Computing disease-linked SOD1 mutations: deciphering protein stability and patient-phenotype relations

Area of Science:

• Biochemistry and Molecular Biology
• Computational Biology
• Genetics

Background:

• Protein stability is crucial for biotechnology, cell biology, and drug design.
• Computational models offer efficient alternatives to experimental methods for assessing amino acid substitution effects.
• Cu/Zn Superoxide Dismutase 1 (SOD1) is a key protein for studying genotype-phenotype correlations in Amyotrophic Lateral Sclerosis (ALS).

Purpose of the Study:

• To evaluate the performance of eight protein stability prediction calculators.
• To assess the structure sensitivity of these computational methods.
• To correlate computed SOD1 stability changes with ALS patient data.

Main Methods:

• Benchmarking eight protein stability calculators (PoPMuSiC, I-Mutant, CUPSAT, FoldX, mCSM, BeatMusic, ENCoM) against 54 experimental SOD1 mutation stability changes.
• Utilizing four high-resolution protein structures to test method sensitivity.
• Employing Bland-Altman plots for agreement analysis.
• Analyzing patient data alongside experimental and computed protein stabilities.

Main Results:

• PoPMuSiC and FoldX demonstrated superior performance in predicting SOD1 stability changes.
• The predictive performance of the calculators was largely independent of protein structure.
• A correlation was observed between SOD1 stability changes and ALS patient survival times.

Conclusions:

• PoPMuSiC and FoldX are recommended for predicting SOD1 stability changes.
• Protein stability is a significant factor in SOD1 pathogenicity and ALS progression.
• Computational stability predictions can inform genotype-phenotype correlations in neurodegenerative diseases.