Wiley Interdisciplinary Reviews: Computational Molecular Science最新文献

{"title":"Advancements in DNA Tagging and Storage: Techniques, Applications, and Future Implications","authors":"Adam Kuzdraliński,&nbsp;Marek Miśkiewicz,&nbsp;Hubert Szczerba,&nbsp;Wojciech Mazurczyk,&nbsp;Tomasz Ociepa,&nbsp;Michał Lechowski,&nbsp;Bogdan Księżopolski","doi":"10.1002/wcms.70040","DOIUrl":"https://doi.org/10.1002/wcms.70040","url":null,"abstract":"<div>\u0000 \u0000 <p>DNA-based technologies for object authentication and data storage are becoming an interesting alternative to classic identification systems, yet their practical implementation faces fundamental technical and commercial barriers that limit widespread adoption. This review presents an analysis of DNA tagging and storage technologies, assessing their technical features, cost-effectiveness, and real-world applicability through comparison of competing approaches. We demonstrate that DNA tagging and data storage applications exhibit fundamentally different requirements, necessitating divergent technological strategies rather than unified solutions. DNA tagging faces severe cost disadvantages ($1–$100 per authentication versus $0.01–$0.10 for established technologies) and extended verification times (30 min to 6+ hours versus instant readout), limiting viability to high-security, low-volume markets such as pharmaceuticals and luxury goods. Current commercial implementations frequently lack peer-reviewed validation, creating an evidence deficit that undermines enterprise confidence. Among current approaches, isothermal amplification methods (LAMP, RPA) combined with colorimetric detection represent the most promising pathway for field-deployable authentication, while Illumina sequencing platforms provide optimal performance for data storage applications. The absence of standardization frameworks fundamentally constrains commercial adoption across both domains, preventing interoperability and enabling unsubstantiated performance claims. We conclude that successful commercialization requires strategic reorientation toward application-specific optimization and integrative approaches where DNA serves as secondary authentication combined with established identifiers, rather than competing directly on speed and cost metrics.</p>\u0000 <p>This article is categorized under:\u0000\u0000 </p><ul>\u0000 \u0000 <li>Structure and Mechanism &gt; Molecular Structures</li>\u0000 \u0000 <li>Data Science &gt; Databases and Expert Systems</li>\u0000 \u0000 <li>Molecular and Statistical Mechanics &gt; Molecular Mechanics</li>\u0000 </ul>\u0000 </div>","PeriodicalId":236,"journal":{"name":"Wiley Interdisciplinary Reviews: Computational Molecular Science","volume":"15 4","pages":""},"PeriodicalIF":16.8,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144647000","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 Fluid Interfaces","authors":"Chung Chi Chio,&nbsp;Yutong Yang,&nbsp;Yufan Xia,&nbsp;Ying-Lung Steve Tse","doi":"10.1002/wcms.70041","DOIUrl":"https://doi.org/10.1002/wcms.70041","url":null,"abstract":"<p>Fluid interfaces are fundamental to numerous natural and industrial processes, making their study crucial for both academic and practical purposes. Molecular dynamics (MD) simulations have become an indispensable tool for investigating the structures and molecular-level phenomena occurring at these interfaces. This review explores various computational strategies employed to model fluid interfaces, including classical force fields, quantum mechanical (QM) methods, and neural network potentials. The review begins by discussing the choice of potential energy functions, followed by a discussion of boundary conditions and their importance in simulating systems like the air-water and water–oil interfaces. The review then shifts to comparing nonpolarizable and polarizable force fields, highlighting when electronic polarization becomes necessary for accurately modeling the interface systems. The use of ab initio molecular dynamics (AIMD) is also examined, particularly for its ability to capture electronic effects, albeit with significant computational costs. Finally, we explore the growing role of machine learning, particularly neural network potentials, in simulating complex interface systems. By reviewing key studies on air-water and water–oil interfaces, we summarize the latest advancements in modeling fluid interfaces, with particular attention to chemical reactions near these interfaces. This review provides a concise and approachable overview of the computational approaches that are advancing our understanding of fluid interfaces at the molecular scale.</p><p>This article is categorized under:\u0000\u0000 </p>","PeriodicalId":236,"journal":{"name":"Wiley Interdisciplinary Reviews: Computational Molecular Science","volume":"15 4","pages":""},"PeriodicalIF":16.8,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/wcms.70041","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144647001","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":"Have You Tried Turning It Off and On Again? Stochastic Resetting for Enhanced Sampling","authors":"Ofir Blumer,&nbsp;Barak Hirshberg","doi":"10.1002/wcms.70038","DOIUrl":"https://doi.org/10.1002/wcms.70038","url":null,"abstract":"<p>Molecular dynamics simulations are widely used across chemistry, physics, and biology, providing quantitative insight into complex processes with atomic detail. However, their limited timescale of a few microseconds is a significant obstacle in describing phenomena such as conformational transitions of biomolecules and polymorphism in molecular crystals. Recently, stochastic resetting, that is, randomly stopping and restarting the simulations, emerged as a powerful enhanced sampling approach, which is collective variable-free, highly parallelized, and easily implemented in existing molecular dynamics codes. Resetting expedites sampling rare events while enabling the inference of kinetic observables of the underlying process. It can be employed as a standalone tool or in combination with other enhanced sampling methods, such as Metadynamics, with each technique compensating for the drawbacks of the other. Here, we comprehensively describe resetting and its theoretical background, review recent developments in stochastic resetting for enhanced sampling, and provide instructive guidelines for practitioners.