Development of a strategy and computational application to select candidate protein analogues with reduced HLA binding and immunogenicity

An ankyrin repeat chaperone targets toxic oligomers during amyloidogenesis

Numerous age-linked diseases are rooted in protein misfolding; this has motivated the development of small molecules and therapeutic antibodies that target the aggregation of disease-linked proteins. Here we explore another approach: molecular chaperones with engineerable protein scaffolds such as the ankyrin repeat domain (ARD). We tested the ability of cpSRP43, a small, robust, ATP- and cofactor-independent plant chaperone built from an ARD, to antagonize disease-linked protein aggregation. cpSRP43 delays the aggregation of multiple proteins including the amyloid beta peptide (Aβ) associated with Alzheimer's disease and α-synuclein associated with Parkinson's disease. Kinetic modeling and biochemical analyses show that cpSRP43 targets early oligomers during Aβ aggregation, preventing their transition to a self-propagating nucleus on the fibril surface. Accordingly, cpSRP43 rescued neuronal cells from the toxicity of extracellular Aβ42 aggregates. The substrate-binding domain of cpSRP43, composed primarily of the ARD, is necessary and sufficient to prevent Aβ42 aggregation and protect cells against Aβ42 toxicity. This work provides an example in which an ARD chaperone non-native to mammalian cells harbors anti-amyloidal activity, which may be exploited for bioengineering.

Considering epitopes conservity in targeting SARS-CoV-2 mutations in variants: a novel immunoinformatics approach to vaccine design

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has gained mutations at an alarming rate in the past years. Developing mutations can increase the virus's pathogenicity and virulence; reduce the efficacy of vaccines, antibodies neutralization, and even challenge adaptive immunity. So, it is essential to identify conserved epitopes (with fewer mutations) in different variants with appropriate antigenicity to target the variants by an appropriate vaccine design. Yet as, 3369 SARS-CoV-2 genomes were collected from global initiative on sharing avian flu data. Then, mutations in the immunodominant regions (IDRs), immune epitope database (IEDB) epitopes, and also predicted epitopes were calculated. In the following, epitopes conservity score against the total number of events (mutations) and the number of mutated sites in each epitope was weighted by Shannon entropy and then calculated by the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). Based on the TOPSIS conservity score and antigenicity score, the epitopes were plotted. The result demonstrates that almost all epitopes and IDRs with various lengths have gained different numbers of mutations in dissimilar sites. Herein, our two-step calculation for conservity recommends only 8 IDRs, 14 IEDB epitopes, and 10 predicted epitopes among all epitopes. The selected ones have higher conservity and higher immunogenicity. This method is an open-source multi-criteria decision-making platform, which provides a scientific approach to selecting epitopes with appropriate conservity and immunogenicity; against ever-changing viruses.

Humanization of Camelid Single-Domain Antibodies

Humanization of therapeutic antibodies derived from animal immunizations is often required to minimize immunogenicity risks in humans, which can cause potentially harmful and serious side effects and reduce antibody efficacy. Humanization is typically applied to conventional monoclonal antibodies derived in rodents as well as single-domain antibodies isolated from camelids and sharks (VHHs and VNARs). A streamlined protocol is described here for sequence humanization of camelid VHHs, which represent a promising biotherapeutic format with many desirable attributes. From human framework selection and complementarity-determining region grafting strategies to empirical scoring for prioritization of back-mutations, step-by-step instructions, and templates are provided along with bioinformatics resources to assist each step of the humanization process. Alternative approaches, warnings, and caveats are also presented.

