Structural Characterization of a Protein A Mimetic Peptide Dendrimer Bound to Human IgG

Effects of molecule hydrophobicity and structural flexibility of appended bispecific antibody on Protein A chromatography

Appended bispecific antibody (aBsAb) with two single chain variable fragments (scFv) linked at the c-terminus of its heavy chains is one of the promising formats in bispecific therapeutics. The presence of hydrophobic and flexible scFv fragments render aBsAb molecules higher molecule hydrophobicity and structural flexibility compared to monoclonal antibody (mAb), thus making its purification more challenging. We set out to investigate how the unique molecular properties of aBsAb affect its performance on Protein A chromatography. We showed that aBsAb has a high propensity for chromatography-induced aggregation due to its high molecule hydrophobicity, and this couldn't be improved by the addition of common chaotropic salts. Moreover, the presence of chaotropic salts, such as arginine hydrochloride (Arg-HCl), retarded aBsAb elution during Protein A chromatography rather than facilitating which was widely observed in mAb Protein A elution. Nevertheless, we were able to overcome the aggregation issue by optimizing elution condition and improved aBsAb purity from 29 % to 93 % in Protein A eluate with a high molecular weight (HMW) species of less than 5 %. We also showed that the high molecular flexibility of aBsAb leads to different hydrodynamic sizes of the aBsAb molecule post Protein A elution, neutralization, and re-acidification, which are pH dependent. This is different from mAbs where their sizes do not change post neutralization even with re-exposure to acid. The above unique observations of aBsAb in Protein A chromatography were clearly explained from the perspectives of its high molecular hydrophobicity and structural flexibility.

Peptide Dendrimer-Based Antibacterial Agents: Synthesis and Applications

Pathogenic bacteria cause the deaths of millions of people every year. With the development of antibiotics, hundreds and thousands of people's lives have been saved. Nevertheless, bacteria can develop resistance to antibiotics, rendering them insensitive to antibiotics over time. Peptides containing specific amino acids can be used as antibacterial agents; however, they can be easily degraded by proteases in vivo. To address these issues, branched peptide dendrimers are now being considered as good antibacterial agents due to their high efficacy, resistance to protease degradation, and low cytotoxicity. The ease with which peptide dendrimers can be synthesized and modified makes them accessible for use in various biological and nonbiological fields. That is, peptide dendrimers hold a promising future as antibacterial agents with prolonged efficacy without bacterial resistance development. Their in vivo stability and multivalence allow them to effectively target multi-drug-resistant strains and prevent biofilm formation. Thus, it is interesting to have an overview of the development and applications of peptide dendrimers in antibacterial research, including the possibility of employing machine learning approaches for the design of AMPs and dendrimers. This review summarizes the synthesis and applications of peptide dendrimers as antibacterial agents. The challenges and perspectives of using peptide dendrimers as the antibacterial agents are also discussed.

Rational design of humanized antibody inhibitors for cathepsin S

Cathepsin S (CTSS) is involved in pathogenesis of many human diseases. Inhibitors blocking its protease activity hold therapeutic potential. In comparison to small-molecule inhibitors, monoclonal antibodies capable of inhibiting CTSS enzymatic activity may possess advantageous pharmacological properties. Here we designed and produced inhibitory antibodies targeting human CTSS by genetically fusing the propeptide of procathepsin S (proCTSS) with antibodies in clinic. The resulting antibody fusions in full-length or fragment antigen-binding format could be stably expressed and potently inhibit CTSS proteolytic activity in high specificity. These fusion antibodies not only demonstrate a new approach for facile synthesis of antibody inhibitors against CTSS, but also represent novel anti-CTSS therapeutic candidates.