</p><p>This article is categorized under:\u0000\u0000 </p>","PeriodicalId":236,"journal":{"name":"Wiley Interdisciplinary Reviews: Computational Molecular Science","volume":"15 4","pages":""},"PeriodicalIF":16.8,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/wcms.70038","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144646998","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":"Cover Image, Volume 15, Issue 2","authors":"Sousa Javan Nikkhah,&nbsp;Matthias Vandichel","doi":"10.1002/wcms.70035","DOIUrl":"https://doi.org/10.1002/wcms.70035","url":null,"abstract":"<p>The cover image is basThe cover image is based on the article <i>Dissipative Particle Dynamics Modeling in Polymer Science and Engineering</i> by Sousa Javannikkhah et al., https://doi.org/10.1002/wcms.70018\u0000 \u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":236,"journal":{"name":"Wiley Interdisciplinary Reviews: Computational Molecular Science","volume":"15 2","pages":""},"PeriodicalIF":16.8,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/wcms.70035","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144197230","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":"Cover Image, Volume 15, Issue 2","authors":"Xiaoyan Zheng,&nbsp;Qian Peng","doi":"10.1002/wcms.70027","DOIUrl":"https://doi.org/10.1002/wcms.70027","url":null,"abstract":"<p>The cover image is based on the article <i>Multiscale Simulations and Property Predictions for Organic Luminescent Aggregates</i> by Qian Peng et al., https://doi.org/10.1002/wcms.70021.\u0000\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":236,"journal":{"name":"Wiley Interdisciplinary Reviews: Computational Molecular Science","volume":"15 2","pages":""},"PeriodicalIF":16.8,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/wcms.70027","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144197231","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":"Cover Image, Volume 15, Issue 3","authors":"Yosef Masoudi-Sobhanzadeh,&nbsp;Anisur Rahman,&nbsp;Shuxiang Li,&nbsp;Saman Bazmi,&nbsp;Sushant Kumar,&nbsp;Anna R. Panchenko","doi":"10.1002/wcms.70036","DOIUrl":"https://doi.org/10.1002/wcms.70036","url":null,"abstract":"<p>The cover image is based on the article <i>Building Nucleosome Positioning Maps: Discovering Hidden Gems</i> by Anna Panchenko et al., https://doi.org/10.1002/wcms.70029.\u0000\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":236,"journal":{"name":"Wiley Interdisciplinary Reviews: Computational Molecular Science","volume":"15 3","pages":""},"PeriodicalIF":16.8,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/wcms.70036","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144197313","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":"Machine Learning Transition State Geometries and Applications in Reaction Property Prediction","authors":"Isaac W. Beaglehole,&nbsp;Miles J. Pemberton,&nbsp;Elliot H. E. Farrar,&nbsp;Matthew N. Grayson","doi":"10.1002/wcms.70025","DOIUrl":"https://doi.org/10.1002/wcms.70025","url":null,"abstract":"<p>The calculation of transition state (TS) geometries is essential for understanding reaction mechanisms and rational synthetic methodology design. However, traditional methods like density functional theory are often too computationally expensive for large-scale TS identification and are significantly slower than high-throughput experimental screening methods. Recent advancements in machine learning (ML) offer promising alternatives, enabling the direct prediction of TS geometries, reducing the reliance on expensive quantum mechanical (QM) calculations, and affording predictions ahead of experiments. The works explored here include the broader application of ML in reaction property prediction, emphasizing how accurate TS geometries can serve as vital input data to improve model accuracy. A comprehensive review of ML methods developed to explicitly predict TS geometries is then presented, with attention to their application in downstream tasks, such as energy barrier calculations, and their use as initial structures for further optimization via QM methods. Finally, a critical evaluation of the accuracy and limitations of existing TS prediction methods is discussed, highlighting challenges that impede wider adoption and areas where further research is needed.