Coupling Between Properties of the Protein Shape and the Rate of Protein Folding
Overview
Affiliations
There are several important questions on the coupling between properties of the protein shape and the rate of protein folding. We have studied a series of structural descriptors intended for describing protein shapes (the radius of gyration, the radius of cross-section, and the coefficient of compactness) and their possible connection with folding behavior, either rates of folding or the emergence of folding intermediates, and compared them with classical descriptors, protein chain length and contact order. It has been found that when a descriptor is normalized to eliminate the influence of the protein size (the radius of gyration normalized to the radius of gyration of a ball of equal volume, the coefficient of compactness defined as the ratio of the accessible surface area of a protein to that of an ideal ball of equal volume, and relative contact order) it completely looses its ability to predict folding rates. On the other hand, when a descriptor correlates well with protein size (the radius of cross-section and absolute contact order in our consideration) then it correlates well with the logarithm of folding rates and separates reasonably well two-state folders from multi-state ones. The critical control for the performance of new descriptors demonstrated that the radius of cross-section has a somewhat higher predictive power (the correlation coefficient is -0.74) than size alone (the correlation coefficient is -0.65). So, we have shown that the numerical descriptors of the overall shape-geometry of protein structures are one of the important determinants of the protein-folding rate and mechanism.
Bian B, Kumagai T, Saito Y Imeta. 2024; 2(4):e148.
PMID: 38868219 PMC: 10989810. DOI: 10.1002/imt2.148.
Identifying potential monkeypox virus inhibitors: an study targeting the A42R protein.
Ashley C, Broni E, Wood C, Okuneye T, Ojukwu M, Dong Q Front Cell Infect Microbiol. 2024; 14:1351737.
PMID: 38500508 PMC: 10945028. DOI: 10.3389/fcimb.2024.1351737.
Harihar B, Saravanan K, Gromiha M, Selvaraj S Mol Biotechnol. 2024; 67(3):862-884.
PMID: 38498284 DOI: 10.1007/s12033-024-01119-4.
Structural insights into the binding of zoledronic acid with RANKL computational simulations.
Wang R, Zhang W, Ma H, Zou D, Zhang Z, Wang S Front Mol Biosci. 2022; 9:992473.
PMID: 36200071 PMC: 9527314. DOI: 10.3389/fmolb.2022.992473.
Comparative analysis of non structural protein 1 of SARS-CoV2 with SARS-CoV1 and MERS-CoV: An study.
Chaudhuri A J Mol Struct. 2021; 1243:130854.
PMID: 34121768 PMC: 8188392. DOI: 10.1016/j.molstruc.2021.130854.