Relationship between potential aggregation-prone regions and HLA-DR-binding T-cell immune epitopes: implications for rational design of novel and follow-on therapeutic antibodies

Restoring immune balance with Tregitopes: A new approach to treating immunological disorders

The induction of immunological tolerance is a promising strategy for managing autoimmune diseases, allergies, and transplant rejection. Tregitopes, a class of peptides, have emerged as potential agents for this purpose. They activate regulatory T cells, which are pivotal in reducing inflammation and promoting tolerance, by binding to MHC II molecules and facilitating their processing and presentation to Treg cells, thereby encouraging their proliferation. Moreover, Tregitopes influence the phenotype of antigen-presenting cells by attenuating the expression of CD80, CD86, and MHC class II while enhancing ILT3, resulting in the inhibition of NF-kappa B signaling pathways. Various techniques, including in vitro and in silico methods, are applied to identify Tregitope candidates. Currently, Tregitopes play a vital role in balancing immune activation and tolerance in clinical applications such as Pompe disease, diabetes-related antigens, and the prevention of spontaneous abortions in autoimmune diseases. Similarly, Tregitopes can induce antigen-specific regulatory T cells. Their anti-inflammatory effects are significant in conditions such as autoimmune encephalomyelitis, inflammatory bowel disease, and Guillain-Barré syndrome. Additionally, Tregitopes have been leveraged to enhance vaccine design and efficacy. Recent advancements in understanding the potential benefits and drawbacks of IVIG and the discovery of the function and mechanism of Tregitopes have introduced Tregitopes as a popular option for immune system modulation. It is expected that they will bring about a significant revolution in the management and treatment of autoimmune and immunological diseases. This article is a comprehensive review of Tregitopes, concluding with the potential of these epitopes as a therapeutic avenue for immunological disorders.

Intrinsic physicochemical profile of marketed antibody-based biotherapeutics

Successful biologic drug discovery and development involves finding functional as well as developable candidates. Once a candidate has been demonstrated to be functional, the next step is to determine whether it can be translated into a drug product. This requires that the candidate can withstand stresses encountered during manufacturing, shipping, and storage. Additionally, it must be safe, efficacious, and possess good pharmacology. In silico analyses of the variable regions of 77 marketed antibody-based biotherapeutics have revealed five nonredundant physicochemical descriptors. Distributions of these descriptors, observed for marketed biotherapeutics, can help prioritize a drug candidate for experimental testing at early discovery stages, guide engineering efforts to further optimize it, and help increase the productivity of biologic drug discovery and development.

Feeding biopharma pipelines with biotherapeutic candidates that possess desirable developability profiles can help improve the productivity of biologic drug discovery and development. Here, we have derived an in silico profile by analyzing computed physicochemical descriptors for the variable regions (Fv) found in 77 marketed antibody-based biotherapeutics. Fv regions of these biotherapeutics demonstrate significant diversities in their germlines, complementarity determining region loop lengths, hydrophobicity, and charge distributions. Furthermore, an analysis of 24 physicochemical descriptors, calculated using homology-based molecular models, has yielded five nonredundant descriptors whose distributions represent stability, isoelectric point, and molecular surface characteristics of their Fv regions. Fv regions of candidates from our internal discovery campaigns, human next-generation sequencing repertoires, and those in clinical-stages (CST) were assessed for similarity with the physicochemical profile derived here. The Fv regions in 33% of CST antibodies show physicochemical properties that are dissimilar to currently marketed biotherapeutics. In comparison, physicochemical characteristics of ∼29% of the Fv regions in human antibodies and ∼27% of our internal hits deviated significantly from those of marketed biotherapeutics. The early availability of this information can help guide hit selection, lead identification, and optimization of biotherapeutic candidates. Insights from this work can also help support portfolio risk assessment, in-licensing, and biopharma collaborations.

Exploring the sequence features determining amyloidosis in human antibody light chains

The light chain (AL) amyloidosis is caused by the aggregation of light chain of antibodies into amyloid fibrils. There are plenty of computational resources available for the prediction of short aggregation-prone regions within proteins. However, it is still a challenging task to predict the amyloidogenic nature of the whole protein using sequence/structure information. In the case of antibody light chains, common architecture and known binding sites can provide vital information for the prediction of amyloidogenicity at physiological conditions. Here, in this work, we have compared classical sequence-based, aggregation-related features (such as hydrophobicity, presence of gatekeeper residues, disorderness, β-propensity, etc.) calculated for the CDR, FR or V_L regions of amyloidogenic and non-amyloidogenic antibody light chains and implemented the insights gained in a machine learning-based webserver called "V_LAmY-Pred" ( https://web.iitm.ac.in/bioinfo2/vlamy-pred/ ). The model shows prediction accuracy of 79.7% (sensitivity: 78.7% and specificity: 79.9%) with a ROC value of 0.88 on a dataset of 1828 variable region sequences of the antibody light chains. This model will be helpful towards improved prognosis for patients that may likely suffer from diseases caused by light chain amyloidosis, understanding origins of aggregation in antibody-based biotherapeutics, large-scale in-silico analysis of antibody sequences generated by next generation sequencing, and finally towards rational engineering of aggregation resistant antibodies.