Machine Learning Model for Biomimetic Chromatography Peptide Ligands

Purification is an essential part of antibody production, which are important therapeutic biomolecules. Common methods of antibody purification rely on affinity chromatography (AC), wherein whole proteins are oftentimes used as ligands to catch the antibodies to be purified. While AC has been successful in purifying antibodies, it is associated with multiple challenges such as high cost and low stability, among others. A promising alternative is using short peptide sequences in place of whole proteins as the stationary phase for the chromatographic separation of the antibodies. In an effort to accelerate the discovery and development of short peptides for biomimetic chromatography, this study reports the creation of a machine learning classification which was trained and tested on 480 tetrapeptides. The optimized logistic regression model uses Cruciani properties as the input variables and can categorize peptides into one of two classes based on their binding affinity with immunoglobulin G (IgG). The externally validated model demonstrates satisfactory predictive performance and excellent discrimination as demonstrated by performance metrics such as AUC = 0.874, Balanced Accuracy = 0.874, F1 = 0.871, Precision = 0.884, and Recall = 0.859. Apart from this, the classifier has also provided valuable insights into important variables that influence the classification, such as electrostatic and hydrophobic interactions. Overall, the classifier can be regarded as a welcome development for biomimetic chromatography and is the first study that aims to integrate machine learning in the biomimetic chromatography peptide development process.

A Strategy for Selective Deletion of Autoimmunity-Related T Cells by pMHC-Targeted Delivery

Autoimmune diseases such as rheumatoid arthritis are caused by immune system recognition of self-proteins and subsequent production of effector T cells that recognize and attack healthy tissue. Therapies for these diseases typically utilize broad immune suppression, which can be effective, but which also come with an elevated risk of susceptibility to infection and cancer. T cell recognition of antigens is driven by binding of T cell receptors to peptides displayed on major histocompatibility complex proteins (MHCs) on the cell surface of antigen-presenting cells. Technology for recombinant production of the extracellular domains of MHC proteins and loading with peptides to produce pMHCs has provided reagents for detection of T cell populations, and with the potential for therapeutic intervention. However, production of pMHCs in large quantities remains a challenge and a translational path needs to be established. Here, we demonstrate a fusion protein strategy enabling large-scale production of pMHCs. A peptide corresponding to amino acids 259-273 of collagen II was fused to the N-terminus of the MHC_II beta chain, and the alpha and beta chains were each fused to human IgG4 Fc domains and co-expressed. A tag was incorporated to enable site-specific conjugation. The cytotoxic drug payload, MMAF, was conjugated to the pMHC and potent, peptide-specific killing of T cells that recognize the collagen pMHC was demonstrated with tetramerized pMHC-MMAF conjugates. Finally, these pMHCs were incorporated into MMAF-loaded 3DNA nanomaterials in order to provide a biocompatible platform. Loading and pMHC density were optimized, and peptide-specific T cell killing was demonstrated. These experiments highlight the potential of a pMHC fusion protein-targeted, drug-loaded nanomaterial approach for selective delivery of therapeutics to disease-relevant T cells and new treatment options for autoimmune disease.

Recent Applications of Retro-Inverso Peptides

Natural and de novo designed peptides are gaining an ever-growing interest as drugs against several diseases. Their use is however limited by the intrinsic low bioavailability and poor stability. To overcome these issues retro-inverso analogues have been investigated for decades as more stable surrogates of peptides composed of natural amino acids. Retro-inverso peptides possess reversed sequences and chirality compared to the parent molecules maintaining at the same time an identical array of side chains and in some cases similar structure. The inverted chirality renders them less prone to degradation by endogenous proteases conferring enhanced half-lives and an increased potential as new drugs. However, given their general incapability to adopt the 3D structure of the parent peptides their application should be careful evaluated and investigated case by case. Here, we review the application of retro-inverso peptides in anticancer therapies, in immunology, in neurodegenerative diseases, and as antimicrobials, analyzing pros and cons of this interesting subclass of molecules.

