Study On The Relationship Between Amino Acid Network Properties And Fe-SOD Thermostability

There has been considerable interest in protein thermostability in the field of biologicalscience. Considering protein consists of amino acids and amino acid-amino acid interactions,in this article, we use amino acid network (ANN) to describe protein structure.To better fullyunderstand the heat resistant mechanism of thermophilic protein, we need to find more factorsrelated to protein thermostability from the system level, and promote protein application inindustry.(1) We constructed six types of AANs based on the information contained in ironsuperoxide dismutase (Fe-SOD) three-dimensional structures. Analysis of Fe-SOD networkproperties such as degree, the characteristic path length and so forth, it was observed thatthermophilic Fe-SOD amino acid networks have the greater average degree, the strongeraverage strength and the higher Pearson correlation coefficient than mesophilic Fe-SODamino acid networks, but thermophilic Fe-SOD amino acid networks have shortercharacteristic path length than mesophilic Fe-SOD amino acid networks.(2) Analysis of the degree of distribution and rich club of these AANs indicated thatAANs have highly interacting nodes, namely, the Hubs. Most hubs are uniformly distributedin evolutionally conserved regular secondary structures to maintain Fe-SOD biologicalfunctionality. Moreover, a comparison of hubs in several Fe-SOD ANNs with differentthermostability levels revealed that hydrophobic amino acids, such as glycine, leucine, andphenylalanine, but not glutamine and threonine, have more interactions and form hubs and istherefore conducive to a more highly hydrophobic core and denser packing of thermostableFe-SOD. Increased numbers of hubs, increased numbers of hubs in3/10helices, turn structuresand especially in alpha helices, and the ratio of inner hubs in secondary structure are allimportant factors for Fe-SOD thermostability. Mutating Hub residues on the Fe-SOD surfaceimproves Fe-SOD thermostability by increasing hydrogen bond interactions.(3) We use complex network modularization analysis methods such as Girvan-Newmanand eigenvector method to modularize Fe-SOD AANs. It is observed that ANNs containobvious communities. Importantly, many secondary structures reside fully in identicalcommunities. In addition, an analysis of mesophilic and thermophilic Fe-SOD AAN’communities, revealed that highly thermally stable Fe-SOD AANs had more highlyassociated community structures than mesophilic Fe-SOD AANs. Thermophilic Fe-SODAANs also had more highly similar agreements between communities and secondarystructures than mesophilic Fe-SOD AANs. The communities in Fe-SOD AANs show thatdense interactions in modules can raise Fe-SOD thermal stability.(4) To find the differences of structure between mesophilic and thermophilic Fe-SODANNs, we use GRAAL and MI-GRAAL algrithms to global align ANNs. It was found thatless similarity between nodes in any two ANNs, while greater similarity between local regionsin two ANNs indicated that highly similarity regions may relate some Fe-SOD biologicalfunctions. The similarity between mesophilic Fe-SOD ANNs is more highly than between thermophiles Fe-SOD ANNs.(5) Analysis of Fe-SOD ANNs robustness, we observed that the key residues of ANNsmainly contain conserved residues, hydrophobic residues, residues in regular secondarystructures and Fe-SOD activity site residues. The comparison of key residues distribution indifferent thermal stability Fe-SOD, we found that key residues are more uniform distributionin thermophilic Fe-SOD. The uniform distribution of key residues, can improve the overallrobustness of Fe-SOD.These phenomena indicated that analyzed the relationship of proteinsequence-structure-function from the perspective of AANs is a promising area of futureresearch.