The representation of carbohydrates in 3D space using symbols is a powerful visualization method, but such representations are lacking in currently available visualization software. The work presented here allows researchers to display carbohydrate 3D structures as 3D-SNFG symbols using LiteMol from a web browser (e.g., v.litemol.org/?loadFromCS=5T3X ). Any PDB ID can be substituted at the end of the URL. Alternatively, the user may enter a PDB ID or upload a structure. LiteMol is available at https://v.litemol.org and automatically depicts any carbohydrate residues as 3D-SNFG symbols. To embed LiteMol in a webpage, visit https://github.com/dsehnal/LiteMol .
- Keywords
- 3D-SNFG, LiteMol, SNFG, carbohydrate, glycan, glycoprotein, oligosaccharide, structure, symbol nomenclature for glycans, visualization,
- MeSH
- Molecular Conformation * MeSH
- Polysaccharides chemistry MeSH
- Carbohydrates chemistry MeSH
- Software * MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Research Support, N.I.H., Extramural MeSH
- Names of Substances
- Polysaccharides MeSH
- Carbohydrates MeSH
This paper focuses on the method for creating 3-dimensional (3D) digital models extracted from patient- specific scans of the brain. The described approach consists of several cross-platform stages: raw data segmentation, data correction in 3D-modelling software, post-processing of the 3D digital models and their presentation on an interactive web-based platform. This method of data presentation offers a cost and time effective option to present medical data accurately. An important aspect of the process is using real patient data and enriching the traditional slice-based representation of the scans with 3D models that can provide better understanding of the organs' structures. The resulting 3D digital models also form the basis for further processing into different modalities, for example models in Virtual Reality or 3D physical model printouts. The option to make medical data less abstract and more understandable can extend their use beyond diagnosis and into a potential aid in anatomy and patient education. The methods presented in this paper were originally based on the master thesis 'Transparent Minds: Testing for Efficiency of Transparency in 3D Physical and 3D Digital Models', which focussed on creating and comparing the efficiency of transparent 3D physical and 3D digital models from real-patient data.
- Keywords
- 3D models, Alzheimer’s disease, data segmentation, medical art, medical visualization, patient data,
- MeSH
- Models, Anatomic * MeSH
- Humans MeSH
- Brain MeSH
- Software MeSH
- Virtual Reality * MeSH
- Imaging, Three-Dimensional methods MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
Large biomolecular structures are being determined experimentally on a daily basis using established techniques such as crystallography and electron microscopy. In addition, emerging integrative or hybrid methods (I/HM) are producing structural models of huge macromolecular machines and assemblies, sometimes containing 100s of millions of non-hydrogen atoms. The performance requirements for visualization and analysis tools delivering these data are increasing rapidly. Significant progress in developing online, web-native three-dimensional (3D) visualization tools was previously accomplished with the introduction of the LiteMol suite and NGL Viewers. Thereafter, Mol* development was jointly initiated by PDBe and RCSB PDB to combine and build on the strengths of LiteMol (developed by PDBe) and NGL (developed by RCSB PDB). The web-native Mol* Viewer enables 3D visualization and streaming of macromolecular coordinate and experimental data, together with capabilities for displaying structure quality, functional, or biological context annotations. High-performance graphics and data management allows users to simultaneously visualise up to hundreds of (superimposed) protein structures, stream molecular dynamics simulation trajectories, render cell-level models, or display huge I/HM structures. It is the primary 3D structure viewer used by PDBe and RCSB PDB. It can be easily integrated into third-party services. Mol* Viewer is open source and freely available at https://molstar.org/.
- MeSH
- Internet MeSH
- Protein Conformation MeSH
- Macromolecular Substances chemistry MeSH
- Models, Molecular * MeSH
- Software * MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Research Support, N.I.H., Extramural MeSH
- Research Support, U.S. Gov't, Non-P.H.S. MeSH
- Names of Substances
- Macromolecular Substances MeSH
Cell culture methods have been developed in efforts to produce biologically relevant systems for developmental and disease modeling, and appropriate analytical tools are essential. Knowledge of ultrastructural characteristics represents the basis to reveal in situ the cellular morphology, cell-cell interactions, organelle distribution, niches in which cells reside, and many more. The traditional method for 3D visualization of ultrastructural components, serial sectioning using transmission electron microscopy (TEM), is very labor-intensive due to contentious TEM slice preparation and subsequent image processing of the whole collection. In this chapter, we present serial block-face scanning electron microscopy, together with complex methodology for spheroid formation, contrasting of cellular compartments, image processing, and 3D visualization. The described technique is effective for detailed morphological analysis of stem cell spheroids, organoids, as well as organotypic cell cultures.