virusMED: an atlas of hotspots of viral proteins

Metal binding sites, antigen epitopes and drug binding sites are the hotspots in viral proteins that control how viruses interact with their hosts. virusMED (virus Metal binding sites, Epitopes and Drug binding sites) is a rich internet application based on a database of atomic interactions around hotspots in 7041 experimentally determined viral protein structures. 25306 hotspots from 805 virus strains from 75 virus families were characterized, including influenza, HIV-1 and SARS-CoV-2 viruses. Just as Google Maps organizes and annotates points of interest, virusMED presents the positions of individual hotspots on each viral protein and creates an atlas upon which newly characterized functional sites can be placed as they are being discovered. virusMED contains an extensive set of annotation tags about the virus species and strains, viral hosts, viral proteins, metal ions, specific antibodies and FDA-approved drugs, which permits rapid screening of hotspots on viral proteins tailored to a particular research problem. The virusMED portal (https://virusmed.biocloud.top) can serve as a window to a valuable resource for many areas of virus research and play a critical role in the rational design of new preventative and therapeutic agents targeting viral infections.

Adapting protein sequences for optimized therapeutic efficacy

Therapeutic proteins alleviate disease pathology by supplementing missing or defective native proteins, sequestering superfluous proteins, or by acting through designed non-natural mechanisms. Although therapeutic proteins often have the same amino acid sequence as their native counterpart, their maturation paths from expression to the site of physiological activity are inherently different, and optimizing protein sequences for properties that 100s of millions of years of evolution did not need to address presents an opportunity to develop better biological treatments. Because therapeutic proteins are inherently non-natural entities, optimization for their desired function should be considered analogous to that of small molecule drug candidates, which are optimized through expansive combinatorial variation by the medicinal chemist. Here, we review recent successes and challenges of protein engineering for optimized therapeutic efficacy.

Predicting Immunogenicity Risk in Biopharmaceuticals

The assessment of immunogenicity of biopharmaceuticals is a crucial step in the process of their development. Immunogenicity is related to the activation of adaptive immunity. The complexity of the immune system manifests through numerous different mechanisms, which allows the use of different approaches for predicting the immunogenicity of biopharmaceuticals. The direct experimental approaches are sometimes expensive and time consuming, or their results need to be confirmed. In this case, computational methods for immunogenicity prediction appear as an appropriate complement in the process of drug design. In this review, we analyze the use of various In silico methods and approaches for immunogenicity prediction of biomolecules: sequence alignment algorithms, predicting subcellular localization, searching for major histocompatibility complex (MHC) binding motifs, predicting T and B cell epitopes based on machine learning algorithms, molecular docking, and molecular dynamics simulations. Computational tools for antigenicity and allergenicity prediction also are considered.

Improved prediction of HLA antigen presentation hotspots: Applications for immunogenicity risk assessment of therapeutic proteins

Immunogenicity risk assessment is a critical element in protein drug development. Currently, the risk assessment is most often performed using MHC-associated peptide proteomics (MAPPs) and/or T-cell activation assays. However, this is a highly costly procedure that encompasses limited sensitivity imposed by sample sizes, the MHC repertoire of the tested donor cohort and the experimental procedures applied. Recent work has suggested that these techniques could be complemented by accurate, high-throughput and cost-effective prediction of in silico models. However, this work covered a very limited set of therapeutic proteins and eluted ligand (EL) data. Here, we resolved these limitations by showcasing, in a broader setting, the versatility of in silico models for assessment of protein drug immunogenicity. A method for prediction of MHC class II antigen presentation was developed on the hereto largest available mass spectrometry (MS) HLA-DR EL data set. Using independent test sets, the performance of the method for prediction of HLA-DR antigen presentation hotspots was benchmarked. In particular, the method was showcased on a set of protein sequences including four therapeutic proteins and demonstrated to accurately predict the experimental MS hotspot regions at a significantly lower false-positive rate compared with other methods. This gain in performance was particularly pronounced when compared to the NetMHCIIpan-3.2 method trained on binding affinity data. These results suggest that in silico methods trained on MS HLA EL data can effectively and accurately be used to complement MAPPs assays for the risk assessment of protein drugs.

