Influence of Disease-Causing Mutations on Protein Structural Networks

Area of Science:

• Biophysics
• Structural Biology
• Computational Biology

Background:

• Protein tertiary structure analysis is crucial for understanding function and disease.
• Protein Structure Networks (PSNs) offer a robust framework for studying residue interactions.
• Disease-causing mutations can subtly or dramatically alter protein structures and functions.

Purpose of the Study:

• To investigate the impact of disease-causing mutations on protein structures using weighted PSNs.
• To analyze how mutations affect global and local network properties in proteins.
• To understand the propagation of mutation effects across protein structures, potentially impacting distant functional sites.

Main Methods:

• Construction and analysis of weighted Protein Structure Networks (PSNs) for wildtype and mutant proteins.
• Utilizing curated mutation data from UniProtKB/Swiss-Prot and 3D structures from the Protein Data Bank.
• Comparative analysis of network dissimilarity at global and local levels to identify mutation-induced changes.

Main Results:

• Identified significant variations in network parameters correlating with altered protein function and stability due to mutations.
• Observed cases where mutations caused substantial all-atom network dissimilarity with minimal backbone changes, and vice versa.
• Demonstrated that mutations can influence structurally distant sites within the protein network.

Conclusions:

• Weighted PSNs are effective tools for dissecting the structural consequences of disease mutations.
• Mutation effects can propagate through the protein structure, impacting function and stability.
• Understanding network alterations provides insights into disease mechanisms and potential therapeutic targets.