- Keywords
- 3D visualization, Image reconstruction, Image segmentation, Morphology, Organoid, SBF-SEM, Scanning electron microscopy, Serial block-face, Spheroid, Stem cell, Ultrastructure,
- MeSH
- Spheroids, Cellular ultrastructure MeSH
- Embryonic Stem Cells ultrastructure MeSH
- Cells, Cultured MeSH
- Humans MeSH
- Microscopy, Electron, Scanning methods MeSH
- Image Processing, Computer-Assisted MeSH
- Imaging, Three-Dimensional methods MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
This paper describes a new tool for eye-tracking data and their analysis with the use of interactive 3D models. This tool helps to analyse interactive 3D models easier than by time-consuming, frame-by-frame investigation of captured screen recordings with superimposed scanpaths. The main function of this tool, called 3DgazeR, is to calculate 3D coordinates (X, Y, Z coordinates of the 3D scene) for individual points of view. These 3D coordinates can be calculated from the values of the position and orientation of a virtual camera and the 2D coordinates of the gaze upon the screen. The functionality of 3DgazeR is introduced in a case study example using Digital Elevation Models as stimuli. The purpose of the case study was to verify the functionality of the tool and discover the most suitable visualization methods for geographic 3D models. Five selected methods are presented in the results section of the paper. Most of the output was created in a Geographic Information System. 3DgazeR works with the SMI eye-tracker and the low-cost EyeTribe tracker connected with open source application OGAMA, and can compute 3D coordinates from raw data and fixations.
- Keywords
- 3D analysis tool, 3D model, 3D visualization, Geographic Information System, cartography, eye-tracking,
- Publication type
- Journal Article MeSH
With the ever-expanding toolkit of molecular viewers, the ability to visualize macromolecular structures has never been more accessible. Yet, the idiosyncratic technical intricacies across tools and the integration complexities associated with handling structure annotation data present significant barriers to seamless interoperability and steep learning curves for many users. The necessity for reproducible data visualizations is at the forefront of the current challenges. Recently, we introduced MolViewSpec (homepage: https://molstar.org/mol-view-spec/, GitHub project: https://github.com/molstar/mol-view-spec), a specification approach that defines molecular visualizations, decoupling them from the varying implementation details of different molecular viewers. Through the protocols presented herein, we demonstrate how to use MolViewSpec and its 3D view-building Python library for creating sophisticated, customized 3D views covering all standard molecular visualizations. MolViewSpec supports representations like cartoon and ball-and-stick with coloring, labeling, and applying complex transformations such as superposition to any macromolecular structure file in mmCIF, BinaryCIF, and PDB formats. These examples showcase progress towards reusability and interoperability of molecular 3D visualization in an era when handling molecular structures at scale is a timely and pressing matter in structural bioinformatics as well as research and education across the life sciences. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Creating a MolViewSpec view using the MolViewSpec Python package Basic Protocol 2: Creating a MolViewSpec view with reference to MolViewSpec annotation files Basic Protocol 3: Creating a MolViewSpec view with labels and other advanced features Support Protocol 1: Computing rotation and translation vectors Support Protocol 2: Creating a MolViewSpec annotation file.
- Keywords
- 3D visualization, Protein Data Bank, interoperability, macromolecular structure, mmCIF,
- MeSH
- Macromolecular Substances chemistry MeSH
- Models, Molecular MeSH
- Software * MeSH
- Imaging, Three-Dimensional MeSH
- Publication type
- Journal Article MeSH
- Names of Substances
- Macromolecular Substances MeSH
The easiest and often most useful way to work with experimentally determined or computationally predicted structures of biomolecules is by viewing their three-dimensional (3D) shapes using a molecular visualization tool. Mol* was collaboratively developed by RCSB Protein Data Bank (RCSB PDB, RCSB.org) and Protein Data Bank in Europe (PDBe, PDBe.org) as an open-source, web-based, 3D visualization software suite for examination and analyses of biostructures. It is capable of displaying atomic coordinates and related experimental data of biomolecular structures together with a variety of annotations, facilitating basic and applied research, training, education, and information dissemination. Across RCSB.org, the RCSB PDB research-focused web portal, Mol* has been implemented to support single-mouse-click atomic-level visualization of biomolecules (e.g., proteins, nucleic acids, carbohydrates) with bound cofactors, small-molecule ligands, ions, water molecules, or other macromolecules. RCSB.org Mol* can seamlessly display 3D structures from various sources, allowing structure interrogation, superimposition, and comparison. Using influenza A H5N1 virus as a topical case study of an important pathogen, we exemplify how Mol* has been embedded within various RCSB.org tools-allowing users to view polymer sequence and structure-based annotations integrated from trusted bioinformatics data resources, assess patterns and trends in groups of structures, and view structures of any size and compositional complexity. In addition to being linked to every experimentally determined biostructure and Computed Structure Model made available at RCSB.org, Standalone Mol* is freely available for visualizing any atomic-level or multi-scale biostructure at rcsb.org/3d-view.