T-Cell Dependent Immunogenicity of Protein Therapeutics Pre-clinical Assessment and Mitigation-Updated Consensus and Review 2020

Immune responses to protein and peptide drugs can alter or reduce their efficacy and may be associated with adverse effects. While anti-drug antibodies (ADA) are a standard clinical measure of protein therapeutic immunogenicity, T cell epitopes in the primary sequences of these drugs are the key drivers or modulators of ADA response, depending on the type of T cell response that is stimulated (e.g., T helper or Regulatory T cells, respectively). In a previous publication on T cell-dependent immunogenicity of biotherapeutics, we addressed mitigation efforts such as identifying and reducing the presence of T cell epitopes or T cell response to protein therapeutics prior to further development of the protein therapeutic for clinical use. Over the past 5 years, greater insight into the role of regulatory T cell epitopes and the conservation of T cell epitopes with self (beyond germline) has improved the preclinical assessment of immunogenic potential. In addition, impurities contained in therapeutic drug formulations such as host cell proteins have also attracted attention and become the focus of novel risk assessment methods. Target effects have come into focus, given the emergence of protein and peptide drugs that target immune receptors in immuno-oncology applications. Lastly, new modalities are entering the clinic, leading to the need to revise certain aspects of the preclinical immunogenicity assessment pathway. In addition to drugs that have multiple antibody-derived domains or non-antibody scaffolds, therapeutic drugs may now be introduced via viral vectors, cell-based constructs, or nucleic acid based therapeutics that may, in addition to delivering drug, also prime the immune system, driving immune response to the delivery vehicle as well as the encoded therapeutic, adding to the complexity of assessing immunogenicity risk. While it is challenging to keep pace with emerging methods for the preclinical assessment of protein therapeutics and new biologic therapeutic modalities, this collective compendium provides a guide to current best practices and new concepts in the field.

IEDB-AR: immune epitope database-analysis resource in 2019

The Immune Epitope Database Analysis Resource (IEDB-AR, http://tools.iedb.org/) is a companion website to the IEDB that provides computational tools focused on the prediction and analysis of B and T cell epitopes. All of the tools are freely available through the public website and many are also available through a REST API and/or a downloadable command-line tool. A virtual machine image of the entire site is also freely available for non-commercial use and contains most of the tools on the public site. Here, we describe the tools and functionalities that are available in the IEDB-AR, focusing on the 10 new tools that have been added since the last report in the 2012 NAR webserver edition. In addition, many of the tools that were already hosted on the site in 2012 have received updates to newest versions, including NetMHC, NetMHCpan, BepiPred and DiscoTope. Overall, this IEDB-AR update provides a substantial set of updated and novel features for epitope prediction and analysis.

Validation of a de-immunization strategy for monoclonal antibodies using cynomolgus macaque as a surrogate for human

The immunogenicity of biotherapeutics presents a major challenge during the clinical development of new protein drugs including monoclonal antibodies. To address this, multiple humanization and de-immunization techniques that employ in silico algorithms and in vitro test systems have been proposed and implemented. However, the success of these approaches has been variable and to date, the ability of these techniques to predict immunogenicity has not been systematically tested in humans or other primates. This study tested whether antibody humanization and de-immunization strategies reduce the risk of anti-drug antibody (ADA) development using cynomolgus macaque as a surrogate for human. First human-cyno chimeric antibodies were constructed by grafting the variable domains of the adalimumab and golimumab monoclonal antibodies onto cynomolgus macaque IgG1 and Igκ constant domains followed by framework germlining to cyno to reduce the xenogenic content. Next, B and T cell epitopes and aggregation-prone regions were identified using common in silico methods to select domains with an ADA risk for additional modification. The resultant engineered antibodies had a comparable affinity for TNFα, demonstrated similar biophysical properties, and exhibited significantly reduced ADA levels in cynomolgus macaque compared with the parental antibodies, with a corresponding improvement in the pharmacokinetic profile. Notably, plasma concentrations of the engineered antibodies were quantifiable through 504 hours (chimeric) and 840 hours (germlined/de-immunized), compared with only 336 hours (adalimumab) or 336-672 hours (golimumab). The results point to the significant value in the investment in these engineering strategies as an important guide for monoclonal antibody optimization that can contribute to improved clinical outcomes.

