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Single amino-acid substitution in a protein affects its structure and function. These changes are the primary reasons for the advent of many complex diseases. Analyzing single point mutations in a protein is crucial to see their impact and to understand the disease mechanism. This has given many biophysical resources, including databases and web-based tools to explore the effects of mutations on the structure and function of human proteins. For a given mutation, each tool provides a score-based outcomes which indicate deleterious probability. In recent years, developments in existing programs and the introduction of new prediction algorithms have transformed the state-of-the-art protein mutation analysis. In this study, we have performed a systematic study of the most commonly used mutational analysis programs (10 sequence-based and 5 structure-based) to compare their prediction efficiency. We have carried out extensive mutational analyses using these tools for previously known pathogenic single point mutations of five different proteins. These analyses suggested that sequence-based tools, PolyPhen2, PROVEAN, and PMut, and structure-based web tool, mCSM have a better prediction accuracy. This study indicates that the employment of more than one program based on different approaches should significantly improve the prediction power of the available methods. [ABSTRACT FROM AUTHOR]

Parkinsonism-associated deglycase-PARK7/DJ-1 (PARK7) is a multifunctional protein having significant roles in inflammatory and immune disorders and cell protection against oxidative stress. Mutations in PARK7 may result in the onset and progression of a few neurodegenerative disorders such as Parkinson's disease. This study has analyzed the non-synonymous single nucleotide polymorphisms (nsSNPs) resulting in single amino acid substitutions in PARK7 to explore its disease-causing variants and their structural dysfunctions. Initially, we retrieved the mutational dataset of PARK7 from the Ensembl database and performed detailed analyses using sequence-based and structure-based approaches. The pathogenicity of the PARK7 was then performed to distinguish the destabilizing/deleterious variants. Aggregation propensity, noncovalent interactions, packing density, and solvent accessible surface area analyses were carried out on the selected pathogenic mutations. The SODA study suggested that mutations in PARK7 result in aggregation, inducing disordered helix and altering the strand propensity. The effect of mutations alters the number of hydrogen bonds and hydrophobic interactions in PARK7, as calculated from the Arpeggio server. The study indicated that the alteration in the hydrophobic contacts and frustration of the protein could alter the stability of the missense variants of the PARK7, which might result in disease progression. This study provides a detailed understanding of the destabilizing effects of single amino acid substitutions in PARK7. [ABSTRACT FROM AUTHOR]