Analysis of protein sequence/structure similarity relationships

Area of Science:

• Biochemistry
• Structural Biology
• Computational Biology

Background:

• Traditional analyses of protein sequence-structure relationships primarily focus on expected similarities between structurally similar proteins.
• A comprehensive understanding of diverse sequence-structure correlations, including unexpected ones, is lacking.

Purpose of the Study:

• To develop a general map of protein sequence-structure relationships encompassing all similarity and dissimilarity categories.
• To perform energetic analyses of these relationships and elucidate their underlying principles.

Main Methods:

• Categorization of protein relationships into four types: expected similarity (S), unexpected similarity (S(?)), expected dissimilarity (D), and unexpected dissimilarity (D(?)).
• Derivation of a formula linking sequence and structural deviations to protein stiffness in the expected similarity region (S).
• Analysis of energetic factors contributing to the presence or absence of proteins in different relationship categories.

Main Results:

• In the expected similarity region (S), trends are explained by protein stability and energetics; a derived formula relating sequence/structural deviations to stiffness shows good data fit.
• The absence of data in the unexpected similarity region (S?) is attributed to unfavorable energetics.
• The unexpected dissimilarity region (D?) is populated by proteins capable of significant structural changes, indicating adaptability.

Conclusions:

• Protein sequence-structure relationships are diverse and can be categorized based on similarity and dissimilarity.
• Protein energetics are fundamental to understanding these relationships, explaining observed patterns and data distributions.
• The study provides a framework for analyzing the interplay between sequence, structure, stability, and flexibility in proteins.