LDDT (Local Distance Difference Test)

... is a method for evaluating the quality of protein structure models compared to a reference structure. It is incorporated into the Structure Assessment tool for comprehensive model evaluation.

Mariani V, Biasini M, Barbato A, Schwede T

lDDT: a local superposition-free score for comparing protein structures and models using distance difference tests.

Bioinformatics 29, 2722-2728. (2013) 2398656810.1093/bioinformatics/btt473

Key Features

• It is a superposition-free score that evaluates local distance differences between atoms in a model and a reference structure
• LDDT considers all atoms in the model, not just backbone atoms, allowing it to assess side chain accuracy
• It does not require global superposition of structures, making it less sensitive to domain movements in multi-domain proteins
• The score ranges from 0 to 1, with higher values indicating better agreement between the model and reference

Calculation Method

LDDT is calculated as follows:

• For each atom pair in the reference structure within a certain distance (by default 15 Å), the corresponding distance in the model is compared
• Distances are considered preserved if they are within specified thresholds (0.5 Å, 1 Å, 2 Å, and 4 Å)
• The final score is the average fraction of preserved distances across these four thresholds
• By default, stereochemical quality checks can be incorporated to penalize unrealistic local geometry

Applications

• Assessing protein structure prediction accuracy, especially in automated evaluation pipelines
• Comparing models to ensembles of structures (e.g. NMR models) without selecting a single reference
• Evaluating local model quality in specific regions like binding sites
• Classifying prediction difficulty in structure prediction experiments

LDDT provides a robust measure of local structural similarity that captures side chain accuracy while being less affected by domain movements compared to global superposition-based scores.

To use the deprecated implementation of LDDT, you can still visit LDDT (2013). But we would like to know why you want to use this version! Please drop us an email and share your thoughts on what makes it useful for you.