Research On Post-Translational Modification Of Nitration/S-Nitrosylation Based On Structural Bioinformatics

Post-translational modification is a significant process in the protein biosynthesis, including modification, folding, cutting and other biological processes. Up to now, over 200 types of post-translational modifications were found. The redox post-translational modification included nitration and S-nitrosylation. These two modifications were associated with modulating phosphorylation cascades, inducing immunological response, protein function regulation, human health and disease and cellular signaling. Based on the protein structural information from PDB database, the analysis was based on structural bioinformatics, and were grouped into two main parts: 1) Anslysis of nitration/S-nitrosylation based on structural bioinformatics and molecular dynamics simuations. 2) New algorithms based on protein amino-acid networks.In part one, the tyrosine nitration and cysteine S-nitrosylation were analyzed. For nitration, we analyzed the local protein structures and amino acid topological networks of the nitrated and non-nitrated tyrosine sites in nitrated proteins, including neighboring atomic distribution, amino acid pair(AAP) and amino acid triangle(AAT). It has been found that aromatic and aliphatic residues, particularly with large volume, aromatic, aliphatic, or acidic side chain, are disfavored for the nitration. After integrating these structural features and topological network features with traditional sequence features, the predictive model achieve the sensitivity of 63.30% and the specificity of 92.24%, resulting in a much better accuracy compared to the previous models with only protein sequence information. For S-nitrosylation, we integrated all structural information of S-nitrosylated proteins in the PDB database and carried out a case study with the famous one, hemoglobin, the R and T-state of which share identical sequence but different capacity for S-nitrosylation. Compared to the non-modified cysteine residues in those proteins, the S-nitrosylated cysteines presented a lower p Ka(11.54 ± 2.54), a higher population of neighboring basic residues(in particular His), a lower abundancy of aromatic/aliphatic residues(i.e. Phe, Leu). It seems that deprotonation of cysteine residues and basic environment could promote the modification. As an example, the basic residues, including Hisβ92, Hisβ143 and Lys143, came closer to Cysβ93 in the case of deprotonated R-state hemoglobin. Furthermore, front regions of the S-nitrosylated cysteine sites were of a lower population of big-volume residues such as Phe, Tyr and Leu. In the MD simulation, it was observed that Pheβ103 and Tyrβ145 moved away when Cysβ93 is deprotonated in R-state. Statistically, the S-nitrosylated cysteines located at a higher flexible sequence, and correspondingly, Cysβ93 possessed a higher RMSF in R-state than that in T-state. With considerations of the four characteristics, a 3-dimensional model was constructed and explained 61.92% of the S-nitrosylated cysteine sites and 58.13% of the non-S-nitrosylated cysteine sites in the S-nitrosylated proteins.In part two, the protein amino-acid topological network(residue topological network) were used to analyze the structural similarity of protein functional sites. First, the methods for building a protein amino-acid topological network were analyzed. Based on the old methods, a new method were propose, which was more robustness. Futhremore, two new algorithms were built and used for the functional sites detections.