- Keywords
- 3D biostructure, Protein Data Bank, global health, influenza A H5N1 virus, molecular visualization, open‐source, pandemic preparedness, viral pathogen, virus life cycle, web‐based,
- MeSH
- Databases, Protein MeSH
- Protein Conformation MeSH
- Models, Molecular MeSH
- Proteome * chemistry MeSH
- Software * MeSH
- Viral Proteins chemistry MeSH
- Influenza A Virus, H5N1 Subtype * chemistry MeSH
- Publication type
- Journal Article MeSH
- Names of Substances
- Proteome * MeSH
- Viral Proteins MeSH
SUMMARY: Amino acid residues showing above background levels of conservation are often indicative of functionally significant regions within a protein. Understanding how the sequence conservation profile relates in space requires projection onto a protein structure, a potentially time-consuming process. 3DPatch is a web application that streamlines this task by automatically generating multiple sequence alignments (where appropriate) and finding structural homologs, presenting the user with a choice of structures matching their query, annotated with residue conservation scores in a matter of seconds. AVAILABILITY AND IMPLEMENTATION: 3DPatch is written in JavaScript and is freely available at http://www.skylign.org/3DPatch/. Mozilla Firefox, Google Chrome, and Safari web browsers are supported. Source code is available under MIT license at https://github.com/davidjakubec/3DPatch. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
- MeSH
- Databases, Protein MeSH
- Web Browser MeSH
- Protein Conformation * MeSH
- Humans MeSH
- Sequence Alignment * MeSH
- Software * MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
Ever-increasing availability of experimental volumetric data (e.g., in .ccp4, .mrc, .map, .rec, .zarr, .ome.tif formats) and advances in segmentation software (e.g., Amira, Segger, IMOD) and formats (e.g., .am, .seg, .mod, etc.) have led to a demand for efficient web-based visualization tools. Despite this, current solutions remain scarce, hindering data interpretation and dissemination. Previously, we introduced Mol* Volumes & Segmentations (Mol* VS), a web application for the visualization of volumetric, segmentation, and annotation data (e.g., semantically relevant information on biological entities corresponding to individual segmentations such as Gene Ontology terms or PDB IDs). However, this lacked important features such as the ability to edit annotations (e.g., assigning user-defined descriptions of a segment) and seamlessly share visualizations. Additionally, setting up Mol* VS required a substantial programming background. This article presents an updated version, Mol* VS 2.0, that addresses these limitations. As part of Mol* VS 2.0, we introduce the Annotation Editor, a user-friendly graphical interface for editing annotations, and the Volumes & Segmentations Toolkit (VSToolkit) for generating shareable files with visualization data. The outlined protocols illustrate the utilization of Mol* VS 2.0 for visualization of volumetric and segmentation data across various scales, showcasing the progress in the field of molecular complex visualization. © 2024 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: VSToolkit-setting up and visualizing a user-constructed Mol* VS 2.0 database entry Basic Protocol 2: VSToolkit-visualizing multiple time frames and volume channels Support Protocol 1: Example: Adding database entry idr-13457537 Alternate Protocol 1: Local-server-and-viewer-visualizing multiple time frames and volume channels Support Protocol 2: Addition of database entry custom-tubhiswt Basic Protocol 3: VSToolkit-visualizing a specific channel and time frame Basic Protocol 4: VSToolkit-visualizing geometric segmentation Basic Protocol 5: VSToolkit-visualizing lattice segmentations Alternate Protocol 2: "Local-server-and-viewer"-visualizing lattice segmentations Basic Protocol 6: "Local-server-and-viewer"-visualizing multiple volume channels Support Protocol 3: Deploying a server API Support Protocol 4: Hosting Mol* viewer with VS extension 2.0 Support Protocol 5: Example: Addition of database entry empiar-11756 Support Protocol 6: Example: Addition of database entry emd-1273 Support Protocol 7: Editing annotations Support Protocol 8: Addition of database entry idr-5025553.
- Keywords
- 3D visualization tools, annotation data, large‐scale datasets, segmentation data, volumetric data,
- MeSH
- Internet MeSH
- Computer Graphics MeSH
- Software * MeSH
- User-Computer Interface MeSH
- Data Visualization MeSH
- Publication type
- Journal Article MeSH
The advent of cryo-electron microscopy (cryo-EM) and cryo-electron tomography (cryo-ET), coupled with computational modeling, has enabled the creation of integrative 3D models of viruses, bacteria, and cellular organelles. These models, composed of thousands of macromolecules and billions of atoms, have historically posed significant challenges for manipulation and visualization without specialized molecular graphics tools and hardware. With the recent advancements in GPU rendering power and web browser capabilities, it is now feasible to render interactively large molecular scenes directly on the web. In this work, we introduce Mesoscale Explorer, a web application built using the Mol* framework, dedicated to the visualization of large-scale molecular models ranging from viruses to cell organelles. Mesoscale Explorer provides unprecedented access and insight into the molecular fabric of life, enhancing perception, streamlining exploration, and simplifying visualization of diverse data types, showcasing the intricate details of these models with unparalleled clarity.
