Wiley Interdisciplinary Reviews: Computational Molecular Science最新文献_第3页

From Perception to Prediction and Interpretation: Enlightening the Gray Zone of Molecular Bricks of Life With the Help of Machine Learning and Quantum Chemistry 从感知到预测和解释：借助机器学习和量子化学照亮生命分子砖块的灰色地带

IF 16.8 2区化学

Wiley Interdisciplinary Reviews: Computational Molecular Science Pub Date : 2025-01-06 DOI: 10.1002/wcms.70000

Vincenzo Barone

{"title":"From Perception to Prediction and Interpretation: Enlightening the Gray Zone of Molecular Bricks of Life With the Help of Machine Learning and Quantum Chemistry","authors":"Vincenzo Barone","doi":"10.1002/wcms.70000","DOIUrl":"https://doi.org/10.1002/wcms.70000","url":null,"abstract":"<div>\u0000 \u0000 The latest developments of a general exploration/exploitation strategy for the computational study of molecular bricks of life in the gas-phase are presented and illustrated by means of prototypical semi-rigid and flexible systems. In the first step, generalized natural internal coordinates are employed to obtain a clear-cut separation between different degrees of freedom, and machine-learning algorithms based on chemical descriptors (synthons) drive fast quantum chemical methods in the exploration of rugged potential energy surfaces ruled by soft degrees of freedom. Then, different quantum chemical models are carefully selected for exploiting energies, geometries, and vibrational frequencies with the aim of maximizing the accuracy of the overall description while retaining a reasonable cost for all the steps. In particular, a composite wave-function method is used for energies, whereas a double-hybrid functional is employed for geometries and harmonic frequencies and a cheaper global hybrid functional for anharmonic contributions. A panel of molecular bricks of life containing up to 50 atoms is employed to show that the proposed strategy draws closer to the accuracy of state-of-the-art composite wave-function methods for small semi-rigid molecules, but is applicable to much larger systems. The implementation of the whole computational workflow in terms of preprocessing and postprocessing of data provided by standard electronic structure codes paves the way toward the accurate yet not prohibitively expensive study of medium- to large-sized molecules by a user-friendly black-box tool exploitable also by experiment-oriented researchers.\u0000 </div>","PeriodicalId":236,"journal":{"name":"Wiley Interdisciplinary Reviews: Computational Molecular Science","volume":"15 1","pages":""},"PeriodicalIF":16.8,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143112602","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}

引用次数: 0

Good Practices in Database Generation for Benchmarking Density Functional Theory 密度泛函理论基准数据库生成的良好实践

IF 16.8 2区化学

Wiley Interdisciplinary Reviews: Computational Molecular Science Pub Date : 2025-01-05 DOI: 10.1002/wcms.1737

Amir Karton, Marcelo T. de Oliveira

{"title":"Good Practices in Database Generation for Benchmarking Density Functional Theory","authors":"Amir Karton, Marcelo T. de Oliveira","doi":"10.1002/wcms.1737","DOIUrl":"https://doi.org/10.1002/wcms.1737","url":null,"abstract":"<div>\u0000 \u0000 The hundreds of density functional theory (DFT) methods developed over the past three decades are often referred to as the “zoo” of DFT approximations. In line with this terminology, the numerous DFT benchmark studies might be considered the “safari” of DFT evaluation efforts, reflecting their abundance, diversity, and wide range of application and methodological aspects. These benchmarks have played a critical role in establishing DFT as the dominant approach in quantum chemical applications and remain essential for selecting an appropriate DFT method for specific chemical properties (e.g., reaction energy, barrier height, or noncovalent interaction energy) and systems (e.g., organic, inorganic, or organometallic). DFT benchmark studies are a vital tool for both DFT users in method selection and DFT developers in method design and parameterization. This review provides best-practice guidance on key methodological aspects of DFT benchmarking, such as the quality of benchmark reference values, dataset size, reference geometries, basis sets, statistical analysis, and electronic availability of the benchmark data. Additionally, we present a flowchart to assist users in systematically choosing these methodological aspects, thereby enhancing the reliability and reproducibility of DFT benchmarking studies.\u0000 </div>","PeriodicalId":236,"journal":{"name":"Wiley Interdisciplinary Reviews: Computational Molecular Science","volume":"15 1","pages":""},"PeriodicalIF":16.8,"publicationDate":"2025-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143112260","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}