Computational approaches to therapeutic antibody design: established methods and emerging trends

Antibodies are proteins that recognize the molecular surfaces of potentially noxious molecules to mount an adaptive immune response or, in the case of autoimmune diseases, molecules that are part of healthy cells and tissues. Due to their binding versatility, antibodies are currently the largest class of biotherapeutics, with five monoclonal antibodies ranked in the top 10 blockbuster drugs. Computational advances in protein modelling and design can have a tangible impact on antibody-based therapeutic development. Antibody-specific computational protocols currently benefit from an increasing volume of data provided by next generation sequencing and application to related drug modalities based on traditional antibodies, such as nanobodies. Here we present a structured overview of available databases, methods and emerging trends in computational antibody analysis and contextualize them towards the engineering of candidate antibody therapeutics.

Immunogenicity of Bioproducts: Cellular Models to Evaluate the Impact of Therapeutic Antibody Aggregates

Patients treated with bioproducts (BPs) frequently develop anti-drug antibodies (ADAs) with potential neutralizing capacities leading to loss of clinical response or potential hypersensitivity reactions. Many factors can influence BP immunogenicity and could be related to the patient, the treatment, as well as to the product itself. Among these latter factors, it is now well accepted that BP aggregation is associated with an increased potential for immunogenicity, as aggregates seem to be correlated with ADA development. Moreover, the presence of high-affinity ADAs suggests a CD4 T-cell dependent adaptive immune response and therefore a pivotal role for antigen-presenting cells (APCs), such as dendritic cells (DCs). In this review, we address the in vitro methods developed to evaluate how monoclonal antibodies could trigger the immunization process by focusing on the role of aggregated antibodies in the establishment of this response. In particular, we will present the different cell-based assays that have been used to assess the potential of antibodies and their aggregates to modulate cellular mechanisms leading to activation and the biological parameters (cellular activation markers, proliferation and secreted molecules) that can be measured to evaluate the different cell activation stages and their consequences in the propagation of the immune response. Indeed, the use of such strategies could help evaluate the risk of BP immunogenicity and their role in mitigating this risk.

Nonclinical immunogenicity risk assessment of therapeutic proteins

Therapeutic protein drugs have significantly improved the management of many severe and chronic diseases. However, their development and optimal clinical application are complicated by the induction of unwanted immune responses. Therapeutic protein-induced antidrug antibodies can alter drug pharmacokinetics and pharmacodynamics leading to impaired efficacy and occasionally serious safety issues. There has been a growing interest over the past decade in developing methods to assess the risk of unwanted immunogenicity during preclinical drug development, with the aim to mitigate the risk during the molecular design phase, clinical development and when products reach the market. Here, we discuss approaches to therapeutic protein immunogenicity risk assessment, with attention to assays and in vivo models used to mitigate this risk.

Fifty-Eight Years and Counting: High-Impact Publishing in Computational Pharmaceutical Sciences and Mechanism-Based Modeling

With this issue of the Journal of Pharmaceutical Sciences, we celebrate the nearly 6 decades of contributions to mechanistic-based modeling and computational pharmaceutical sciences. Along with its predecessor, The Journal of the American Pharmaceutical Association: Scientific Edition first published in 1911, JPharmSci has been a leader in the advancement of pharmaceutical sciences beginning with its inaugural edition in 1961. As one of the first scientific journals focusing on pharmaceutical sciences, JPharmSci has established a reputation for publishing high-quality research articles using computational methods and mechanism-based modeling. The journal's publication record is remarkable. With over 15,000 articles, 3000 notes, and more than 650 reviews from industry, academia, and regulatory agencies around the world, JPharmSci has truly been the leader in advancing pharmaceutical sciences.

