Molecular Evolution Of Protein And Its Relationship With Intra-Molecular Interaction

The molecular evolution and the intra-and inter-molecular interaction of proteins are closely related.On one hand,some key interactions tend to be maintained during evolution.On the other hand,the protein evolves by changing certain intra-molecular interactions.Therefore,the study of the relationships between molecular evolution and intra-molecular interaction is essential to the understanding of structure-function relationship of protein and to the uncovering of mechanisms underlying molecular evolution of the protein.Here,the following studies were conducted to reveal the relationship between protein evolution and intra-molecular interaction.Ⅰ.Predicting protein-protein interaction interfaces from co-evolution informationIdentification of protein interaction interfaces is very important for understanding the molecular mechanisms underlying biological phenomena.Here,we present a novel method for predicting protein interaction interfaces from sequences by using PAM matrix(PIFPAM).Sequence alignments for interacting proteins were constructed and parsed into segments using sliding windows.By calculating distance matrix for each segment,the correlation coefficients between segments were estimated.The interaction interfaces were predicted by extracting highly correlated segment pairs from the correlation map.The predictions achieved an accuracy 0.41-0.71 for eight intra-protein interaction examples,and 0.07-0.60 for four inter-protein interaction examples.Compared with three previously published methods,PIFPAM predicted more contacting site pairs for 11 out of the 12 example proteins,and predicted at least 34%more contacting site pairs for eight proteins of them.The factors affecting the predictions were also analyzed.Since PIFPAM uses only the alignments of the two interacting proteins as input,it is especially useful when no three-dimensional protein structure data are available. Ⅱ.Improving the analysis of protein co-evolutionThe calculation of correlative coefficient of a pair of evolutionary trees has been used in the estimation of protein co-evolution and in the prediction of protein-protein interaction.However,in many cases,a high correlative coefficient is just only the result of their common evolutionary history rather than the interaction between them. Though efforts have been made to reduce the effect of the common evolutionary history,another key shortage of the method is still untouched,that is the lack of the statistics of the obtained correlative coefficient.For a given correlative coefficient,a P value is needed to give out the probability that an equal or a higher correlative coefficient is obtained by the random and independent mutation of the sites.Here in this study,we presented a method to compute this P value.Firstly,the evolutionary tree of the fusion protein of the proteins under study is constructed,and then this tree is used as a guide tree to simulate to produce multiple sets of sequences with each set having the same evolutionary history as the guide tree of the fusion protein.Because the simulation was conducted under the PAM model,i.e.the sites mutate randomly and independently,the probability that a given correlative coefficient is obtained by random and independent mutation could be calculated.And the P value is calculated as the sum of the probabilities that an equal or a higher correlative coefficient is obtained.For a given correlative coefficient smaller than 0.05,it is suggested that the two proteins co-evolve due to the correlated mutations between their sites.Using this method,the common evolutionary history ofα-andβ-subunits of phycocyanin were simulated,and 1000 sequence sets were obtained.The evolutionary trees of the simulated sequences were very similar to the guide tree constructed using the fusion sequence ofα-andβ-subunits(r=0.864±0.021),suggesting that the simulated sequences have similar evolutionary history as the fusion sequence ofα-andβ-subunits,and that they can be used to calculate the P values.The correlative coefficient for the interface residues of theα-andβ-subunits was 0.515(versus r=0.266±0.135 for simulated sequences),and the corresponding P value was 0.029, suggesting that the interface residues were correlated during the evolution.However, the correlative coefficient for the fullα-andβ-subunits was 0.644 with a P value 0.802,suggesting that this r value 0.644 probably come from the common evolutionary history(plus the random and independent evolution of the sites) rather than the correlated mutations.This disagreement looks like coming from two points. The first is the signal of common history is much stronger than the correlated mutations.The second is that different parts of a protein may have different evolutionary trees,and that the combination of different parts may lead to the decrease of the signal.Ⅲ.The analysis of protein intra-molecular networkEach protein molecular contains a huge intra-molecular interaction network with the nodes being the residues or groups and the edges being inter-group interactions. The nodes(sites) have different evolutionary rates,and some conserved sites tend to cluster together,suggesting that the clustered conserved sites might be subject to the same selection pressure.Here,the intra-(αβ) interaction network of phycocyanin was investigated.The results showed that the intra-(αβ) network comprisee 48 subnetworks each with a conserved core.The core residues of some subnetworks were completely conserved.Some subnetworks were related to the functional centers or structural centers of the protein.The three phycocyanobilins within one(αβ) are three functional centers,and they each corresponded to a completely conserved subnetwork with one phycocyanobilin surround by the completely conserved core sites.The conservation of each subnetwork decreased from the core to the periphery. Among the seven subnetworks whose size is bigger than ten residues,only two pair of them(among all 21 pairs of them) have a correlative coefficient with P smaller than 0.05.This result suggested that the functional centers in the protein were nearly independent during evolution.Ⅳ.The optimization of intra-molecular interactions during molecular evolution The cold adaptation mechanism of cold-adapted enzymes was studied to uncover the optimization strategy of intra-molecular interaction during the protein evolution.Increased conformational flexibility is the prevailing explanation for the high catalytic efficiency of cold-adapted enzymes at low temperatures.However,less is known about the structural determinants of flexibility.We reported two novel cold-adapted zinc metalloproteases in the thermolysin family,vibriolysin MCP-02 from a deep sea bacterium and vibriolysin E495 from an Arctic sea ice bacterium,and compared them with their mesophilic homolog,pseudolysin from a terrestrial bacterium.Their catalytic efficiencies,k_cat/K_m(10-40℃),followed the order pseudolysin＜MCP-02＜E495 with a ratio of～1:2:4 at 25℃.MCP-02 and E495 have the same optimal temperature(T_opt,57℃,5℃lower than pseudolysin) and apparent melting temperature(T_m=64℃,～10℃lower than pseudolysin).Structural analysis showed that the slightly lower stabilities resulted from a decrease in the number of salt bridges.Fluorescence quenching experiments and molecular dynamics simulations showed that the flexibilities of the proteins were pseudolysin＜MCP-02＜E495,suggesting that optimization of flexibility is a strategy for cold adaptation. Molecular dynamics results showed that the ordinal increase in flexibility from pseudolysin to MCP-02 and E495,especially the increase from MCP-02 to E495, mainly resulted from the decrease of hydrogen-bond stability in the dynamic structure, which was due to the increase in asparagine,serine,and threonine residues.Finally,a model for the cold adaptation of MCP-02 and E495 was proposed.This is the first report of the optimization of hydrogen-bonding dynamics as a strategy for cold adaptation and provides new insights into the structural basis underlying conformational flexibility.