引用次数: 0

Nonequilibrium Dynamics at Cellular Interfaces: Insights From Simulation and Theory 非平衡动力学在细胞界面：从模拟和理论的见解

IF 16.8 2区化学

Wiley Interdisciplinary Reviews: Computational Molecular Science Pub Date : 2024-12-09 DOI: 10.1002/wcms.1736

Zheng Jiao, Lijuan Gao, Xueqing Jin, Jiaqi Li, Yuming Wang, Wenlong Chen, Li-Tang Yan

{"title":"Nonequilibrium Dynamics at Cellular Interfaces: Insights From Simulation and Theory","authors":"Zheng Jiao, Lijuan Gao, Xueqing Jin, Jiaqi Li, Yuming Wang, Wenlong Chen, Li-Tang Yan","doi":"10.1002/wcms.1736","DOIUrl":"https://doi.org/10.1002/wcms.1736","url":null,"abstract":"<div>\u0000 \u0000 Active matters, which consume energy to exert mechanical forces, include molecular motors, synthetic nanomachines, actively propelled bacteria, and viruses. A series of unique phenomena emerge when active matters interact with cellular interfaces. Activity changes the mechanism of nanoparticle intracellular delivery, while active mechanical processes generated in the cytoskeleton play a major role in membrane protein distribution and transport. This review provides a comprehensive overview of the theoretical and simulation models used to study these nonequilibrium phenomena, offering insights into how activity enhances cellular uptake, influences membrane deformation, and governs surface transport dynamics. Furthermore, we explore the impact of membrane properties, such as fluidity and viscosity, on transport efficiency and discuss the slippage dynamics and active rotation behaviors on the membrane surface. The interplay of active particles and membranes highlights the essential role of nonequilibrium dynamics in cellular transport processes, with potential applications in drug delivery and nanotechnology. Finally, we provide an outlook highlighting the significance of deeper theoretical and simulation-based investigations to optimize active particles and understand their behavior in complex biological environments.\u0000 </div>","PeriodicalId":236,"journal":{"name":"Wiley Interdisciplinary Reviews: Computational Molecular Science","volume":"14 6","pages":""},"PeriodicalIF":16.8,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142860656","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}

引用次数: 0

Unveiling Drug Discovery Insights Through Molecular Electrostatic Potential Analysis 通过分子静电势分析揭示药物发现的见解

IF 16.8 2区化学

Wiley Interdisciplinary Reviews: Computational Molecular Science Pub Date : 2024-12-03 DOI: 10.1002/wcms.1735

Mambatta Haritha, Cherumuttathu H. Suresh

{"title":"Unveiling Drug Discovery Insights Through Molecular Electrostatic Potential Analysis","authors":"Mambatta Haritha, Cherumuttathu H. Suresh","doi":"10.1002/wcms.1735","DOIUrl":"https://doi.org/10.1002/wcms.1735","url":null,"abstract":"<div>\u0000 \u0000 Molecular electrostatic potential (MESP) analysis has emerged as a pivotal tool in drug discovery, providing insights into molecular reactivity and noncovalent interactions essential for drug function. While widely used MESP-on-isodensity surface analysis offers interpretations of electron-rich or deficient regions of a drug molecule, the MESP topology parameters such as spatial minimum (Vmin) and MESP at nuclei (Vn) provide a quantitative understanding. The investigation into the correlation between MESP parameters and various molecular properties such as lipophilicity, pKa (acidity/basicity), conformations, and tautomeric forms is crucial for understanding the impact on biological activity of drugs and facilitating drug design. Moreover, MESP topology analysis serves as a fundamental tool in elucidating the pharmacological behavior of compounds and optimizing their therapeutic efficacy. A quantitative study utilizing Vn parameters to assess the hydrogen bond propensity of a drug presents a novel strategy for investigating drug-receptor interactions with increased precision. The qualitative and quantitative analysis of the MESP features of various drugs, including their applications in cancer, tuberculosis, tumors, inflammation, and infectious diseases such as malaria, bacterial infections, fungal infections, and viral infections, is conducted in this review.\u0000 </div>","PeriodicalId":236,"journal":{"name":"Wiley Interdisciplinary Reviews: Computational Molecular Science","volume":"14 6","pages":""},"PeriodicalIF":16.8,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142764056","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}

