d-StructMAn: Containerized structural annotation on the scale from genetic variants to whole proteomes

Area of Science:

• Genomics
• Structural Biology
• Computational Biology

Background:

• Genetic variants influence disease phenotypes through effects on protein structure and interactions.
• Understanding these effects requires detailed structural annotation of variants within protein complexes.
• Intermolecular interactions are evolutionarily conserved, providing a basis for functional interpretation.

Purpose of the Study:

• To introduce d-StructMAn, a novel computational method for structural annotation of genetic variants.
• To implement d-StructMAn as an efficient and user-friendly tool, available as a Docker container.
• To apply d-StructMAn to large-scale human genetic datasets for proteome-wide annotation.

Main Methods:

• Development of a novel computational method (d-StructMAn) for structural annotation.
• Implementation of the method in a Docker container for accessibility and efficiency.
• Application to large datasets including ClinVar variants and the entire human proteome.

Main Results:

• d-StructMAn enables structural annotation of local genetic variants (SNVs, in-frame indels).
• The tool successfully annotated over 46% of human proteome positions, covering more than 60% of proteins.
• Annotation was performed on extensive datasets, including all ClinVar variants.

Conclusions:

• d-StructMAn is a pioneering, efficient tool for annotating protein-coding genetic variation.
• It provides structural context for variants, focusing on intermolecular interactions.
• The tool is suitable for proteome-scale analyses and aids in predicting genotype-phenotype relationships.