An efficient chemical screening method for structure-based inhibitors to nucleic acid enzymes targeting the DNA repair-replication interface and SARS CoV-2

We present a Chemistry and Structure Screen Integrated Efficiently (CASSIE) approach (named for Greek prophet Cassandra) to design inhibitors for cancer biology and pathogenesis. CASSIE provides an effective path to target master keys to control the repair-replication interface for cancer cells and SARS CoV-2 pathogenesis as exemplified here by specific targeting of Poly(ADP-ribose) glycohydrolase (PARG) and ADP-ribose glycohydrolase ARH3 macrodomains plus SARS CoV-2 nonstructural protein 3 (Nsp3) Macrodomain 1 (Mac1) and Nsp15 nuclease. As opposed to the classical massive effort employing libraries with large numbers of compounds against single proteins, we make inhibitor design for multiple targets efficient. Our compact, chemically diverse, 5000 compound Goldilocks (GL) library has an intermediate number of compounds sized between fragments and drugs with predicted favorable ADME (absorption, distribution, metabolism, and excretion) and toxicological profiles. Amalgamating our core GL library with an approved drug (AD) library, we employ a combined GLAD library virtual screen, enabling an effective and efficient design cycle of ranked computer docking, top hit biophysical and cell validations, and defined bound structures using human proteins or their avatars. As new drug design is increasingly pathway directed as well as molecular and mechanism based, our CASSIE approach facilitates testing multiple related targets by efficiently turning a set of interacting drug discovery problems into a tractable medicinal chemistry engineering problem of optimizing affinity and ADME properties based upon early co-crystal structures. Optimization efforts are made efficient by a computationally-focused iterative chemistry and structure screen. Thus, we herein describe and apply CASSIE to define prototypic, specific inhibitors for PARG vs distinct inhibitors for the related macrodomains of ARH3 and SARS CoV-2 Nsp3 plus the SARS CoV-2 Nsp15 RNA nuclease.

Monitoring size and oligomeric-state distribution of therapeutic mAbs by NMR and DLS: Trastuzumab as a case study

Monoclonal antibodies (mAbs) are the modalities of choice for immunotherapy. This class of products are known to exhibit considerable heterogeneity with respect to size, aggregation states, and charge. This makes it challenging for biopharmaceutical manufacturers, in particular biosimilar producers, to maintain consistency in product quality. In order to fingerprint these biotherapeutic products, multiple, high-resolution analytical tools are used to characterize the numerous critical quality attributes. Recently, there has been growing interest in enhancing adaptability of 1D and 2D NMR platforms for characterization of higher order structure with emphasis on 1D ¹H, 2D ¹H-¹⁵N and ¹H-¹³C NMR experiments at natural abundance. In this communication, we report the applicability of 2D-DOSY NMR for quantification of colloidal diffusivities, namely diffusion coefficient (and associated hydrodynamic radius) for monomeric IgG1 mAb formulations at physiological conditions. Similarity assessment has been performed for trastuzumab originator (multiple batches) and marketed biosimilars to showcase the applicability of this approach. While dynamic light scattering measurements are known to be sensitive to presence of larger particles with a concentration dependence for estimation of colloidal diffusivities, size estimated by NMR experiments was found to be more in agreement with the computational hydrodynamic size estimations derived from the published crystal structures of intact mAb at formulation concentration.

Identification of preferred multimodal ligand-binding regions on IgG1 FC using nuclear magnetic resonance and molecular dynamics simulations

In this study, the binding of multimodal chromatographic ligands to the IgG1 F_C domain were studied using nuclear magnetic resonance and molecular dynamics simulations. Nuclear magnetic resonance experiments carried out with chromatographic ligands and a perdeuterated ¹⁵ N-labeled F_C domain indicated that while single-mode ion exchange ligands interacted very weakly throughout the F_C surface, multimodal ligands containing negatively charged and aromatic moieties interacted with specific clusters of residues with relatively high affinity, forming distinct binding regions on the F_C . The multimodal ligand-binding sites on the F_C were concentrated in the hinge region and near the interface of the C_H 2 and C_H 3 domains. Furthermore, the multimodal binding sites were primarily composed of positively charged, polar, and aliphatic residues in these regions, with histidine residues exhibiting some of the strongest binding affinities with the multimodal ligand. Interestingly, comparison of protein surface property data with ligand interaction sites indicated that the patch analysis on F_C corroborated molecular-level binding information obtained from the nuclear magnetic resonance experiments. Finally, molecular dynamics simulation results were shown to be qualitatively consistent with the nuclear magnetic resonance results and to provide further insights into the binding mechanisms. An important contribution to multimodal ligand-F_C binding in these preferred regions was shown to be electrostatic interactions and π-π stacking of surface-exposed histidines with the ligands. This combined biophysical and simulation approach has provided a deeper molecular-level understanding of multimodal ligand-F_C interactions and sets the stage for future analyses of even more complex biotherapeutics.

