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 .

Structure-function relationships are a core concept in many STEM disciplines. Most biology curricula introduce students to macromolecules, their building blocks, and other small molecules that play key roles in biological processes. However, the shapes, interactions, and functions of these molecules are often discussed using schematic diagrams, ignoring the vast amounts of three-dimensional structural and bioinformatics data freely available from public data resources. Keeping up with and incorporating the rapidly evolving data, tools, and resources in suitable, structure-function focused lessons can be time-consuming and challenging. A group of experienced biology, chemistry, and biochemistry educators collaboratively developed the "Box of Lessons" (BOL) to engage students and educators in authentic explorations, reinforcing disciplinary concepts, while developing skills in biomolecular visualization and use of public bioinformatics data resources and tools. The BOL consists of multimedia learning materials, ready-to-use, student- and educator-facing worksheets with teaching notes, aligned with ASBMB learning goals. Materials in this collection have been reviewed and piloted by undergraduate educators before its publication on PDB-101, as modular open educational resources. Educators are encouraged to select BOL elements relevant to their curricular context and adapt them to fit their students' needs and learning goals.

Molecular origami offers an offline way to explore the 3D structures of biology. Visit PDB101.rcsb.org to download free paper models of DNA, green fluorescent protein, viruses, and more.

Open access to three-dimensional atomic-level biostructure information from the Protein Data Bank (PDB) facilitated discovery/development of 100% of the 34 new low molecular weight, protein-targeted, antineoplastic agents approved by the US FDA 2019–2023. Analyses of PDB holdings, the scientific literature, and related documents for each drug-target combination revealed that the impact of structural biologists and public-domain 3D biostructure data was broad and substantial, ranging from understanding target biology (100% of all drug targets), to identifying a given target as likely druggable (100% of all targets), to structure-guided drug discovery (>80% of all new small-molecule drugs, made up of 50% confirmed and >30% probable cases). In addition to aggregate impact assessments, illustrative case studies are presented for six first-in-class small-molecule anti-cancer drugs, including a selective inhibitor of nuclear export targeting Exportin 1 (selinexor, Xpovio), an ATP-competitive CSF-1R receptor tyrosine kinase inhibitor (pexidartinib,Turalia), a non-ATP-competitive inhibitor of the BCR-Abl fusion protein targeting the myristoyl binding pocket within the kinase catalytic domain of Abl (asciminib, Scemblix), a covalently-acting G12C KRAS inhibitor (sotorasib, Lumakras or Lumykras), an EZH2 methyltransferase inhibitor (tazemostat, Tazverik), and an agent targeting the basic-Helix-Loop-Helix transcription factor HIF-2α (belzutifan, Welireg).