引用次数: 0

Embedded Many-Body Green's Function Methods for Electronic Excitations in Complex Molecular Systems 复杂分子系统中电子激发的嵌入式多体格林函数方法

IF 16.8 2区化学

Wiley Interdisciplinary Reviews: Computational Molecular Science Pub Date : 2024-11-17 DOI: 10.1002/wcms.1734

Gianluca Tirimbó, Vivek Sundaram, Björn Baumeier

{"title":"Embedded Many-Body Green's Function Methods for Electronic Excitations in Complex Molecular Systems","authors":"Gianluca Tirimbó, Vivek Sundaram, Björn Baumeier","doi":"10.1002/wcms.1734","DOIUrl":"https://doi.org/10.1002/wcms.1734","url":null,"abstract":"Many-body Green's function theory in the GW approximation with the Bethe–Salpeter equation (BSE) provides a powerful framework for the first-principles calculations of single-particle and electron–hole excitations in perfect crystals and molecules alike. Application to complex molecular systems, for example, solvated dyes, molecular aggregates, thin films, interfaces, or macromolecules, is particularly challenging as they contain a prohibitively large number of atoms. Exploiting the often localized nature of excitation in such disordered systems, several methods have recently been developed in which GW-BSE is applied to a smaller, tractable region of interest that is embedded into an environment described with a lower-level method. Here, we review the various strategies proposed for such embedded many-body Green's functions approaches, including quantum–quantum and quantum–classical embeddings, and focus in particular on how they include environment screening effects either intrinsically in the screened Coulomb interaction in the GW and BSE steps or via extrinsic electrostatic couplings.","PeriodicalId":236,"journal":{"name":"Wiley Interdisciplinary Reviews: Computational Molecular Science","volume":"14 6","pages":""},"PeriodicalIF":16.8,"publicationDate":"2024-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/wcms.1734","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142665090","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}

引用次数: 0

ROBERT: Bridging the Gap Between Machine Learning and Chemistry 罗伯特：缩小机器学习与化学之间的差距

IF 16.8 2区化学

Wiley Interdisciplinary Reviews: Computational Molecular Science Pub Date : 2024-10-22 DOI: 10.1002/wcms.1733

David Dalmau, Juan V. Alegre-Requena

{"title":"ROBERT: Bridging the Gap Between Machine Learning and Chemistry","authors":"David Dalmau, Juan V. Alegre-Requena","doi":"10.1002/wcms.1733","DOIUrl":"https://doi.org/10.1002/wcms.1733","url":null,"abstract":"Beyond addressing technological demands, the integration of machine learning (ML) into human societies has also promoted sustainability through the adoption of digitalized protocols. Despite these advantages and the abundance of available toolkits, a substantial implementation gap is preventing the widespread incorporation of ML protocols into the computational and experimental chemistry communities. In this work, we introduce ROBERT, a software carefully crafted to make ML more accessible to chemists of all programming skill levels, while achieving results comparable to those of field experts. We conducted benchmarking using six recent ML studies in chemistry containing from 18 to 4149 entries. Furthermore, we demonstrated the program's ability to initiate workflows directly from SMILES strings, which simplifies the generation of ML predictors for common chemistry problems. To assess ROBERT's practicality in real-life scenarios, we employed it to discover new luminescent Pd complexes with a modest dataset of 23 points, a frequently encountered scenario in experimental studies.","PeriodicalId":236,"journal":{"name":"Wiley Interdisciplinary Reviews: Computational Molecular Science","volume":"14 5","pages":""},"PeriodicalIF":16.8,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/wcms.1733","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142525092","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}