Design, creation and in vitro testing of a reduced immunogenicity humanized anti-CD25 monoclonal antibody that retains functional activity

Humanized and fully human sequence-derived therapeutic antibodies retain the capacity to induce anti-drug antibodies. Daclizumab (humanized version of the murine anti-Tac antibody; E.HAT) was selected for a proof of concept application of engineering approaches to reduce potential immunogenicity due to its demonstrated immunogenicity in the clinic. Reduced immunogenicity variants of E.HAT were created by identifying and modifying a CD4+ T cell epitope region in the VH region. Variant epitope region peptides were selected for their reduced capacity to induce CD4+ T cell proliferative responses in vitro. Variant antibody molecules were created, and CD25 affinity and potency were similar to the unmodified parent antibody. Fab fragments from the variant antibodies induced a lower frequency and magnitude of responses in human peripheral blood mononuclear cells proliferation tests. By the empirical selection of two amino acid mutations, fully functional humanized E.HAT antibodies with reduced potential to induce immune responses in vitro were created.

ImmunomeBrowser: a tool to aggregate and visualize complex and heterogeneous epitopes in reference proteins

Motivation

Datasets that are derived from different studies (e.g. MHC ligand elution, MHC binding, B/T cell epitope screening etc.) often vary in terms of experimental approaches, sizes of peptides tested, including partial and or nested overlapping peptides and in the number of donors tested.

Results

We present a customized application of the Immune Epitope Database’s ImmunomeBrowser tool, which can be used to effectively aggregate and visualize heterogeneous immunological data. User provided peptide sets and associated response data is mapped to a user-provided protein reference sequence. The output consists of tables and figures representing the aggregated data represented by a Response Frequency score and associated estimated confidence interval. This allows the user to visualizing regions associated with dominant responses and their boundaries. The results are presented both as a user interactive javascript based web interface and a tabular format in a selected reference sequence.

Availability and implementation

The ‘ImmunomeBrowser’ has been a longstanding feature of the IEDB (http://www.iedb.org). The present application extends the use of this tool to work with user-provided datasets, rather than the output of IEDB queries. This new server version of the ImmunomeBrowser is freely accessible at http://tools.iedb.org/immunomebrowser/.

TCPro: an In Silico Risk Assessment Tool for Biotherapeutic Protein Immunogenicity

Most immune responses to biotherapeutic proteins involve the development of anti-drug antibodies (ADAs). New drugs must undergo immunogenicity assessments to identify potential risks at early stages in the drug development process. This immune response is T cell-dependent. Ex vivo assays that monitor T cell proliferation often are used to assess immunogenicity risk. Such assays can be expensive and time-consuming to carry out. Furthermore, T cell proliferation requires presentation of the immunogenic epitope by major histocompatibility complex class II (MHCII) proteins on antigen-presenting cells. The MHC proteins are the most diverse in the human genome. Thus, obtaining cells from subjects that reflect the distribution of the different MHCII proteins in the human population can be challenging. The allelic frequencies of MHCII proteins differ among subpopulations, and understanding the potential immunogenicity risks would thus require generation of datasets for specific subpopulations involving complex subject recruitment. We developed TCPro, a computational tool that predicts the temporal dynamics of T cell counts in common ex vivo assays for drug immunogenicity. Using TCPro, we can test virtual pools of subjects based on MHCII frequencies and estimate immunogenicity risks for different populations. It also provides rapid and inexpensive initial screens for new biotherapeutics and can be used to determine the potential immunogenicity risk of new sequences introduced while bioengineering proteins. We validated TCPro using an experimental immunogenicity dataset, making predictions on the population-based immunogenicity risk of 15 protein-based biotherapeutics. Immunogenicity rankings generated using TCPro are consistent with the reported clinical experience with these therapeutics.

