DNATCO

DNATCO assigns Nucleotide Conformers (NtCs) and CANA codes to dinucleotide structures to classify and validate DNA and RNA conformations for structural analysis.

Key Features:

• Extensive Structural Database: Contains over 120,000 dinucleotides extracted from more than 2,000 non-redundant nucleic acid crystal structures that underpin conformational analysis.
• NtC and CANA Classification Systems: Employs Nucleotide Conformers (NtCs) and the Conformational Alphabet of Nucleic Acids (CANA) to categorize dinucleotides into 96+1 distinct conformers grouped into 15 CANA codes.
• Automated Assignment Protocol: Provides an automated protocol for assigning NtC classes and CANA codes to nucleic acid structures.
• Validation and Refinement Tools: Implements the confal validation score to quantify conformity to predefined NtC geometries and supports refinement of structures not initially assigned to any NtC class.
• Interactive Visualization: Offers an animated Interactive 3D Complement (I3DC) for visualizing DNA and RNA conformations on Proteopedia.
• File Format Support: Supports analysis of structures in mmCIF and PDB formats.

Scientific Applications:

• Structural Analysis: Provides detailed conformational classifications to aid analysis and validation of DNA and RNA structures, including guanine quadruplexes and regulatory protein complexes.
• Sequence-Dependent Recognition: Assesses sequence preferences for different conformers to support research into sequence-dependent recognition and nucleic acid–protein interactions.
• Structural Polymorphism Identification: Facilitates identification of structural polymorphisms in DNA and RNA to explore their roles in function and adaptation to binding partners.
• Modeling and Refinement: Supplies annotation and validation metrics to support modeling and refinement of nucleic acid structures and improve computational model accuracy.

Methodology:

Applies Fourier averaging and clustering to analyze torsion angles within dinucleotide units; uses statistical goodness-of-fit tests to assess sequence preferences for main conformers; employs pattern-recognition search algorithms to identify nontrivial structural patterns and novel RNA loop types.