{"title":"通过分子可视化的结构洞察:工具,应用和局限性的综合综述","authors":"Ved Vrat Verma, Swapnil Vimal, Manoj Kumar Mishra, Varun Kumar Sharma","doi":"10.1007/s00894-025-06402-y","DOIUrl":null,"url":null,"abstract":"<div><h3>Context</h3><p>Biomolecules serve as intrinsic repositories of information related to function, binding interactions, molecular motion, and structural conformations. With the rapid accumulation of structural data from fields such as structural biology and cheminformatics, the ability to visualize biomolecular architecture has become essential for researchers in biology, pharmacology, and related disciplines. Molecular visualization represents a foundational step in accessing and interpreting this data, enabling its application in diverse scientific and therapeutic contexts. Recent advancements in computational algorithms and web-based visualization platforms have provided powerful resources for structural biologists, chemists, and crystallographers, facilitating efficient analysis and reproducibility of experimental outcomes. This review offers a comprehensive overview of contemporary molecular visualization tools, emphasizing their practical applications. Particular attention is given to PyMOL and NGL Viewer, with detailed guidance for their implementation in visualizing proteins, DNA, protein–ligand complexes, protein–protein interactions, protein-DNA assemblies, and small molecule ligands. Challenges frequently encountered in structural biology and cheminformatics, such as the identification of lead compounds for therapeutic development, are also addressed. Molecular dynamics simulations, including binding free energy calculations, are discussed as cost- and time-effective strategies to enhance drug discovery pipelines. In response to the increasing complexity of data-driven research, this review aims to serve as a valuable resource for professionals seeking efficient, reliable visualization tools to support structure-based research and drug design.</p><h3>Methods</h3><p>This review article provides a comprehensive comparative analysis of biomolecular visualization features integrated into standalone and web-based molecular visualization tools. PyMOL (standalone) and NGL (web-based) were systematically employed to visualize proteins, ligands, protein–ligand complexes, protein–protein complexes, and protein-DNA complexes. The methodological framework outlined in this study establishes standardized guidelines for the effective utilization of molecular visualization tools, offering valuable insights for structural biologists and researchers engaged in molecular modeling and structural analysis.</p></div>","PeriodicalId":651,"journal":{"name":"Journal of Molecular Modeling","volume":"31 6","pages":""},"PeriodicalIF":2.5000,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A comprehensive review on structural insights through molecular visualization: tools, applications, and limitations\",\"authors\":\"Ved Vrat Verma, Swapnil Vimal, Manoj Kumar Mishra, Varun Kumar Sharma\",\"doi\":\"10.1007/s00894-025-06402-y\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Context</h3><p>Biomolecules serve as intrinsic repositories of information related to function, binding interactions, molecular motion, and structural conformations. With the rapid accumulation of structural data from fields such as structural biology and cheminformatics, the ability to visualize biomolecular architecture has become essential for researchers in biology, pharmacology, and related disciplines. Molecular visualization represents a foundational step in accessing and interpreting this data, enabling its application in diverse scientific and therapeutic contexts. Recent advancements in computational algorithms and web-based visualization platforms have provided powerful resources for structural biologists, chemists, and crystallographers, facilitating efficient analysis and reproducibility of experimental outcomes. This review offers a comprehensive overview of contemporary molecular visualization tools, emphasizing their practical applications. Particular attention is given to PyMOL and NGL Viewer, with detailed guidance for their implementation in visualizing proteins, DNA, protein–ligand complexes, protein–protein interactions, protein-DNA assemblies, and small molecule ligands. Challenges frequently encountered in structural biology and cheminformatics, such as the identification of lead compounds for therapeutic development, are also addressed. Molecular dynamics simulations, including binding free energy calculations, are discussed as cost- and time-effective strategies to enhance drug discovery pipelines. In response to the increasing complexity of data-driven research, this review aims to serve as a valuable resource for professionals seeking efficient, reliable visualization tools to support structure-based research and drug design.</p><h3>Methods</h3><p>This review article provides a comprehensive comparative analysis of biomolecular visualization features integrated into standalone and web-based molecular visualization tools. PyMOL (standalone) and NGL (web-based) were systematically employed to visualize proteins, ligands, protein–ligand complexes, protein–protein complexes, and protein-DNA complexes. The methodological framework outlined in this study establishes standardized guidelines for the effective utilization of molecular visualization tools, offering valuable insights for structural biologists and researchers engaged in molecular modeling and structural analysis.</p></div>\",\"PeriodicalId\":651,\"journal\":{\"name\":\"Journal of Molecular Modeling\",\"volume\":\"31 6\",\"pages\":\"\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2025-05-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Molecular Modeling\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s00894-025-06402-y\",\"RegionNum\":4,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Molecular Modeling","FirstCategoryId":"92","ListUrlMain":"https://link.springer.com/article/10.1007/s00894-025-06402-y","RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
A comprehensive review on structural insights through molecular visualization: tools, applications, and limitations
Context
Biomolecules serve as intrinsic repositories of information related to function, binding interactions, molecular motion, and structural conformations. With the rapid accumulation of structural data from fields such as structural biology and cheminformatics, the ability to visualize biomolecular architecture has become essential for researchers in biology, pharmacology, and related disciplines. Molecular visualization represents a foundational step in accessing and interpreting this data, enabling its application in diverse scientific and therapeutic contexts. Recent advancements in computational algorithms and web-based visualization platforms have provided powerful resources for structural biologists, chemists, and crystallographers, facilitating efficient analysis and reproducibility of experimental outcomes. This review offers a comprehensive overview of contemporary molecular visualization tools, emphasizing their practical applications. Particular attention is given to PyMOL and NGL Viewer, with detailed guidance for their implementation in visualizing proteins, DNA, protein–ligand complexes, protein–protein interactions, protein-DNA assemblies, and small molecule ligands. Challenges frequently encountered in structural biology and cheminformatics, such as the identification of lead compounds for therapeutic development, are also addressed. Molecular dynamics simulations, including binding free energy calculations, are discussed as cost- and time-effective strategies to enhance drug discovery pipelines. In response to the increasing complexity of data-driven research, this review aims to serve as a valuable resource for professionals seeking efficient, reliable visualization tools to support structure-based research and drug design.
Methods
This review article provides a comprehensive comparative analysis of biomolecular visualization features integrated into standalone and web-based molecular visualization tools. PyMOL (standalone) and NGL (web-based) were systematically employed to visualize proteins, ligands, protein–ligand complexes, protein–protein complexes, and protein-DNA complexes. The methodological framework outlined in this study establishes standardized guidelines for the effective utilization of molecular visualization tools, offering valuable insights for structural biologists and researchers engaged in molecular modeling and structural analysis.
期刊介绍:
The Journal of Molecular Modeling focuses on "hardcore" modeling, publishing high-quality research and reports. Founded in 1995 as a purely electronic journal, it has adapted its format to include a full-color print edition, and adjusted its aims and scope fit the fast-changing field of molecular modeling, with a particular focus on three-dimensional modeling.
Today, the journal covers all aspects of molecular modeling including life science modeling; materials modeling; new methods; and computational chemistry.
Topics include computer-aided molecular design; rational drug design, de novo ligand design, receptor modeling and docking; cheminformatics, data analysis, visualization and mining; computational medicinal chemistry; homology modeling; simulation of peptides, DNA and other biopolymers; quantitative structure-activity relationships (QSAR) and ADME-modeling; modeling of biological reaction mechanisms; and combined experimental and computational studies in which calculations play a major role.