accuracy to Condensed Phase Systems.","authors":"Bence Balázs Mészáros, András Szabó, János Daru","doi":"10.1021/acs.jctc.5c00367","DOIUrl":"https://doi.org/10.1021/acs.jctc.5c00367","url":null,"abstract":"<p><p>DFT-based machine-learning potentials (MLPs) are now routinely trained for condensed-phase systems, but surpassing DFT accuracy remains challenging due to the cost or unavailability of periodic reference calculations. Our previous work ( <i>Phys. Rev. Lett.</i> 2022, 129, 226001) demonstrated that high-accuracy periodic MLPs can be trained within the CCMD framework using extended yet finite reference calculations. Here, we introduce <i>short-range</i> Δ<i>-Machine Learning</i> (srΔML), a method that starts from a baseline MLP trained on low-level periodic data and adds a Δ-MLP correction based on high-level cluster calculations at the CC level. Applied to liquid water, srΔML reduces the required cluster size from (H₂O)₆₄ to (H₂O)₁₅ and significantly lowers the number of clusters needed, resulting in a 50-200× reduction in computational cost. The resulting potential closely reproduces the target CC potential and accurately captures both two- and three-body structural descriptors.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144172217","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":"<i>Multiple-Basin Go̅-Martini</i> for Investigating Conformational Transitions and Environmental Interactions of Proteins.","authors":"Song Yang, Chen Song","doi":"10.1021/acs.jctc.5c00256","DOIUrl":"10.1021/acs.jctc.5c00256","url":null,"abstract":"<p><p>Proteins are inherently dynamic molecules, and their conformational transitions among various states are essential for numerous biological processes, which are often modulated by their interactions with surrounding environments. Although molecular dynamics (MD) simulations are widely used to investigate these transitions, all-atom (AA) methods are often limited by short time scales and high computational costs, and coarse-grained (CG) implicit-solvent Go̅-like models are usually incapable of studying the interactions between proteins and their environments. Here, we present an approach called Multiple-basin Go̅-Martini, which combines the recent Go̅-Martini model with an exponential mixing scheme to facilitate the simulation of spontaneous protein conformational transitions in explicit environments. We demonstrate the versatility of our method through five diverse case studies: GlnBP, Arc, Hinge, SemiSWEET, and TRAAK, representing ligand-binding proteins, fold-switching proteins, <i>de novo</i> designed proteins, transporters, and mechanosensitive ion channels, respectively. Multiple-basin Go̅-Martini offers a new computational tool for investigating protein conformational transitions, identifying key intermediate states, and elucidating essential interactions between proteins and their environments, particularly protein-membrane interactions. In addition, this approach can efficiently generate thermodynamically meaningful data sets of protein conformational space, which may enhance deep learning-based models for predicting protein conformation distributions.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"5304-5321"},"PeriodicalIF":5.7,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12120924/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143952996","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}