Mastering the LORE of protein structure.

Area of Science:

• Structural Biology
• Computational Biology
• Biochemistry

Background:

• Protein structure determination is crucial for understanding biological function.
• Traditional methods for protein model building and refinement can be complex and time-consuming.
• A need exists for advanced computational tools to assist in analyzing and manipulating protein structural data.

Purpose of the Study:

• To present the design, operation, and capabilities of LORE, a novel protein-database management tool.
• To introduce a computational approach for identifying and utilizing structural substructures within known protein crystal structures.
• To enhance molecular modeling and structure-refinement applications through advanced editing functionalities.

Main Methods:

• Development of LORE, a software tool integrating database management with structural analysis.
• Implementation of algorithms for searching a library of known crystal structures based on geometric similarity.
• Inclusion of sophisticated molecular editing capabilities for manipulating structural segments.

Main Results:

• LORE effectively searches for substructures of varying complexity, from simple turns to intricate assemblies of secondary structure elements.
• The tool provides advanced capabilities for manipulating and editing structural segments.
• Demonstrated utility of LORE in complementing traditional protein map-fitting and model-building programs.

Conclusions:

• LORE offers a valuable supplement to existing protein structure analysis software.
• The program's ability to identify and manipulate structural substructures significantly aids in molecular modeling and structure refinement.
• LORE represents a significant advancement in computational tools for structural biology.