Cobalt-Directed Assembly of Antibodies onto Metal-Phenolic Networks for Enhanced Particle Targeting

The orientation-specific immobilization of antibodies onto nanoparticles, to preserve antibody-antigen recognition, is a key challenge in developing targeted nanomedicines. Herein, we report the targeting ability of metal-phenolic network (MPN)-coated gold nanoparticles with surface-physisorbed antibodies against respective antigens. The MPN coatings were self-assembled from metal ions (Fe^III, Co^II, Cu^II, Ni^II, or Zn^II) cross-linked with tannic acid. Upon physisorption of antibodies, all particle systems exhibited enhanced association with target antigens, with Co^II systems demonstrating more than 2-fold greater association. These systems contained more metal atoms distributed in a way to specifically interact with antibodies, which were investigated by molecular dynamics simulations. A model antibody fragment crystallizable (Fc) region in solution with Co^II-tannic acid complexes revealed that the solvent-exposed Co^II can directly coordinate to the histidine-rich portion of the Fc region. This one-pot interaction suggests anchoring of the antibody Fc region to the MPN on nanoparticles, allowing for enhanced targeting.

Enhanced preclinical antitumor activity of M7824, a bifunctional fusion protein simultaneously targeting PD-L1 and TGF-β

Antibodies targeting immune checkpoints are emerging as potent and viable cancer therapies, but not all patients respond to these as single agents. Concurrently targeting additional immunosuppressive pathways is a promising approach to enhance immune checkpoint blockade, and bifunctional molecules designed to target two pathways simultaneously may provide a strategic advantage over the combination of two single agents. M7824 (MSB0011359C) is a bifunctional fusion protein composed of a monoclonal antibody against programmed death ligand 1 (PD-L1) fused to the extracellular domain of human transforming growth factor-β (TGF-β) receptor II, which functions as a "trap" for all three TGF-β isoforms. We demonstrate that M7824 efficiently, specifically, and simultaneously binds PD-L1 and TGF-β. In syngeneic mouse models, M7824 suppressed tumor growth and metastasis more effectively than treatment with either an anti-PD-L1 antibody or TGF-β trap alone; furthermore, M7824 extended survival and conferred long-term protective antitumor immunity. Mechanistically, the dual anti-immunosuppressive function of M7824 resulted in activation of both the innate and adaptive immune systems, which contributed to M7824's antitumor activity. Finally, M7824 was an effective combination partner for radiotherapy or chemotherapy in mouse models. Collectively, our preclinical data demonstrate that simultaneous blockade of the PD-L1 and TGF-β pathways by M7824 elicits potent and superior antitumor activity relative to monotherapies.

Protein Interaction with Charged Macromolecules: From Model Polymers to Unfolded Proteins and Post-Translational Modifications

Interaction of proteins with charged macromolecules is involved in many processes in cells. Firstly, there are many naturally occurred charged polymers such as DNA and RNA, polyphosphates, sulfated glycosaminoglycans, etc., as well as pronouncedly charged proteins such as histones or actin. Electrostatic interactions are also important for "generic" proteins, which are not generally considered as polyanions or polycations. Finally, protein behavior can be altered due to post-translational modifications such as phosphorylation, sulfation, and glycation, which change a local charge of the protein region. Herein we review molecular modeling for the investigation of such interactions, from model polyanions and polycations to unfolded proteins. We will show that electrostatic interactions are ubiquitous, and molecular dynamics simulations provide an outstanding opportunity to look inside binding and reveal the contribution of electrostatic interactions. Since a molecular dynamics simulation is only a model, we will comprehensively consider its relationship with the experimental data.

