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. 2014 Sep;1844(9):1530-40.
doi: 10.1016/j.bbapap.2014.04.020. Epub 2014 May 2.

Creating stable stem regions for loop elongation in Fcabs - insights from combining yeast surface display, in silico loop reconstruction and molecular dynamics simulations

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Creating stable stem regions for loop elongation in Fcabs - insights from combining yeast surface display, in silico loop reconstruction and molecular dynamics simulations

Christoph Hasenhindl et al. Biochim Biophys Acta. 2014 Sep.

Abstract

Fcabs (Fc antigen binding) are crystallizable fragments of IgG where the C-terminal structural loops of the CH3 domain are engineered for antigen binding. For the design of libraries it is beneficial to know positions that will permit loop elongation to increase the potential interaction surface with antigen. However, the insertion of additional loop residues might impair the immunoglobulin fold. In the present work we have probed whether stabilizing mutations flanking the randomized and elongated loop region improve the quality of Fcab libraries. In detail, 13 libraries were constructed having the C-terminal part of the EF loop randomized and carrying additional residues (1, 2, 3, 5 or 10, respectively) in the absence and presence of two flanking mutations. The latter have been demonstrated to increase the thermal stability of the CH3 domain of the respective solubly expressed proteins. Assessment of the stability of the libraries expressed on the surface of yeast cells by flow cytometry demonstrated that loop elongation was considerably better tolerated in the stabilized libraries. By using in silico loop reconstruction and mimicking randomization together with MD simulations the underlying molecular dynamics were investigated. In the presence of stabilizing stem residues the backbone flexibility of the engineered EF loop as well as the fluctuation between its accessible conformations were decreased. In addition the CD loop (but not the AB loop) and most of the framework regions were rigidified. The obtained data are discussed with respect to the design of Fcabs and available data on the relation between flexibility and affinity of CDR loops in Ig-like molecules.

Keywords: Fcab; Loop reconstruction; Molecular dynamics simulation; Protein engineering; Therapeutic antibody fragment; Yeast surface display.

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Figures

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Graphical abstract
Fig. 1
Fig. 1
Graphical representation of IgG1-CH3-Fc. Residues of interest are shown in blue, sites of randomization and insertion in red (A and B). Most prevalent structures of two systems according to cluster analyses are shown. (A) The variant stem(0), bearing the two stabilizing mutations Q418L and S424T. Residues 419–422 were replaced by alanines. (B) The variant stem(5), differing from stem(0) between residues 419 and 422, where 5 additional alanines were inserted. (C) The variant Q418L/S424T. Amino acids contributing to a hydrophobic cluster on the C-terminal part of the CH3 domain are highlighted in blue. The mutation Q418L is shown in yellow.
Fig. 2
Fig. 2
Differential scanning calorimetric analysis of wild-type IgG-Fc and the variants Q418L and S424T. Protein solutions were adjusted to a concentration of 5 μM in PBS buffer. Temperature range was from 20 to 110 °C. Fits of the obtained endotherms representing distinct unfolding events are depicted in red. The three thermal transitions of the wild-type protein are represented by dashed lines for comparison.
Fig. 3
Fig. 3
ΔT1/2 values for stabilized and non-stabilized libraries. Library designs and nomenclature are shown in Table 1. Constructed libraries were expressed on the surface of yeast and cell suspensions were incubated at increasing temperatures. After cooling cells were probed for binding to FcγRI by using flow cytometry. Obtained ΔT1/2 values describe the overall destabilization of a distinct library with respect to the yeast-displayed wild-type protein. Error bars are the standard errors of the mean of three replicate experiments.
Fig. 4
Fig. 4
Atom-positional root-mean-square fluctuation for Cα atoms. (A) ΔRMSF for each residue with respect to the wild-type CH3 domain is shown for Q418L (red), S424T (green) and Q418L/S424T. (B) Change in ΔRMSF for stem(0) with respect to stem-(0). (C) Change in RMSF for stem(5) with respect to stem-(5). For nomenclature see Table 1.
Fig. 5
Fig. 5
Cluster lifetime analysis. The 10 most populated clusters are shown for each simulated system in the following order: (A) wild-type CH3 domain, (B) Q418L, (C) S424T, (D) Q418L / S424T, (E) stem-(0), (F) stem(0), (G) stem-(5), (H) stem(5) (see Table 3). White bars represent how often a cluster was visited in the course of 2 separate 20 ns simulations. Gray bars represent the average lifetime of a cluster, i.e. the average number of snapshots in the simulation observed in the cluster before a cluster switch occurs.
Fig. 6
Fig. 6
Combined EF loop clustering of corresponding systems. Stacked bars represent combined clusters from two separate simulations of the wild-type CH3 domain (blue), the double mutant Q418L/S424T (red), the stabilized, ‘randomized’ variant stem(0) (green) and the non-stabilized, randomized variant stem-(0) (purple). RMSD (in nm) of cluster central member structures with respect to the central member structure of cluster 1 are shown on top of bars.
Fig. 7
Fig. 7
Graphical representation of the combined EF loop clustering of wild-type CH3 domain, Q418L/S424T, stem(0) and stem-(0). The EF loop of the central member structure of cluster 1 is shown in black. (A) Central member structure of cluster 1. (B) Superposition of central member structure EF loops for the structurally similar clusters 1, 2, 4, 5, 8, 9 and 10. (C) Superposition of central member structure EF loops for the structurally deviating clusters 3, 6 and 7.

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