Side chain flexibility and the symmetry of protein homodimers

Abstract

A comprehensive analysis of crystallographic data of 565 high-resolution protein homodimers comprised of over 250,000 residues suggests that amino acids form two groups that differ in their tendency to distort or symmetrize the structure of protein homodimers. Residues of the first group tend to distort the protein homodimer and generally have long or polar side chains. These include: Lys, Gln, Glu, Arg, Asn, Met, Ser, Thr and Asp. Residues of the second group contribute to protein symmetry and are generally characterized by short or aromatic side chains. These include: Ile, Pro, His, Val, Cys, Leu, Trp, Tyr, Phe, Ala and Gly. The distributions of the continuous symmetry measures of the proteins and the continuous chirality measures of their building blocks highlight the role of side chain geometry and the interplay between entropy and symmetry in dictating the conformational flexibility of proteins.

From Chaos to Ordering: New Studies in the Shannon Entropy of 2D Patterns

“…Thus, clearly distinguished 2D ordering emerged from the aforementioned mathematical procedure applied to the initially random set of points. We quantified the ordering with Voronoi entropy and the continuous measure of symmetry [ 24 , 25 , 26 , 27 , 28 , 29 ]. The Shannon (Voronoi) entropy and the continuous measure of symmetry of the addressed patterns demonstrated pronounced asymptotic behavior, while approaching the close asymptotic values with the increase in the number of iteration steps.…”

“…Now we introduce the continuous symmetry measure (abbreviated CSM), as it was defined in references [ 24 , 25 , 26 ]. Consider a non-symmetrical shape consisting of points , (which are the seed points of the given Voronoi diagram) characterized by a given symmetry group G .…”

“…At the first step, the points of the nearest shape possessing the G -symmetry must be identified. An algorithm that identifies the set of points that constitutes this symmetrical shape was introduced in references [ 24 , 25 , 26 ]. Figure 2 depicts an equilateral triangle representing the symmetric shape that corresponds to the given non-symmetric triangle .…”

“…The quantification of 2D ordering is crucial for understanding phase transitions [ 1 , 2 , 3 , 4 ], the characterization of attractors in non-linear systems [ 5 ], the treatment of images [ 6 ] and machine learning applied for study of physical systems [ 7 , 8 , 9 ]. Various measures and mathematical procedures were implemented for the quantification of ordering in 2D patterns, including Voronoi tessellations followed by the calculation of the information (Shannon) entropy of the distribution of the Voronoi polygons (which is also called the Voronoi entropy and abbreviated in the text as VE; VE below within the text denotes the Shannon entropy) [ 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 ], Minkovski functionals [ 18 , 19 , 20 ], method of correlation functions [ 21 , 22 , 23 ], and calculation of the recently introduced continuous and Shannon measures of symmetry [ 6 , 24 , 25 , 26 , 27 ]. It was demonstrated that the introduced measures of symmetry do not necessarily correlate [ 27 , 28 ].…”

Functional Characterization of 21 Rare Allelic CYP1A2 Variants Identified in a Population of 4773 Japanese Individuals by Assessing Phenacetin O-Deethylation

“…The Gly233Arg substitution, located in a highly conserved region, caused notable structural changes. The hydrophobic Gly residue often grants greater flexibility to the protein structure than Arg [ 45 , 46 ]. This substitution appears to cause changes in the proximity between the F helix and heme and Arg, allowing further stabilization of the protein structure and potentially altering its folding capacity.…”