Protective effects of silibinin on insulin amyloid fibrillation, cytotoxicity and mitochondrial membrane damage

A growing body of evidence suggests that secretion and assembly of insulin to amyloid fibrils reduce its efficacy in treating type II diabetes and may lead to dysfunctioning of several organs. The research presented here explores the effects of silibinin on the in vitro amyloid fibrillation and cytotoxicity of bovine insulin fibrils on SH-SY5Y human neuroblastoma cells. Interaction of the resulting structures with rat brain mitochondria was also investigated. Using a range of methods for amyloid detection we showed that insulin fibrillation was significantly inhibited by silibinin in a dose-dependent fashion. Moreover, we found that silibinin was very effective in attenuating insulin fibril-induced neuronal toxicity characterized by decrease of cell viability, the release of lactate dehydrogenase, intracellular reactive oxygen species enhancement, morphological alterations, and apoptotic cell death induction. While insulin fibrillation products showed the capacity to damage mitochondria, the resultant structures produced in the presence of silibinin were totally ineffective. Together, results demonstrate the capacity of insulin fibrils to cause SH-SY5Y cell death by inducing necrosis/apoptosis changes and suggest how silibinin may afford protection. It is concluded that elucidation of such protection may provide important insights into the development of preventive and therapeutic agents for amyloid-related diseases.

A role for macromolecular crowding in off-target binding of therapeutic antibodies

The nonspecific binding of certain therapeutic antibodies to tissues or to soluble biomolecules can accelerate their clearance from the circulation and undermine their benefit to patients. This article proposes that tandem amino acid repeat sequences in antibody hypervariable segments, particularly the complementarity determining regions (CDRs), can enhance this off-target binding. This hypothesis is based on two sets of observations. First, in a limited number of cases, antibodies with clusters of amino acid repeats in their CDRs have significantly higher clearance rates in experimental animals than otherwise identical antibodies without the repeats. Second, tandem amino acid repeats are abundant in intracellular hub proteins where they appear to promote the promiscuous binding of these proteins to a wide variety of other molecules. These nonspecific hub protein interactions are highly favored by the intense macromolecular crowding that permeates the cytoplasm. A survey of the variable region sequences of 137 antibodies in various stages of development revealed that 26 have at least one CDR containing a cluster of three closely spaced amino acid repeats. If the overall hypothesis is valid, then it suggests strategies for site-directed mutagenesis to improve pharmacokinetic behavior and for the design of more reliable in vitro binding assays to predict off-target binding in vivo.

Biopharmaceutical Informatics: supporting biologic drug development via molecular modelling and informatics

Objectives

The purpose of this article is to introduce an emerging field called ‘Biopharmaceutical Informatics’. It describes how tools from Information technology and Molecular Biophysics can be adapted, developed and gainfully employed in discovery and development of biologic drugs.

Key Findings

The findings described here are based on literature surveys and the authors’ collective experiences in the field of biologic drug product development. A strategic framework to forecast early the hurdles faced during drug product development is weaved together and elucidated using chemical degradation as an example. Efficiency of translating biologic drug discoveries into drug products can be significantly improved by combining learnings from experimental biophysical and analytical data on the drug candidates with molecular properties computed from their sequences and structures via molecular modeling and simulations.

Summary

Biopharmaceutical Informatics seeks to promote applications of computational tools towards discovery and development of biologic drugs. When fully implemented, industry-wide, it will enable rapid materials-free developability assessments of biologic drug candidates at early stages as well as streamline drug product development activities such as commercial scale production, purification, formulation, analytical characterization, safety and in vivo performance.

Autoimmune Responses to Soluble Aggregates of Amyloidogenic Proteins Involved in Neurodegenerative Diseases: Overlapping Aggregation Prone and Autoimmunogenic regions

Why do patients suffering from neurodegenerative diseases generate autoantibodies that selectively bind soluble aggregates of amyloidogenic proteins? Presently, molecular basis of interactions between the soluble aggregates and human immune system is unknown. By analyzing sequences of experimentally validated T-cell autoimmune epitopes, aggregating peptides, amyloidogenic proteins and randomly generated peptides, here we report overlapping regions that likely drive aggregation as well as generate autoantibodies against the aggregates. Sequence features, that make short peptides susceptible to aggregation, increase their incidence in human T-cell autoimmune epitopes by 4–6 times. Many epitopes are predicted to be significantly aggregation prone (aggregation propensities ≥10%) and the ones containing experimentally validated aggregating regions are enriched in hydrophobicity by 10–20%. Aggregate morphologies also influence Human Leukocyte Antigen (HLA) - types recognized by the aggregating regions containing epitopes. Most (88%) epitopes that contain amyloid fibril forming regions bind HLA-DR, while majority (63%) of those containing amorphous β-aggregating regions bind HLA-DQ. More than two-thirds (70%) of human amyloidogenic proteins contain overlapping regions that are simultaneously aggregation prone and auto-immunogenic. Such regions help clear soluble aggregates by generating selective autoantibodies against them. This can be harnessed for early diagnosis of proteinopathies and for drug/vaccine design against them.

