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

Abstract

Abstract Protein stability is a requisite in the field of biotechnology, cell biology and drug design. To understand effects of amino acid substitutions, computational models are preferred to save time and expenses. As a systemically important, highly abundant, stable protein, the knowledge of Cu/Zn Superoxide dismutase1 (SOD1) is important, making it a suitable test case for genotype-phenotype correlation in understanding ALS. Here, we report performance of eight protein stability calculators (PoPMuSiC 3.1, I-Mutant 2.0, I-Mutant 3.0, CUPSAT, FoldX, mCSM, BeatMusic and ENCoM) against 54 experimental stability changes due to mutations of SOD1. Four different high-resolution structures were used to test structure sensitivity that may affect protein calculations. Bland-Altman plot was also used to assess agreement between stability analyses. Overall, PoPMuSiC and FoldX emerge as the best methods in this benchmark. The relative performance of all the eight methods was very much structure independent, and also displayed less structural sensitivity. We also analyzed patient’s data in relation to experimental and computed protein stabilities for mutations of human SOD1. Correlation between disease phenotypes and stability changes suggest that the changes in SOD1 stability correlate with ALS patient survival times. Thus, the results clearly demonstrate the importance of protein stability in SOD1 pathogenicity.