Targeting Allostery with Avatars to Design Inhibitors Assessed by Cell Activity: Dissecting MRE11 Endo- and Exonuclease Activities

For inhibitor design, as in most research, the best system is question dependent. We suggest structurally defined allostery to design specific inhibitors that target regions beyond active sites. We choose systems allowing efficient quality structures with conformational changes as optimal for structure-based design to optimize inhibitors. We maintain that evolutionarily related targets logically provide molecular avatars, where this Sanskrit term for descent includes ideas of functional relationships and of being a physical embodiment of the target's essential features without requiring high sequence identity. Appropriate biochemical and cell assays provide quantitative measurements, and for biomedical impacts, any inhibitor's activity should be validated in human cells. Specificity is effectively shown empirically by testing if mutations blocking target activity remove cellular inhibitor impact. We propose this approach to be superior to experiments testing for lack of cross-reactivity among possible related enzymes, which is a challenging negative experiment. As an exemplary avatar system for protein and DNA allosteric conformational controls, we focus here on developing separation-of-function inhibitors for meiotic recombination 11 nuclease activities. This was achieved not by targeting the active site but rather by geometrically impacting loop motifs analogously to ribosome antibiotics. These loops are neighboring the dimer interface and active site act in sculpting dsDNA and ssDNA into catalytically competent complexes. One of our design constraints is to preserve DNA substrate binding to geometrically block competing enzymes and pathways from the damaged site. We validate our allosteric approach to controlling outcomes in human cells by reversing the radiation sensitivity and genomic instability in BRCA mutant cells.

Conformational and Colloidal Stabilities of Isolated Constant Domains of Human Immunoglobulin G and Their Impact on Antibody Aggregation under Acidic Conditions

Antibody therapeutics are now in widespread use and provide a new approach for treating serious diseases such as rheumatic diseases and cancer. Monoclonal antibodies used as therapeutic agents must be of high quality, and their safety must be guaranteed. Aggregated antibody is a degradation product that may be generated during the manufacturing process. To maintain the high quality and safety of antibody therapeutics, it is necessary to understand the mechanism of aggregation and to develop technologies to strictly control aggregate formation. Here, we extensively investigated the conformational and colloidal characteristics of isolated antibody constant domains, and provided insights into the molecular mechanism of antibody aggregation. Isolated domains (CH2, CH3, CL, and CH1-CL dimer) of human immunoglobulin G were synthesized, solubilized using 49 sets of solution conditions (pH 2-8 and 0-300 mM NaCl), and characterized using circular dichroism, intrinsic tryptophan fluorescence, and dynamic light scattering. Salt-induced conformational changes and oligomer formation were kinetically analyzed by NaCl-jump measurements (from 0 to 300 mM at pH 3). Phase diagrams revealed that the domains have different conformational and colloidal stabilities. The unfolded fractions of CH3 and CH2 at pH 3 were larger than that of CL and CH1-CL dimer. The secondary and tertiary structures and particle sizes of CH3 and CH2 showed that, in non-native states, these domains were sensitive to salt concentration. Kinetic analyses suggest that oligomer formation by CH3 and CH2 proceeds through partially refolded conformations. The colloidal stability of CH3 in non-native states is the lowest of the four domains under the conditions tested. We propose that the impact of IgG constant domains on aggregation follows the order CH3 > CH2 > CH1-CL dimer > CL; furthermore, we suggest that CH3 plays the most critical role in driving intact antibody aggregation under acidic conditions.

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.

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

Staphylococcus aureus protein A (SpA) is the most popular affinity ligand for immunoglobulin G1 (IgG1). However, the molecular basis for the dissociation dynamics of SpA-IgG1 complex is unclear. Herein, coarse-grained (CG) molecular dynamics (MD) simulations with the Martini force field were used to study the dissociation dynamics of the complex. The CG-MD simulations were first verified by the agreement in the structural and interactional properties of SpA and human IgG1 (hIgG1) in the association process between the CG-MD and all-atom MD at different NaCl concentrations. Then, the CG-MD simulation studies focused on the molecular insight into the dissociation dynamics of SpA-hIgG1 complex at pH 3.0. It is found that there are four steps in the dissociation process of the complex. First, there is a slight conformational adjustment of helix II in SpA. This is followed by the phenomena that the electrostatic interactions provided by the three hot spots (Glu143, Arg146 and Lys154) of helix II of SpA break up, leading to the dissociation of helix II from the binding site of hIgG1. Subsequently, breakup of the hydrophobic interactions between helix I (Phe132, Tyr133 and His137) in SpA and hIgG1 occurs, resulting in the disengagement of helix I from its binding site of hIgG1. Finally, the non-specific interactions between SpA and hIgG1 decrease slowly till disappearance, leading to the complete dissociation of the SpA-hIgG1 complex. This work has revealed that CG-MD coupled with the Martini force field is an effective method for studying the dissociation dynamics of protein-protein complex.

