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Comprehensive Protein and Nucleic Acid Structural Dataset
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About
This collection provides comprehensive data on protein and nucleic acid structures, detailing classifications, experimental methods, and sequence information. The dataset includes information on crystallization conditions and macromolecule types, with each entry linked by a unique identifier.
Features:
- structureId: Unique identifier for each structure.
- classification: Functional category of the macromolecule (e.g., DNA-RNA hybrid, protein).
- experimentalTechnique: Method used to determine the structure, such as X-ray diffraction.
- macromoleculeType: Type of macromolecule, such as DNA, RNA, or Protein.
- residueCount: Total number of residues in the structure.
- resolution: Resolution of the structure in angstroms.
- structureMolecularWeight: Molecular weight of the macromolecule in Daltons.
- crystallizationMethod: Method used to crystallize the structure, such as vapor diffusion.
- crystallizationTempK: Temperature (in Kelvin) used during crystallization.
- densityMatthews: Matthews coefficient indicating solvent content in the crystal.
- densityPercentSol: Percentage of solvent in the crystallized structure.
- pdbxDetails: Additional details on crystallization conditions.
- phValue: pH level during crystallization.
- publicationYear: Year the structure was published.
- chainId: Identifier for each chain in multi-chain structures.
- sequence: Amino acid or nucleotide sequence of the macromolecule.
- residueCount (Sequence): Residue count for each sequence in the dataset.
Usage:
Ideal for structural biology research, bioinformatics, and pharmaceutical development. The dataset can be used for applications such as studying protein interactions, drug design, and macromolecular function.
Coverage:
This dataset covers diverse protein and nucleic acid structures deposited in the Protein Data Bank (PDB), spanning various structural classes and experimental techniques.
License:
Open Database License (ODbL)
Who Can Use It:
- Researchers and students in bioinformatics or molecular biology.
- Pharmaceutical scientists involved in drug discovery.
- Data scientists interested in biomolecular analysis.
How to Use It:
The dataset can be used to:
- Analyze macromolecular structures and their functions.
- Study structural characteristics related to specific biological functions.
- Build computational models for drug design and biomolecular interactions.
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