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

IF 2.5 4区 化学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Ved Vrat Verma, Swapnil Vimal, Manoj Kumar Mishra, Varun Kumar Sharma
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引用次数: 0

摘要

生物分子是与功能、结合相互作用、分子运动和结构构象相关的内在信息库。随着结构生物学和化学信息学等领域结构数据的快速积累,可视化生物分子结构的能力对生物学、药理学和相关学科的研究人员来说变得至关重要。分子可视化是获取和解释这些数据的基础步骤,使其能够在各种科学和治疗环境中应用。计算算法和基于网络的可视化平台的最新进展为结构生物学家、化学家和晶体学家提供了强大的资源,促进了实验结果的有效分析和可重复性。这篇综述提供了一个全面的概述当代分子可视化工具,强调其实际应用。特别关注PyMOL和NGL Viewer,详细指导他们在可视化蛋白质,DNA,蛋白质-配体复合物,蛋白质-蛋白质相互作用,蛋白质-DNA组装和小分子配体中的实现。在结构生物学和化学信息学中经常遇到的挑战,如鉴定用于治疗开发的先导化合物,也被解决。分子动力学模拟,包括结合自由能计算,讨论了成本和时间有效的策略,以加强药物发现管道。为了应对日益复杂的数据驱动研究,本综述旨在为寻求高效、可靠的可视化工具来支持基于结构的研究和药物设计的专业人员提供有价值的资源。方法本文综述了生物分子可视化功能与基于网络的分子可视化工具的综合比较分析。系统地使用PyMOL(独立)和NGL(基于web的)来可视化蛋白质、配体、蛋白质-配体复合物、蛋白质-蛋白质复合物和蛋白质- dna复合物。本研究概述的方法框架为有效利用分子可视化工具建立了标准化的指导方针,为结构生物学家和从事分子建模和结构分析的研究人员提供了宝贵的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.

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来源期刊
Journal of Molecular Modeling
Journal of Molecular Modeling 化学-化学综合
CiteScore
3.50
自引率
4.50%
发文量
362
审稿时长
2.9 months
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.
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