Molecular basis for the dissociation dynamics of protein A-immunoglobulin G1 complex

A Systematic Test of Receptor Binding Kinetics for Ligands in Tumor Necrosis Factor Superfamily by Computational Simulations

Ligands in the tumor necrosis factor (TNF) superfamily are one major class of cytokines that bind to their corresponding receptors in the tumor necrosis factor receptor (TNFR) superfamily and initiate multiple intracellular signaling pathways during inflammation, tissue homeostasis, and cell differentiation. Mutations in the genes that encode TNF ligands or TNFR receptors result in a large variety of diseases. The development of therapeutic treatment for these diseases can be greatly benefitted from the knowledge on binding properties of these ligand–receptor interactions. In order to complement the limitations in the current experimental methods that measure the binding constants of TNF/TNFR interactions, we developed a new simulation strategy to computationally estimate the association and dissociation between a ligand and its receptor. We systematically tested this strategy to a comprehensive dataset that contained structures of diverse complexes between TNF ligands and their corresponding receptors in the TNFR superfamily. We demonstrated that the binding stabilities inferred from our simulation results were compatible with existing experimental data. We further compared the binding kinetics of different TNF/TNFR systems, and explored their potential functional implication. We suggest that the transient binding between ligands and cell surface receptors leads into a dynamic nature of cross-membrane signal transduction, whereas the slow but strong binding of these ligands to the soluble decoy receptors is naturally designed to fulfill their functions as inhibitors of signal activation. Therefore, our computational approach serves as a useful addition to current experimental techniques for the quantitatively comparison of interactions across different members in the TNF and TNFR superfamily. It also provides a mechanistic understanding to the functions of TNF-associated cell signaling pathways.

Computational studies of protein-protein dissociation by statistical potential and coarse-grained simulations: a case study on interactions between colicin E9 endonuclease and immunity proteins

Proteins carry out their diverse functions in cells by forming interactions with each other. The dynamics of these interactions are quantified by the measurement of association and dissociation rate constants. Relative to the efforts made to model the association of biomolecules, little has been studied to understand the principles of protein complex dissociation. Using the interaction between colicin E9 endonucleases and immunity proteins as a test system, here we develop a coarse-grained simulation method to explore the dissociation mechanisms of protein complexes. The interactions between proteins in the complex are described by the knowledge-based potential that was constructed by the statistics from available protein complexes in the structural database. Our study provides the supportive evidences to the dual recognition mechanism for the specificity of binding between E9 DNase and immunity proteins, in which the conserved residues of helix III of Im2 and Im9 proteins act as the anchor for binding, while the sequence variations in helix II make positive or negative contributions to specificity. Beyond that, we further suggest that this binding specificity is rooted in the process of complex dissociation instead of association. While we increased the flexibility of protein complexes, we further found that they are less prone to dissociation, suggesting that conformational fluctuations of protein complexes play important functional roles in regulating their binding and dissociation. Our studies therefore bring new insights to the molecule mechanisms of protein-protein interactions, while the method can serve as a new addition to a suite of existing computational tools for the simulations of protein complexes.

Exploring the unbinding of Leishmania (L.) amazonensis CPB derived-epitopes from H2 MHC class I proteins

New strategies to control Leishmania disease demand an extensive knowledge about several aspects of infection including the understanding of its molecular events. In murine models, cysteine proteinase B from Leishmania amazonensis promotes regulation of immune response, and fragments from its C-terminus extension (cyspep) can play a decisive role in the host-parasite interaction. The interaction between cyspep-derived peptides and major histocompatibility complex (MHC) proteins is a crucial factor in Leishmania infections. Seven cyspep-derived peptides, previously identified as capable of interacting with H-2 (murine) MHC class I proteins, were studied in this work. We established a protocol to simulate the unbinding of these peptides from the cleft of H-2 receptors. From the simulations, we estimated the corresponding free energy of dissociation (ΔGd ) and described the molecular events that occur during the exit of peptides from the cleft. To test the reliability of this method, we first applied it to a calibration set of four crystallographic MHC/peptide complexes. Next, we explored the unbinding of the seven complexes mentioned above. Results were consistent with ΔGd values obtained from surface plasmon resonance (SPR) experiments. We also identified some of the primary interactions between peptides and H-2 receptors, and we detected three regions of influence for the interaction. This pattern was systematically observed for the peptides and helped determine a minimum distance for the real interaction between peptides and H-2 proteins occurring at ∼ 25 Å.

Molecular modeling of the affinity chromatography of monoclonal antibodies

Molecular modeling is a methodology that offers the possibility of studying complex systems such as protein-ligand complexes from an atomistic point of view, making available information that can be difficultly obtained from experimental studies. Here, a protocol for the construction of molecular models of the interaction between antibodies and ligands that can be used for an affinity chromatography process is presented. The outlined methodology focuses mostly on the description of a procedure that may be adopted to determine the structure and free energy of interaction between the antibody and the affinity ligand. A procedure to extend the proposed methodology to include the effect of the environment (buffer solution, spacer, support matrix) is also briefly outlined.