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Rational Design Of Affinity Peptide Ligands For Antibody And Chromatographic Characterizations

Posted on:2012-11-09Degree:DoctorType:Dissertation
Country:ChinaCandidate:B HuangFull Text:PDF
GTID:1221330362453752Subject:Biochemical Engineering
Abstract/Summary:PDF Full Text Request
Rational design of affinity ligands is essential for the application of affinity chromatography. This thesis focuses on the development of rational design methods of affinity peptide ligands using immunoglobulin G (IgG) as the target protein.The thesis firstly established a high-throughput screening method combining molecular docking and IgG affinity chromatography. And a pentapeptide (EFYDD) was obtained using this method. However, the experiment results showed that the binding between the pentapeptide and IgG is mainly driven by electrostatic interaction, which is greatly different from the hydrophobic interaction between protein A (SpA) and IgG. It indicated that the high-throughput screening method has the shortcoming of blindness.In order to overcome the blindness defect of the high-throughput screening, the thesis brought up a rational design method of biomimetic affinity ligands for the first time. First, the all-atom molecular dynamics simulations were used to investigate the molecular mechanism of interaction between SpA and IgG. It is found that hydrophobic interaction was the main driving force for the binding, while electrostatic interaction dominantly regulated the specificity of SpA to different Igs. And the interactions between SpA and IgG1 were predominately regulated by the hot spots. On the basis of the hots spots and interactions of SpA, an affinity binding model of SpA was constructed, which may help design biomimetic affinity ligands for IgG.Secondly, the elution operation is an important step of the affinity chromatography process. Hence, the molecular mechanism of the salt and pH effects on the interaction between SpA and IgG was also investigated by the all-atom molecular dynamics simulations. The salt effects imposed on both hydrophobic and electrostatic interactions of the hot spots resulted in the compensation between helix I and helix II, as well as between the hydrophobic and electrostatic interactions. These two types of compensations made the binding free energy independent of salt. In the pH 3.0 condition, the dissociation of the SpA-IgG complex occurred due to the strong electrostatic repulsive interaction between SpA’s hot spots (H137, R146, and K154) and the residues of IgG. Hence, H137, R146, and K154 were considered as the molecular basis for the dissociation. These molecular mechanisms further improved the affinity binding model of SpA.Since the all-atom molecular dynamics simulation is difficult to investigate the dynamics process of interaction between SpA and IgG due to its enormous computation, the coarse-grained molecular dynamics simulation was applied to study the dissociation of the complex. The dissociation process at pH 3.0 condition consisted of four steps. During the process, the interactions of H137, E143, and R146 of SpA were first weakened, and helix II dissociated with IgG1 before helix I. This also indicated that helix II was the molecular basis of the dissociation. Hence, the coarse-grained molecular dynamics simulation was an effect method to research the protein-protein complex, and could be used for the rational design method.Finally, a SpA-mimic affinity peptide ligand was designed according to the above molecular mechanisms. A biomimetic library containing 28000 peptides was constructed on the basis of the affinity binding model of SpA. Then, two molecular docking and a coarse-grained molecular dynamics simulation were applied to screen the library, and some candidate peptides were obtained. Finally, affinity chromatography was carried out to verify the affinity of candidate peptides, and a high affinity heptapeptide (YFDWRWE) of IgG was selected.
Keywords/Search Tags:protein A, affinity chromatography, high-throughput screening, molecular simulation, biomimetic ligand, coarse-grained model
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