Modeling and analyzing three-dimensional structures of human disease proteins

Area of Science:

• Structural biology
• Genomics
• Computational biology

Background:

• Understanding protein 3D structures is crucial for deciphering molecular mechanisms and disease pathologies.
• Most human diseases lack detailed structural insights into protein malfunction.
• Disease-related mutations provide clues to protein dysfunction.

Purpose of the Study:

• To model human disease-related proteins using homology modeling.
• To analyze structural characteristics of disease mutations and compare them with non-synonymous single nucleotide polymorphisms (SNPs).
• To investigate the impact of mutations on protein structure and function, particularly protein-protein interactions.

Main Methods:

• Homology modeling was employed to generate 3D structures for 1484 domains from 874 human disease proteins.
• Structural coverage was achieved for 48% of residues in 1237 human disease proteins, integrating modeled and experimental structures.
• Disease mutations and non-synonymous SNPs were analyzed for their distribution on protein surfaces and within protein complexes.

Main Results:

• Disease-related mutations showed a statistically significant preference for clustering on protein surfaces.
• Non-synonymous SNPs were found to be randomly distributed on protein surfaces.
• Analysis of 8 experimentally determined protein complexes revealed disease mutations located at protein-protein binding interfaces, unlike SNPs.

Conclusions:

• Disease mutations likely affect protein-protein interaction interfaces, offering insights into disease mechanisms.
• The non-uniform distribution of disease mutations can guide the modeling and evaluation of human disease proteins and their complexes.
• A new resource, Disease Protein Models (DPM), was established to facilitate research on disease-mutation relationships in the context of 3D protein structures.