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.
Highlights
Symmetry plays a central role in protein structure [1,2,3,4,5,6]
The methodology of continuous symmetry and chirality measures offers accurate and efficient tools to describe protein structure, both for the whole protein and at the residue level. This method of quantification helps understand where and why proteins fail to reach perfect symmetry, and what amino acids are responsible for this failure
Our findings suggest that amino acids form two groups with different tendency to distort the symmetry of protein homomers in cases of near symmetry
Summary
Symmetry plays a central role in protein structure [1,2,3,4,5,6]. In the past two decades, various researchers have suggested that symmetry is associated with increased structural stability, higher efficiency of oligomerization mechanisms, possible reduction of errors in biological synthesis and allosteric regulation, among others [1,2,3,4, 7]. Efforts have been made to define and quantify protein symmetry levels using various methods based on quaternary-structure-alignment algorithms [9,10,11,12,13,14,15,16,17,18,19]. These methods involve superposing one peptide on another, and estimating their alignment by root mean square deviation (RMSD) of matching α-carbons, or by a related scoring formula.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
