Amino acid interaction preferences in proteins

Abstract

Understanding the key factors that influence the interaction preferences of amino acids in the folding of proteins have remained a challenge. Here we present a knowledge-based approach for determining the effective interactions between amino acids based on amino acid type, their secondary structure, and the contact based environment that they find themselves in the native state structure as measured by their number of neighbors. We find that the optimal information is approximately encoded in a 60 x 60 matrix describing the 20 types of amino acids in three distinct secondary structures (helix, beta strand, and loop). We carry out a clustering scheme to understand the similarity between these interactions and to elucidate a nonredundant set. We demonstrate that the inferred energy parameters can be used for assessing the fit of a given sequence into a putative native state structure.

Figure 1

A pictorial representation of the environment based scoring matrix. The blue color is for the most negative score (the most attractive) and the red is for the highest positive value (the most repulsive). The range of scores (−2.737 to +2.333) has been divided into 10 equal intervals and are represented by different colors decreasing from blue to red. [Color figure can be viewed in the online issue, which is available at www.interscience.wiley.com.]

Figure 2

Distribution of the number of contacts between one amino acid and other amino acids in their respective secondary structural environment. Three bars are shown for each amino acid, representing the interaction of other amino acids in helix, beta sheet, and loop environments. (a), (b), and (c) are the plots corresponding to the selected residues in helix, beta-sheet, and loop environment, respectively. [Color figure can be viewed in the online issue, which is available at www.interscience.wiley.com.]

Figure 3

A plot of the modification factor F_A−x (on Y-axis) of 20 amino acids in five different environments. The values are relative to the average and so a more negative value indicates that it is less favored than the other environments and vice versa. [Color figure can be viewed in the online issue, which is available at www.interscience.wiley.com.]

Figure 4

Modification factor (on Y-axis) for all 20 amino acids in five ASA based environments. [Color figure can be viewed in the online issue, which is available at www.interscience.wiley.com.]