引用次数: 0

Advanced quantum and semiclassical methods for simulating photoinduced molecular dynamics and spectroscopy 模拟光诱导分子动力学和光谱学的先进量子和半经典方法

IF 16.8 2区化学

Wiley Interdisciplinary Reviews: Computational Molecular Science Pub Date : 2024-10-09 DOI: 10.1002/wcms.1731

Shirin Faraji, David Picconi, Elisa Palacino-González

{"title":"Advanced quantum and semiclassical methods for simulating photoinduced molecular dynamics and spectroscopy","authors":"Shirin Faraji, David Picconi, Elisa Palacino-González","doi":"10.1002/wcms.1731","DOIUrl":"https://doi.org/10.1002/wcms.1731","url":null,"abstract":"Molecular-level understanding of photoinduced processes is critically important for breakthroughs in transformative technologies utilizing light, ranging from photomedicine to photoresponsive materials. Theory and simulation play a crucial role in this task. Despite great advances in hardware and computational methods, the theoretical description of photoinduced phenomena in the presence of complex environments and external photoexcitation conditions still poses formidable challenges for theoreticians and there are numerous formal and computational difficulties that must be overcome. The development of predictive, accurate, and at the same time, computationally efficient theoretical approaches to describe complex problems in photochemistry and photophysics is an active field of research in contemporary theoretical and computational chemistry. In this advanced review, we discuss modern computational advances and novel approaches that have been recently developed in excited-electronic structure methods, and multiscale modeling, with a special emphasis on coupled electron-nuclear dynamics and spectroscopy, from fully quantum to semi-classical methodologies—including dissipative effects, the explicit light field interaction, femtosecond time-resolved spectroscopy, and software infrastructure.This article is categorized under:\u0000 ","PeriodicalId":236,"journal":{"name":"Wiley Interdisciplinary Reviews: Computational Molecular Science","volume":"14 5","pages":""},"PeriodicalIF":16.8,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/wcms.1731","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142429639","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}

引用次数: 0

Computational design of energy-related materials: From first-principles calculations to machine learning 能源相关材料的计算设计：从第一原理计算到机器学习

IF 16.8 2区化学

Wiley Interdisciplinary Reviews: Computational Molecular Science Pub Date : 2024-10-01 DOI: 10.1002/wcms.1732

Haibo Xue, Guanjian Cheng, Wan-Jian Yin

{"title":"Computational design of energy-related materials: From first-principles calculations to machine learning","authors":"Haibo Xue, Guanjian Cheng, Wan-Jian Yin","doi":"10.1002/wcms.1732","DOIUrl":"https://doi.org/10.1002/wcms.1732","url":null,"abstract":"Energy-related materials are crucial for advancing energy technologies, improving efficiency, reducing environmental impacts, and supporting sustainable development. Designing and discovering these materials through computational techniques necessitates a comprehensive understanding of the material space, which is defined by the constituent atoms, composition, and structure. Depending on the search space involved in the investigation, the computational materials design can be categorized into four primary approaches: atomic substitution in fixed prototype structures, crystal structure prediction (CSP), variable-composition CSP, and inverse design across the entire materials space. This review provides an overview of these paradigms, detailing the concepts, strategies, and applications pertinent to energy-related materials. The progression from first-principles calculations to machine learning techniques is emphasized, with the aim of enhancing understanding and elucidating new advancements in computationally design of energy-related materials.This article is categorized under:\u0000 ","PeriodicalId":236,"journal":{"name":"Wiley Interdisciplinary Reviews: Computational Molecular Science","volume":"14 5","pages":""},"PeriodicalIF":16.8,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142429189","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}