Positive selection pressure on E2 protein of classical swine fever virus drives variations in virulence, pathogenesis and antigenicity: Implication for epidemiological surveillance in endemic areas

Classical swine fever (CSF), caused by CSF virus (CSFV), is considered one of the most important infectious diseases with devasting consequences for the pig industry. Recent reports describe the emergence of new CSFV strains resulting from the action of positive selection pressure, due mainly to the bottleneck effect generated by ineffective vaccination. Even though a decrease in the genetic diversity of the positively selected CSFV strains has been observed by several research groups, there is little information about the effect of this selective force on the virulence degree, antigenicity and pathogenicity of this type of strains. Hence, the aim of the current study was to determine the effect of the positive selection pressure on these three parameters of CSFV strains, emerged as result of the bottleneck effects induced by improper vaccination in a CSF-endemic area. Moreover, the effect of the positively selected strains on the epidemiological surveillance system was assessed. By the combination of in vitro, in vivo and immunoinformatic approaches, we revealed that the action of the positive selection pressure induces a decrease in virulence and alteration in pathogenicity and antigenicity. However, we also noted that the evolutionary process of CSFV, especially in segregated microenvironments, could contribute to the gain-fitness event, restoring the highly virulent pattern of the circulating strains. Besides, we denoted that the presence of low virulent strains selected by bottleneck effect after inefficient vaccination can lead to a relevant challenge for the epidemiological surveillance of CSF, contributing to under-reports of the disease, favouring the perpetuation of the virus in the field. In this study, B-cell and CTL epitopes on the E2 3D-structure model were also identified. Thus, the current study provides novel and significant insights into variation in virulence, pathogenesis and antigenicity experienced by CSFV strains after the positive selection pressure effect.

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.

Anti-Drug Antibodies: Emerging Approaches to Predict, Reduce or Reverse Biotherapeutic Immunogenicity

The development of anti-drug antibodies (ADAs) following administration of biotherapeutics to patients is a vexing problem that is attracting increasing attention from pharmaceutical and biotechnology companies. This serious clinical problem is also spawning creative research into novel approaches to predict, avoid, and in some cases even reverse such deleterious immune responses. CD4⁺ T cells are essential players in the development of most ADAs, while memory B-cell and long-lived plasma cells amplify and maintain these responses. This review summarizes methods to predict and experimentally identify T-cell and B-cell epitopes in therapeutic proteins, with a particular focus on blood coagulation factor VIII (FVIII), whose immunogenicity is clinically significant and is the subject of intensive current research. Methods to phenotype ADA responses in humans are described, including T-cell stimulation assays, and both established and novel approaches to determine the titers, epitopes and isotypes of the ADAs themselves. Although rational protein engineering can reduce the immunogenicity of many biotherapeutics, complementary, novel approaches to induce specific tolerance, especially during initial exposures, are expected to play significant roles in future efforts to reduce or reverse these unwanted immune responses.

Antibacterial Peptides in Dermatology-Strategies for Evaluation of Allergic Potential

During recent decades, the market for peptide-based drugs, including antimicrobial peptides, has vastly extended and evolved. These drugs can be useful in treatment of various types of disorders, e.g., cancer, autoimmune diseases, infections, and non-healing wounds. Although peptides are less immunogenic than other biologic therapeutics, they can still induce immune responses and cause allergies. It is important to evaluate the immunogenic and allergic potential of peptides before they are forwarded to the expensive stages of clinical trials. The process of the evaluation of immunogenicity and cytotoxicity is complicated, as in vitro models and bioinformatics tools cannot fully simulate situations in the clinic. Nevertheless, several potentially promising tests for the preclinical evaluation of peptide drugs have been implemented (e.g., cytotoxicity assays, the basophil activation test, and lymphocyte activation assays). In this review, we focus on strategies for evaluation of the allergic potential of peptide-based therapeutics.