{"title":"A Simple, Polarizable, Rigid, 3-Point Water Model Using the Direct Polarization Approximation.","authors":"Liangyue W Drew, Michael K Gilson","doi":"10.1021/acs.jctc.5c00603","DOIUrl":"10.1021/acs.jctc.5c00603","url":null,"abstract":"<p><p>We present dPol, a 3-point, rigid, polarizable water model that uses the direct approximation of polarization. We show that, with a moderate computational cost (∼3× slower than TIP3P), dPol achieves additional accuracy over widely used nonpolarizable 3-point rigid water models. Unlike most polarizable force fields, dPol allows the use of a 2 fs time-step with a conventional molecular dynamics integrator. The partial charges and polarizabilities used in dPol are derived from quantum chemistry calculations, while the Lennard-Jones parameters and geometry are adjusted to reproduce liquid properties under ambient conditions. The final dPol water model reproduces key room-temperature physical properties used in training, with a heat of vaporization of 10.43 kcal/mol, a dielectric constant of 80.7, a high-frequency dielectric constant of 1.60, a molecular polarizability of 1.41 Å<sup>3</sup>, a gas-phase dipole moment of 1.89 D, and a mean liquid-phase dipole moment of 2.55 D. Importantly, dPol also closely reproduces properties outside the training set, including the oxygen-oxygen radial distribution function of liquid water, as well as the self-diffusion coefficient (2.3×10<sup>-5</sup> cm<sup>2</sup> s<sup>-1</sup>) and shear viscosity (0.87 mPa s). Predicted temperature-dependent properties are also largely reproduced; although dPol does not correctly place the density maximum, this is not expected to impede successful application of the model to biomolecular systems near room temperature. The dPol water model is, by design, compatible with our AM1-BCC-dPol polarizable electrostatic model for small organic molecules [J. Chem. Theory Comput., 2024, 20, 1293-1305]. These models in combination establish a foundation for the integration of electronic polarizability into efficient force fields for heterogeneous systems of biological and pharmaceutical interest.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"6964-6978"},"PeriodicalIF":5.7,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144574459","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":"Protein Structure-Function Relationship: A Kernel-PCA Approach for Reaction Coordinate Identification.","authors":"Parisa Mollaei, Amir Barati Farimani","doi":"10.1021/acs.jctc.5c00483","DOIUrl":"10.1021/acs.jctc.5c00483","url":null,"abstract":"<p><p>In this study, we propose a Kernel-PCA model designed to capture structure-function relationships in a protein. This model also enables the ranking of reaction coordinates according to their impact on protein properties. By leveraging machine learning techniques, including Kernel and principal component analysis (PCA), our model uncovers meaningful patterns in the high-dimensional protein data obtained from molecular dynamics (MD) simulations. The effectiveness of our model in accurately identifying reaction coordinates has been demonstrated through its application to a G protein-coupled receptor. Furthermore, this model utilizes a residue-level dynamical network approach to uncover correlations in the structural dynamics of residues that are strongly associated with a specific protein property. These findings underscore the potential of our model as a powerful tool for protein structure-function analysis and visualization.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"7122-7130"},"PeriodicalIF":5.7,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144624998","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}
Rafael Bicudo Ribeiro, and , Henrique Musseli Cezar*,
{"title":"","authors":"Rafael Bicudo Ribeiro, and , Henrique Musseli Cezar*, ","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":"21 14","pages":"XXX-XXX XXX-XXX"},"PeriodicalIF":5.7,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.5c00634","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144671677","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":"","authors":"Atanu Paul, and , Ilya Grinberg*, ","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":"21 14","pages":"XXX-XXX XXX-XXX"},"PeriodicalIF":5.7,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.5c00452","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144671708","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}
Liyao Wang, Andrejs Tučs, Songting Ding, Koji Tsuda* and Adnan Sljoka*,
{"title":"","authors":"Liyao Wang, Andrejs Tučs, Songting Ding, Koji Tsuda* and Adnan Sljoka*, ","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":"21 14","pages":"XXX-XXX XXX-XXX"},"PeriodicalIF":5.7,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.5c00175","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144671710","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}
Dilina Perera, Samuel McAllister, Joan Josep Cerdà, Thomas Vogel
{"title":"Confusion-Driven Machine Learning of Structural Phases of a Flexible, Magnetic Stockmayer Polymer.","authors":"Dilina Perera, Samuel McAllister, Joan Josep Cerdà, Thomas Vogel","doi":"10.1021/acs.jctc.5c00381","DOIUrl":"10.1021/acs.jctc.5c00381","url":null,"abstract":"<p><p>We use a semisupervised, neural-network-based machine learning technique, the confusion method, to investigate structural transitions in magnetic polymers, which we model as chains of magnetic colloidal nanoparticles characterized by dipole-dipole and Lennard-Jones interactions. As input for the neural network, we use the particle positions and magnetic dipole moments of equilibrium polymer configurations, which we generate via replica-exchange Wang-Landau simulations. We demonstrate that by measuring the classification accuracy of neural networks, we can effectively identify transition points between multiple structural phases without any prior knowledge of their existence or location. We corroborate our findings by investigating relevant conventional order parameters. Our study furthermore examines previously unexplored low-temperature regions of the phase diagram, where we find new structural transitions between highly ordered helicoidal polymer configurations.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"6729-6742"},"PeriodicalIF":5.7,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144590055","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}
