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  1. 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. 
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    Free, publicly-accessible full text available July 18, 2025
  2. Abstract Motivation

    Tools for pairwise alignments between 3D structures of proteins are of fundamental importance for structural biology and bioinformatics, enabling visual exploration of evolutionary and functional relationships. However, the absence of a user-friendly, browser-based tool for creating alignments and visualizing them at both 1D sequence and 3D structural levels makes this process unnecessarily cumbersome.

    Results

    We introduce a novel pairwise structure alignment tool (rcsb.org/alignment) that seamlessly integrates into the RCSB Protein Data Bank (RCSB PDB) research-focused RCSB.org web portal. Our tool and its underlying application programming interface (alignment.rcsb.org) empowers users to align several protein chains with a reference structure by providing access to established alignment algorithms (FATCAT, CE, TM-align, or Smith–Waterman 3D). The user-friendly interface simplifies parameter setup and input selection. Within seconds, our tool enables visualization of results in both sequence (1D) and structural (3D) perspectives through the RCSB PDB RCSB.org Sequence Annotations viewer and Mol* 3D viewer, respectively. Users can effortlessly compare structures deposited in the PDB archive alongside more than a million incorporated Computed Structure Models coming from the ModelArchive and AlphaFold DB. Moreover, this tool can be used to align custom structure data by providing a link/URL or uploading atomic coordinate files directly. Importantly, alignment results can be bookmarked and shared with collaborators. By bridging the gap between 1D sequence and 3D structures of proteins, our tool facilitates deeper understanding of complex evolutionary relationships among proteins through comprehensive sequence and structural analyses.

    Availability and implementation

    The alignment tool is part of the RCSB PDB research-focused RCSB.org web portal and available at rcsb.org/alignment. Programmatic access is available via alignment.rcsb.org. Frontend code has been published at github.com/rcsb/rcsb-pecos-app. Visualization is powered by the open-source Mol* viewer (github.com/molstar/molstar and github.com/molstar/rcsb-molstar) plus the Sequence Annotations in 3D Viewer (github.com/rcsb/rcsb-saguaro-3d).

     
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  3. Recent advances in Artificial Intelligence and Machine Learning (e.g., AlphaFold, RosettaFold, and ESMFold) enable prediction of three-dimensional (3D) protein structures from amino acid sequences alone at accuracies comparable to lower-resolution experimental methods. These tools have been employed to predict structures across entire proteomes and the results of large-scale metagenomic sequence studies, yielding an exponential increase in available biomolecular 3D structural information. Given the enormous volume of this newly computed biostructure data, there is an urgent need for robust tools to manage, search, cluster, and visualize large collections of structures. Equally important is the capability to efficiently summarize and visualize metadata, biological/biochemical annotations, and structural features, particularly when working with vast numbers of protein structures of both experimental origin from the Protein Data Bank (PDB) and computationally-predicted models. Moreover, researchers require advanced visualization techniques that support interactive exploration of multiple sequences and structural alignments. This paper introduces a suite of tools provided on the RCSB PDB research-focused web portal RCSB. org, tailor-made for efficient management, search, organization, and visualization of this burgeoning corpus of 3D macromolecular structure data.

     
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  4. Abstract

    The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB, RCSB.org), the US Worldwide Protein Data Bank (wwPDB, wwPDB.org) data center for the global PDB archive, provides access to the PDB data via its RCSB.org research-focused web portal. We report substantial additions to the tools and visualization features available at RCSB.org, which now delivers more than 227000 experimentally determined atomic-level three-dimensional (3D) biostructures stored in the global PDB archive alongside more than 1 million Computed Structure Models (CSMs) of proteins (including models for human, model organisms, select human pathogens, crop plants and organisms important for addressing climate change). In addition to providing support for 3D structure motif searches with user-provided coordinates, new features highlighted herein include query results organized by redundancy-reduced Groups and summary pages that facilitate exploration of groups of similar proteins. Newly released programmatic tools are also described, as are enhanced training opportunities.

     
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  5. Abstract Motivation

    Mapping positional features from one-dimensional (1D) sequences onto three-dimensional (3D) structures of biological macromolecules is a powerful tool to show geometric patterns of biochemical annotations and provide a better understanding of the mechanisms underpinning protein and nucleic acid function at the atomic level.

    Results

    We present a new library designed to display fully customizable interactive views between 1D positional features of protein and/or nucleic acid sequences and their 3D structures as isolated chains or components of macromolecular assemblies.

    Availability and implementation

    https://github.com/rcsb/rcsb-saguaro-3d.

    Supplementary information

    Supplementary data are available at Bioinformatics online.

     
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  6. Abstract Motivation

    Membrane proteins are encoded by approximately one fifth of human genes but account for more than half of all US FDA approved drug targets. Thanks to new technological advances, the number of membrane proteins archived in the PDB is growing rapidly. However, automatic identification of membrane proteins or inference of membrane location is not a trivial task.

    Results

    We present recent improvements to the RCSB Protein Data Bank web portal (RCSB PDB, rcsb.org) that provide a wealth of new membrane protein annotations integrated from four external resources: OPM, PDBTM, MemProtMD and mpstruc. We have substantially enhanced the presentation of data on membrane proteins. The number of membrane proteins with annotations available on rcsb.org was increased by ∼80%. Users can search for these annotations, explore corresponding tree hierarchies, display membrane segments at the 1D amino acid sequence level, and visualize the predicted location of the membrane layer in 3D.

    Availability and implementation

    Annotations, search, tree data and visualization are available at our rcsb.org web portal. Membrane visualization is supported by the open-source Mol* viewer (molstar.org and github.com/molstar/molstar).

    Supplementary information

    Supplementary data are available at Bioinformatics online.

     
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