Function and 3D structure of the N-glycans on glycoproteins

Glycosylation is one of the most common post-translational modifications in eukaryotic cells and plays important roles in many biological processes, such as the immune response and protein quality control systems. It has been notoriously difficult to study glycoproteins by X-ray crystallography since the glycan moieties usually have a heterogeneous chemical structure and conformation, and are often mobile. Nonetheless, recent technical advances in glycoprotein crystallography have accelerated the accumulation of 3D structural information. Statistical analysis of “snapshots” of glycoproteins can provide clues to understanding their structural and dynamic aspects. In this review, we provide an overview of crystallographic analyses of glycoproteins, in which electron density of the glycan moiety is clearly observed. These well-defined N-glycan structures are in most cases attributed to carbohydrate-protein and/or carbohydrate-carbohydrate interactions and may function as “molecular glue” to help stabilize inter- and intra-molecular interactions. However, the more mobile N-glycans on cell surface receptors, the electron density of which is usually missing on X-ray crystallography, seem to guide the partner ligand to its binding site and prevent irregular protein aggregation by covering oligomerization sites away from the ligand-binding site.

A conserved host and pathogen recognition site on immunoglobulins: structural and functional aspects

A common site in the constant region (Fc) of immunoglobulins is recognized by host receptors and is a frequent target of proteins expressed by pathogens. This site is located at the junction of two constant domains in the antibody heavy chains and produces a large shallow cavity formed by loops of the CH2 and CH3 domains in IgG and IgA (CH3 and CH4 domains in IgM). Crystal structures have been determined for complexes of IgG-Fc and IgA-Fc with a structurally diverse set of host, pathogen and in vitro selected ligands. While pathogen proteins may directly block interactions with the immunoglobulins thereby evading host immunity, it is likely that the same pathogen molecules also interact with other host factors to carry out their primary biological function. Herein we review the structural and functional aspects of host and pathogen molecular recognition of the common site on the Fc of immunoglobulins. We also propose that some pathogen proteins may promote virulence by affecting the bridging between innate and adaptive immunity.

Molecular mechanism of the effects of salt and pH on the affinity between protein A and human immunoglobulin G1 revealed by molecular simulations

Protein A from the bacterium Staphylococcus aureus (SpA) has been widely used as an affinity ligand for purification of immunoglobulin G (IgG). The affinity between SpA and IgG is affected differently by salt and pH, but their molecular mechanisms still remain unclear. In this work, molecular dynamics simulations and molecular mechanics Poisson-Boltzmann surface area analysis were performed to investigate the salt (NaCl) and pH effects on the affinity between SpA and human IgG1 (hIgG1). It is found that salt and pH affect the interactions of the hot spots of SpA by different mechanisms. In the salt solution, the compensations between helices I and II of SpA as well as between the nonpolar and electrostatic energies make the binding free energy independent of salt concentration. At pH 3.0, the unfavorable electrostatic interactions increase greatly and become the driving force for dissociation of the SpA-hIgG1 complex. They mainly come from the strong electrostatic repulsions between positively charged residues (H137, R146, and K154) of SpA and the positively charged residues of hIgG1. It is considered to be the molecular basis for hIgG1 elution from SpA-based affinity adsorbents at pH 3.0. The dissociation mechanism is then used to refine the binding model of SpA to hIgG1. The model is expected to help design high-affinity peptide ligands of IgG.