Novel peptide ligands for antibody purification provide superior clearance of host cell protein impurities.

The quest for ligands alternative to Protein A for the purification of monoclonal antibodies (mAbs) has been pursued for almost three decades. Yet, the IgG-binding peptides known to date still fall short of the host cell protein (HCP) logarithmic removal value (LRV) set by Protein A media (2.5-3.1). In this study, we present an integrated computational-experimental approach leading to the discovery of peptide ligands that provide HCP LRVs on par with Protein A. First, the screening of 60,000 peptide variants was performed using a high-throughput search algorithm to identify sequences that ensure IgG affinity binding. Select sequences WQRHGI, MWRGWQ, RHLGWF, and GWLHQR were then negatively screened in silico against a panel of model HCPs to ensure the selection of peptides with high binding selectivity. Candidate ligands WQRHGI and MWRGWQ were conjugated to chromatographic resins and characterized by isothermal binding and breakthrough assays to quantify static and dynamic binding capacity (Qmax and DBC10%), respectively. The resulting Qmax were 52.6 mg of IgG per mL of adsorbent for WQRHGI and 57.48 mg/mL for MWRGWQ, while the DBC10% (2 minutes residence time) were 30.1 mg/mL for WQRHGI and 36.4 mg/mL for MWRGWQ. Evaluation of the peptides by isothermal titration calorimetry (ITC) confirmed the binding energy predicted in silico, and an amino acid scanning study corroborated the affinity-like binding activity of the peptides. WQRHGI-WorkBeads resin was finally characterized by purification of a monoclonal antibody from a Chinese Hamster Ovary (CHO) cell culture harvest, affording a remarkable HCP LRV of 2.7, and consistent product yield and purity over 100 chromatographic cycles. These results demonstrate the potential of WQRHGI as an effective alternative to Protein A for antibody purification.

Chromatographic assay to probe the binding energy and mechanisms of homologous proteins to surface-bound ligands.

Probing the affinity of a ligand for homologous protein targets currently relies on laborious assays that need special equipment and high amounts of isolated, highly pure proteins. Herein we present the use of pISep, an integrated buffer system and modeling package, as an analytical method to rapidly and accurately probe the binding strength and mechanisms of homologous proteins to surface-bound ligands. To demonstrate our method, we utilized the four subclasses of human immunoglobulin G (IgG) as model homologous protein targets and the IgG-binding peptide HWRGWV as model ligand. Following IgG adsorption on a HWRGWV-Toyopearl adsorbent, the pISep buffer system was used to run uncoupled dual elution gradients of pH (from pH 8.5 to 2.5) and either isocratic or time dependent salt concentration. Both the sequence and partial overlap of elution times (IgG4 > IgG3 ≥ IgG1 > IgG2) was found to match closely the values of binding strength (KD) determined with both in silico docking simulations and isothermal titration calorimetry experiments. pISep gradients performed at different values of ionic strengths provided a means to compare the contribution of hydrophobic vs. electrostatic interactions to the IgG-peptide affinity. The shifts in retention times indicated that, among the various components of the binding energy, the hydrophobic interaction dominates in the binding of IgG2 and IgG4, whereas the binding of IgG1 and IgG3 features a balance of electrostatic and hydrophobic modes. These findings were also confirmed by the in silico analysis of the complexes formed by HWRGWV and the Fc fragment of the IgG subclasses. Collectively, these results indicate that the retention times on pISep elution gradients - in particular peak max, overlap, and shift under different conditions - directly correlate to the strength and nature of protein-ligand interactions. This work demonstrates the effectiveness of the pISep toolbox for probing the differential binding of homologous proteins to a reference ligand and informing the optimization of platform processes for the purification and fractionation of biotherapeutics.