Structural Changes and Aggregation Mechanisms for Anti-Streptavidin IgG1 at Elevated Concentration

Non-native protein aggregation may occur during manufacturing and storage of protein therapeutics, and this may decrease drug efficacy or jeopardize patient safety. From a regulatory perspective, changes in higher order structure due to aggregation are of particular interest but can be difficult to monitor directly at elevated protein concentrations. The present report focuses on non-native aggregation of antistreptavidin (AS) IgG1 at 30 mg/mL under solution conditions that prior work at dilute concentrations (e.g., 1 mg/mL) indicated would result in different aggregation mechanisms. Time-dependent aggregation and structural changes were monitored in situ with dynamic light scattering, small-angle neutron scattering, and Raman scattering and ex situ with far-UV circular dichroism and second-derivative UV spectroscopy. The effects of adding 0.15 M (∼5 w/w %) sucrose were also assessed. The addition of sucrose decreased monomer loss rates but did not change protein-protein interactions, aggregation mechanism(s), or aggregate structure and morphology. Consistent with prior results, altering the pD or salt concentration had the primary effect of changing the aggregation mechanism. Overall, the results provide a comparison of aggregate structure and morphology created via different growth mechanisms using orthogonal techniques and show that the techniques agree at least qualitatively. Interestingly, AS-IgG1 aggregates created at pD 5.3 with no added salt formed the smallest aggregates but had the largest structural changes compared to other solution conditions. The observation that the larger aggregates were also those with less structural perturbation compared to folded AS-IgG1 might be expected to extend to other proteins if the same strong electrostatic repulsions that mediate aggregate growth also mediate structural changes of the constituent proteins within aggregates.

The Role of Aggregates of Therapeutic Protein Products in Immunogenicity: An Evaluation by Mathematical Modeling

Therapeutic protein products (TPP) have been widely used to treat a variety of human diseases, including cancer, hemophilia, and autoimmune diseases. However, TPP can induce unwanted immune responses that can impact both drug efficacy and patient safety. The presence of aggregates is of particular concern as they have been implicated in inducing both T cell-independent and T cell-dependent immune responses. We used mathematical modeling to evaluate several mechanisms through which aggregates of TPP could contribute to the development of immunogenicity. Modeling interactions between aggregates and B cell receptors demonstrated that aggregates are unlikely to induce T cell-independent immune responses by cross-linking B cell receptors because the amount of signal transducing complex that can form under physiologically relevant conditions is limited. We systematically evaluate the role of aggregates in inducing T cell-dependent immune responses using a recently developed multiscale mechanistic mathematical model. Our analysis indicates that aggregates could contribute to T cell-dependent immune response by inducing high affinity epitopes which may not be present in the nonaggregated TPP and/or by enhancing danger signals to break tolerance. In summary, our computational analysis is suggestive of novel insights into the mechanisms underlying aggregate-induced immunogenicity, which could be used to develop mitigation strategies.

On the role of aggregation prone regions in protein evolution, stability, and enzymatic catalysis: insights from diverse analyses

The various roles that aggregation prone regions (APRs) are capable of playing in proteins are investigated here via comprehensive analyses of multiple non-redundant datasets containing randomly generated amino acid sequences, monomeric proteins, intrinsically disordered proteins (IDPs) and catalytic residues. Results from this study indicate that the aggregation propensities of monomeric protein sequences have been minimized compared to random sequences with uniform and natural amino acid compositions, as observed by a lower average aggregation propensity and fewer APRs that are shorter in length and more often punctuated by gate-keeper residues. However, evidence for evolutionary selective pressure to disrupt these sequence regions among homologous proteins is inconsistent. APRs are less conserved than average sequence identity among closely related homologues (≥80% sequence identity with a parent) but APRs are more conserved than average sequence identity among homologues that have at least 50% sequence identity with a parent. Structural analyses of APRs indicate that APRs are three times more likely to contain ordered versus disordered residues and that APRs frequently contribute more towards stabilizing proteins than equal length segments from the same protein. Catalytic residues and APRs were also found to be in structural contact significantly more often than expected by random chance. Our findings suggest that proteins have evolved by optimizing their risk of aggregation for cellular environments by both minimizing aggregation prone regions and by conserving those that are important for folding and function. In many cases, these sequence optimizations are insufficient to develop recombinant proteins into commercial products. Rational design strategies aimed at improving protein solubility for biotechnological purposes should carefully evaluate the contributions made by candidate APRs, targeted for disruption, towards protein structure and activity.