Diship Srivastava, Shreya Mukherjee and Niladri Patra*,
{"title":"","authors":"Diship Srivastava, Shreya Mukherjee and Niladri Patra*, ","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":"21 14","pages":"XXX-XXX XXX-XXX"},"PeriodicalIF":5.7,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.5c00757","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144671681","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":"","authors":"Liangyue W. Drew, and , Michael K. Gilson*, ","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":"21 14","pages":"XXX-XXX XXX-XXX"},"PeriodicalIF":5.7,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.5c00603","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144671696","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}
Mike Pauls, Jan Kubelka, Francesca Plückhahn, Christoph Bannwarth
{"title":"An Efficient Exciton Coupling Scheme Based on Simplified Time-Dependent Density Functional Theory.","authors":"Mike Pauls, Jan Kubelka, Francesca Plückhahn, Christoph Bannwarth","doi":"10.1021/acs.jctc.4c01788","DOIUrl":"10.1021/acs.jctc.4c01788","url":null,"abstract":"<p><p>A very efficient and broadly applicable exciton coupling (ExC) approach based on simplified time-dependent density functional theory (sTD-DFT) is presented. Starting from this parent method, nonoverlapping fragments and neglect of interfragment charge transfer excitations are assumed to arrive at the ExC procedure. This leads to an ExC Hamiltonian that provides equivalent electronic absorption and circular dichroism spectra as the parent sTD-DFT method for largely separated fragments. The ExC approach easily accelerates the computation of such spectra of molecular aggregates by about 2 orders of magnitude compared to sTD-DFT. The latter itself is already faster by about 4-5 orders of magnitude compared to regular TD-DFT. We demonstrate the performance of the approach for excitation spectra of organic molecular clusters. Given that the fragment electronic structure in the ExC-sTD-DFT approach is solved independently, computation of spectra for systems with ∼10,000 atoms can be performed within minutes of computation time. Furthermore, the role of electrostatic embedding in the independent fragments is investigated. For the purposes covered in this work, the embedding can be simplified by employing a dielectric continuum, thus greatly reducing the overall computational complexity. This approach may be used in screening photophysical properties of large molecular aggregates and soft matter materials. We present the derivation and implementation for the Tamm-Dancoff-approximated and the random-phase-approximation eigenvalue problems. Benchmarks compared to the parent sTD-DFT methods are shown for absorption and electronic circular dichroism spectra.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"7002-7016"},"PeriodicalIF":5.7,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144525458","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}
Cian C Reeves, Michael Kurniawan, Yuanran Zhu, Nikil Jampana, Jacob Brown, Chao Yang, Khaled Z Ibrahim, Vojtech Vlcek
{"title":"A Practical Framework for Simulating Time-Resolved Spectroscopy Based on a Real-Time Dyson Expansion.","authors":"Cian C Reeves, Michael Kurniawan, Yuanran Zhu, Nikil Jampana, Jacob Brown, Chao Yang, Khaled Z Ibrahim, Vojtech Vlcek","doi":"10.1021/acs.jctc.5c00696","DOIUrl":"10.1021/acs.jctc.5c00696","url":null,"abstract":"<p><p>Time-resolved spectroscopy is a powerful tool for probing electron dynamics in molecules and solids, revealing transient phenomena on subfemtosecond time scales. The interpretation of experimental results is often enhanced by parallel numerical studies, which can provide insight and validation for experimental hypotheses. However, developing a theoretical framework for simulating time-resolved spectra remains a significant challenge. The most suitable approach involves the many-body nonequilibrium Green's function formalism, which accounts for crucial dynamical many-body correlations during time evolution. While these dynamical correlations are essential for observing emergent behavior in time-resolved spectra, they also render the formalism prohibitively expensive for large-scale simulations. Substantial effort has been devoted to reducing this computational cost─through approximations and numerical techniques─while preserving the key dynamical correlations. The ultimate goal is to enable first-principles simulations of time-dependent systems ranging from small molecules to large, periodic, multidimensional solids. In this perspective, we outline key challenges in developing practical simulations for time-resolved spectroscopy, with a particular focus on Green's function methodologies. We highlight a recent advancement toward a scalable framework: the real-time Dyson expansion (RT-DE) [<i>Phys. Rev. Lett.</i> <b>2024</b>, <i>133</i>, 226902]. We introduce the theoretical foundation of RT-DE and discuss strategies for improving scalability, which have already enabled simulations of system sizes beyond the reach of previous fully dynamical approaches. We conclude with an outlook on future directions for extending RT-DE to first-principles studies of dynamically correlated, nonequilibrium systems.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"6667-6682"},"PeriodicalIF":5.7,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144511283","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}