시스템 생물 정보학을 이용한 단백질 구조, 동역학 및 기능의 통합적 이해와 분석
- 시스템 생물 정보학을 이용한 단백질 구조, 동역학 및 기능의 통합적 이해와 분석
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- An improved understanding of protein structure and dynamics has broad implications for elucidating the mechanisms of various biological processes and designing protein engineering experiments. Protein conformational changes play key roles in regulating various protein activities, such as catalysis, gene regulation, and signal transduction, in response to the binding of the protein to lipids, ions, ligands, or other proteins. Although the mechanisms underlying protein conformational changes have been a subject of intense investigations, however, the evolutionary pressure to retain structural transitions has yet to be explored. If amino acid sequences are determinants for protein structures, protein conformational changes should also be encoded in the protein sequences.
Proteins have achieved proper functionality and stability during evolution. For instance, functional sites such as substrate/ligand binding regions, protein-protein interfaces, and active sites of enzymes tend to be conserved to maintain functional specificity. Meanwhile, residues within close proximity in a protein structure come into contact upon folding which involved in allosteric pathways of proteins tend to share similar evolutionary pressures to maintain foldability and stability of protein structure, and eventually gain a coevolutionary relationship. Therefore, sequence-based evolutionary analysis has gained its popularity to study protein structure and function. In this study, I investigated how protein dynamics is encoded in protein sequence through systematic bioinformatics approaches.
First, I characterized the functionally important cooperative residues that mediate protein conformational changes and long-range communication from the substrate binding site to the translocation pathway of membrane protein transporter. To do this, I derived a new evolutionary feature, the co-evolutionary coupling number (CN) to measure the connectivity of co-evolving residue pairs and integrated CN with the sequence conservation score. I tested this method on three Major Facilitator Superfamily (MFS) transporters, LacY, GlpT, and EmrD. I found that the conserved cores of evolutionary coupled residues are involved in flexible translocation pathway of MFS transporters. Furthermore, a subset of the residues forms an interaction network connecting functional sites in the protein structure. This integrative approach could be an effective way to identify key residues important for the long-range communication of membrane protein transporters.
Second, I investigated the relationship between sequence evolution and protein conformational changes. From the analysis of 81 proteins that undergo substantial conformational changes, I discovered that structural transitions are encoded in amino acid sequences as coevolving residue pairs. I found that highly-coevolving residues are clustered in the flexible regions of proteins and facilitate structural transitions by forming and disrupting their interactions cooperatively. Furthermore, I tested the sequence-based evolutionary approach on the two proteins for which conformational changes were revealed by NMR spectroscopy, and confirmed that my method is effective for characterizing the residues important for structural transitions. Results provide insight into the evolution of protein conformational changes and help to identify residues important for structural transitions.
Finally, I proposed the structural and evolutionary properties of rewiring of residue-interaction networks. By decomposing protein structures into residue-interaction networks, I found that interaction rewiring facilitated the efficient signal transduction by providing shortcut between distant sites in protein structure. Specifically, residues with many dynamic interactions were responsible for switching protein activity. Furthermore, those residues were evolutionarily coupled with many other sites. These results demonstrated that rewiring of residue-interaction was crucial for propagating allosteric information to many other sites, thus they have been under evolutionary pressure to have many co-evolving residue pairs.
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