引用次数: 0

Catalysis in the digital age: Unlocking the power of data with machine learning 数字时代的催化：利用机器学习释放数据的力量

IF 16.8 2区化学

Wiley Interdisciplinary Reviews: Computational Molecular Science Pub Date : 2024-09-20 DOI: 10.1002/wcms.1730

Bokinala Moses Abraham, Mullapudi V. Jyothirmai, Priyanka Sinha, Francesc Viñes, Jayant K. Singh, Francesc Illas

{"title":"Catalysis in the digital age: Unlocking the power of data with machine learning","authors":"Bokinala Moses Abraham, Mullapudi V. Jyothirmai, Priyanka Sinha, Francesc Viñes, Jayant K. Singh, Francesc Illas","doi":"10.1002/wcms.1730","DOIUrl":"https://doi.org/10.1002/wcms.1730","url":null,"abstract":"The design and discovery of new and improved catalysts are driving forces for accelerating scientific and technological innovations in the fields of energy conversion, environmental remediation, and chemical industry. Recently, the use of machine learning (ML) in combination with experimental and/or theoretical data has emerged as a powerful tool for identifying optimal catalysts for various applications. This review focuses on how ML algorithms can be used in computational catalysis and materials science to gain a deeper understanding of the relationships between materials properties and their stability, activity, and selectivity. The development of scientific data repositories, data mining techniques, and ML tools that can navigate structural optimization problems are highlighted, leading to the discovery of highly efficient catalysts for a sustainable future. Several data-driven ML models commonly used in catalysis research and their diverse applications in reaction prediction are discussed. The key challenges and limitations of using ML in catalysis research are presented, which arise from the catalyst's intrinsic complex nature. Finally, we conclude by summarizing the potential future directions in the area of ML-guided catalyst development.This article is categorized under:\u0000 ","PeriodicalId":236,"journal":{"name":"Wiley Interdisciplinary Reviews: Computational Molecular Science","volume":"14 5","pages":""},"PeriodicalIF":16.8,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/wcms.1730","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142273293","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}

引用次数: 0

Modern chemical graph theory 现代化学图论

IF 16.8 2区化学

Wiley Interdisciplinary Reviews: Computational Molecular Science Pub Date : 2024-09-18 DOI: 10.1002/wcms.1729

Leonardo S. G. Leite, Swarup Banerjee, Yihui Wei, Jackson Elowitt, Aurora E. Clark

{"title":"Modern chemical graph theory","authors":"Leonardo S. G. Leite, Swarup Banerjee, Yihui Wei, Jackson Elowitt, Aurora E. Clark","doi":"10.1002/wcms.1729","DOIUrl":"https://doi.org/10.1002/wcms.1729","url":null,"abstract":"Graph theory has a long history in chemistry. Yet as the breadth and variety of chemical data is rapidly changing, so too do graph encoding methods and analyses that yield qualitative and quantitative insights. Using illustrative cases within a basic mathematical framework, we showcase modern chemical graph theory's utility in Chemists' analysis and model development toolkit. The encoding of both experimental and simulation data is discussed at various levels of granularity of information. This is followed by a discussion of the two major classes of graph theoretical analyses: identifying connectivity patterns and partitioning methods. Measures, metrics, descriptors, and topological indices are then introduced with an emphasis upon enhancing interpretability and incorporation into physical models. Challenging data cases are described that include strategies for studying time dependence. Throughout, we incorporate recent advancements in computer science and applied mathematics that are propelling chemical graph theory into new domains of chemical study.This article is categorized under:\u0000 ","PeriodicalId":236,"journal":{"name":"Wiley Interdisciplinary Reviews: Computational Molecular Science","volume":"14 5","pages":""},"PeriodicalIF":16.8,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142244795","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}

引用次数: 0