Biotechnology requires the large-scale expression, yield, and storage of recombinant proteins. Each step in protein production has the potential to cause aggregation as proteins, not evolved to exist outside the cell, endure the various steps involved in commercial manufacturing processes. Mechanistic studies into protein aggregation have revealed that certain sequence regions contribute more to the aggregation propensity of a protein than other sequence regions do. Efforts to disrupt these regions have thus far indicated that rational sequence engineering is a useful technique to reduce the aggregation of biotechnologically relevant proteins. To improve our ability to rationally engineer proteins with enhanced expression, solubility, and shelf-life we conducted extensive analyses of aggregation prone regions (APRs) within protein sequences to characterize the various roles these regions play in proteins. Findings from this work indicate that protein sequences have evolved by minimizing their aggregation propensities. However, we also found that many APRs are conserved in protein families and are essential to maintain protein stability and function. Therefore, the contributions that APRs, targeted for disruption, make towards protein stability and function should be carefully evaluated when improving protein solubility via rational design.

Challenges and approaches for the development of safer immunomodulatory biologics

Immunomodulatory biologics are a class of biotechnology-derived therapeutic products that are designed to engage immune-relevant targets and are indicated in the treatment and management of a range of diseases, including immune-mediated inflammatory diseases and malignancies.

Despite their high specificity and therapeutic advantages, immmunomodulatory biologics have been associated with adverse reactions such as serious infections, malignancies and cytokine release syndrome, which arise owing to the on-target or exaggerated pharmacological effects of these drugs. Immunogenicity resulting in the generation of antidrug antibodies is another unwanted effect that leads to loss of efficacy and — rarely — hypersensitivity reactions.

For some adverse reactions, mitigating and preventive strategies are in place, such as stratifying patients on the basis of responsiveness to therapy and the risk of developing adverse reactions. These strategies depend on the availability of robust biomarkers for therapeutic efficacy and the risk of adverse reactions: for example, seropositivity for John Cunningham virus is a risk factor for progressive multifocal leukoencephalopathy. The development of effective biomarkers will greatly aid these strategies.

The development and design of safer immunomodulatory biologics is reliant on a detailed understanding of the nature of the disease, target biology, the interaction of the target with the immunomodulatory biologic and the inherent properties of the biologic that elicit unwanted effects.

The availability of in vitro and in vivo models that can be used to predict adverse reactions associated with immunomodulatory biologics is central to the development of safer immunomodulatory biologics. Some progress has been made in developing in vitro and in silico tests for predicting cytokine release syndrome and immunogenicity, but there is still a lack of models for effectively predicting infections and malignancies.

Two pathways can be followed in designing and developing safer immunomodulatory biologics. The first pathway involves generating a biologic that engages an alternative target or mechanism to produce the desired pharmacodynamic effect without the associated adverse reaction, and is followed when the adverse reaction cannot be dissociated from the target biology. The second pathway involves redesigning the biologic to 'engineer out' components within the biologic structure that trigger adverse effects or to alter the nature of the target–biologic interactions.

Owing to their specificity, immunomodulatory biologics generally have better safety profiles than small-molecule drugs. However, adverse effects such as an increased risk of infections or cytokine release syndrome are of concern. Here, Park and colleagues discuss the current strategies used to predict and mitigate these adverse effects and consider how they can be used to inform the development of safer immunomodulatory biologics.

Immunomodulatory biologics, which render their therapeutic effects by modulating or harnessing immune responses, have proven their therapeutic utility in several complex conditions including cancer and autoimmune diseases. However, unwanted adverse reactions — including serious infections, malignancy, cytokine release syndrome, anaphylaxis and hypersensitivity as well as immunogenicity — pose a challenge to the development of new (and safer) immunomodulatory biologics. In this article, we assess the safety issues associated with immunomodulatory biologics and discuss the current approaches for predicting and mitigating adverse reactions associated with their use. We also outline how these approaches can inform the development of safer immunomodulatory biologics.

Biosimilars and biobetters as tools for understanding and mitigating the immunogenicity of biotherapeutics

In this article, we review key steps for the development of biosimilars and biobetters and related bioanalytical challenges, with a focus on how they are associated with immunogenicity. We analyze the factors that can impact antidrug antibody (ADA) responses and their correlations with preclinical and clinical outcomes to provide relevant insights and to answer questions, including what types of aggregate are immunogenic. We also address strategies for developing less-immunogenic biotherapeutics. Using interferon-β (IFN-β) as a case study, we explore the correlation between aggregation and immunogenicity. We dissect and integrate with clinical data the IFN-β preclinical immunogenicity and aggregation predictions and discuss the feasibility of developing an IFN-β with lower aggregation and/or immunogenicity.