</p>","PeriodicalId":236,"journal":{"name":"Wiley Interdisciplinary Reviews: Computational Molecular Science","volume":"15 3","pages":""},"PeriodicalIF":16.8,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/wcms.70025","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144190680","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":"A Journey With THeSeuSS: Automated Python Tool for Modeling IR and Raman Vibrational Spectra of Molecules and Solids","authors":"Ariadni Boziki,&nbsp;Frédéric Ngono Mebenga,&nbsp;Philippe Fernandes,&nbsp;Alexandre Tkatchenko","doi":"10.1002/wcms.70033","DOIUrl":"https://doi.org/10.1002/wcms.70033","url":null,"abstract":"<p>Vibrational spectroscopy is an indispensable analytical tool that provides structural fingerprints for molecules, solids, and interfaces thereof. This study introduces THeSeuSS (THz Spectra Simulations Software)—an automated computational platform that efficiently simulates IR and Raman spectra for both periodic and non-periodic systems. Using DFT, DFTB and machine-learning force field, THeSeuSS offers robust capabilities for detailed vibrational spectra simulations. Our extensive evaluations and benchmarks demonstrate that THeSeuSS accurately reproduces both previously calculated and experimental spectra, enabling precise comparisons and interpretations of vibrational characteristics in various test cases, including H₂O and glycine molecules in the gas phase, as well as solid ammonia and solid ibuprofen. Designed with a user-friendly interface and seamless integration with existing computational chemistry tools, THeSeuSS enhances the accessibility and applicability of advanced spectroscopic simulations, supporting research and development in chemical, pharmaceutical, and material sciences.</p>","PeriodicalId":236,"journal":{"name":"Wiley Interdisciplinary Reviews: Computational Molecular Science","volume":"15 3","pages":""},"PeriodicalIF":16.8,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/wcms.70033","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144171861","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":"Floquet Nonadiabatic Dynamics in Open Quantum Systems: Overview","authors":"Vahid Mosallanejad,&nbsp;Yu Wang,&nbsp;Jingqi Chen,&nbsp;Wenjie Dou","doi":"10.1002/wcms.70032","DOIUrl":"https://doi.org/10.1002/wcms.70032","url":null,"abstract":"<div>\u0000 \u0000 <p>The Born–Oppenheimer (BO) approximation has shaped our understanding on molecular dynamics microscopically in many physical and chemical systems. However, there are many cases that we must go beyond the BO approximation, particularly when strong light-matter interactions are considered. Floquet theory offers a powerful tool to treat time-periodic quantum systems. In this overview, we briefly review recent developments on Floquet nonadiabatic dynamics, with a special focus on open quantum systems. We first present the general Floquet Liouville von-Neumann (LvN) equation. We then show how to connect Floquet operators to real time observables. We proceed to outline the derivation of the Floquet quantum master equation in treating the dynamics under periodic driving in open quantum systems. We further present the Floquet mixed quantum classical Liouville equation (QCLE) to deal with coupled electron-nuclear dynamics. Finally, we embed FQCLE into a classical master equation (CME) to deal with Floquet nonadiabatic dynamics in open quantum systems. The formulations are general platforms for developing trajectory based dynamical approaches. As an example, we show how Floquet QCLE and Floquet CME can be implemented into a Langevin dynamics with Lorentz force and surface hopping algorithms.</p>\u0000 </div>","PeriodicalId":236,"journal":{"name":"Wiley Interdisciplinary Reviews: Computational Molecular Science","volume":"15 3","pages":""},"PeriodicalIF":16.8,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144148451","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":"ByteQC: GPU-Accelerated Quantum Chemistry Package for Large-Scale Systems","authors":"Zhen Guo,&nbsp;Zigeng Huang,&nbsp;Qiaorui Chen,&nbsp;Jiang Shao,&nbsp;Guangcheng Liu,&nbsp;Hung Q. Pham,&nbsp;Yifei Huang,&nbsp;Changsu Cao,&nbsp;Ji Chen,&nbsp;Dingshun Lv","doi":"10.1002/wcms.70034","DOIUrl":"https://doi.org/10.1002/wcms.70034","url":null,"abstract":"<div>\u0000 \u0000 <p>Applying quantum chemistry algorithms to large-scale systems requires substantial computational resources scaling with the system size and the desired accuracy. To address this, ByteQC, a fully functional and efficient package for large-scale quantum chemistry simulations, has been open sourced at https://github.com/bytedance/byteqc, leveraging recent advances in computational power and many-body algorithms. Regarding computational power, several standard algorithms are efficiently implemented on modern GPUs, ranging from mean-field calculations (Hartree-Fock and density functional theory) to post-Hartree-Fock methods such as Møller-Plesset perturbation theory and coupled cluster methods. For the algorithmic approach, we also employ a quantum embedding method, which significantly expands the tractable system size while preserving high accuracy at the gold-standard level. All these features have been systematically benchmarked. For standalone algorithms, the benchmark results demonstrate up to a 60× speedup when compared to 100-core CPUs. Additionally, the tractable system sizes have been significantly expanded: 1610 orbitals for coupled cluster with single and double excitations (1380 orbitals with perturbative triple excitations), 11,040 orbitals for Møller-Plesset perturbation theory of second order, 37,120 orbitals for mean-field calculations under open boundary conditions, and over 100,000 orbitals for periodic boundary conditions. For the advanced quantum embedding feature, two representative examples are demonstrated: the water cluster problem (2752 orbitals) and a water monomer adsorbed on a boron nitride surface (3929 orbitals), achieving the gold-standard accuracy. With these efforts, ByteQC is expected to significantly advance research in quantum chemistry, particularly in large-scale, high-accuracy calculations.</p>\u0000 </div>","PeriodicalId":236,"journal":{"name":"Wiley Interdisciplinary Reviews: Computational Molecular Science","volume":"15 3","pages":""},"PeriodicalIF":16.8,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144171203","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}