Optimization algorithms for functional deimmunization of therapeutic proteins

<p>Abstract</p> <p>Background</p> <p>To develop protein therapeutics from exogenous sources, it is necessary to mitigate the risks of eliciting an anti-biotherapeutic immune response. A key aspect of the response is the recognition and surface display by antigen-presenting cells of epitopes, short peptide fragments derived from the foreign protein. Thus, developing minimal-epitope variants represents a powerful approach to deimmunizing protein therapeutics. Critically, mutations selected to reduce immunogenicity must not interfere with the protein's therapeutic activity.</p> <p>Results</p> <p>This paper develops methods to improve the likelihood of simultaneously reducing the anti-biotherapeutic immune response while maintaining therapeutic activity. A dynamic programming approach identifies optimal and near-optimal sets of conservative point mutations to minimize the occurrence of predicted T-cell epitopes in a target protein. In contrast with existing methods, those described here integrate analysis of immunogenicity and stability/activity, are broadly applicable to any protein class, guarantee global optimality, and provide sufficient flexibility for users to limit the total number of mutations and target MHC alleles of interest. The input is simply the primary amino acid sequence of the therapeutic candidate, although crystal structures and protein family sequence alignments may also be input when available. The output is a scored list of sets of point mutations predicted to reduce the protein's immunogenicity while maintaining structure and function. We demonstrate the effectiveness of our approach in a number of case study applications, showing that, in general, our best variants are predicted to be better than those produced by previous deimmunization efforts in terms of either immunogenicity or stability, or both factors.</p> <p>Conclusions</p> <p>By developing global optimization algorithms leveraging well-established immunogenicity and stability prediction techniques, we provide the protein engineer with a mechanism for exploring the favorable sequence space near a targeted protein therapeutic. Our mechanism not only helps identify designs more likely to be effective, but also provides insights into the interrelated implications of design choices.</p

Mapping the Pareto Optimal Design Space for a Functionally Deimmunized Biotherapeutic Candidate

The immunogenicity of biotherapeutics can bottleneck development pipelines and poses a barrier to widespread clinical application. As a result, there is a growing need for improved deimmunization technologies. We have recently described algorithms that simultaneously optimize proteins for both reduced T cell epitope content and high-level function. In silico analysis of this dual objective design space reveals that there is no single global optimum with respect to protein deimmunization. Instead, mutagenic epitope deletion yields a spectrum of designs that exhibit tradeoffs between immunogenic potential and molecular function. The leading edge of this design space is the Pareto frontier, i.e. the undominated variants for which no other single design exhibits better performance in both criteria. Here, the Pareto frontier of a therapeutic enzyme has been designed, constructed, and evaluated experimentally. Various measures of protein performance were found to map a functional sequence space that correlated well with computational predictions. These results represent the first systematic and rigorous assessment of the functional penalty that must be paid for pursuing progressively more deimmunized biotherapeutic candidates. Given this capacity to rapidly assess and design for tradeoffs between protein immunogenicity and functionality, these algorithms may prove useful in augmenting, accelerating, and de-risking experimental deimmunization efforts

DEEP LEARNING METHODS FOR PREDICTION OF AND ESCAPE FROM PROTEIN RECOGNITION

Protein interactions drive diverse processes essential to living organisms, and thus numerous biomedical applications center on understanding, predicting, and designing how proteins recognize their partners. While unfortunately the number of interactions of interest still vastly exceeds the capabilities of experimental determination methods, computational methods promise to fill the gap. My thesis pursues the development and application of computational methods for several protein interaction prediction and design tasks. First, to improve protein-glycan interaction specificity prediction, I developed GlyBERT, which learns biologically relevant glycan representations encapsulating the components most important for glycan recognition within their structures. GlyBERT encodes glycans with a branched biochemical language and employs an attention-based deep language model to embed the correlation between local and global structural contexts. This approach enables the development of predictive models from limited data, supporting applications such as lectin binding prediction. Second, to improve protein-protein interaction prediction, I developed a unified geometric deep neural network, ‘PInet’ (Protein Interface Network), which leverages the best properties of both data- and physics-driven methods, learning and utilizing models capturing both geometrical and physicochemical molecular surface complementarity. In addition to obtaining state-of-the-art performance in predicting protein-protein interactions, PInet can serve as the backbone for other protein-protein interaction modeling tasks such as binding affinity prediction. Finally, I turned from ii prediction to design, addressing two important tasks in the context of antibodyantigen recognition. The first problem is to redesign a given antigen to evade antibody recognition, e.g., to help biotherapeutics avoid pre-existing immunity or to focus vaccine responses on key portions of an antigen. The second problem is to design a panel of variants of a given antigen to use as “bait” in experimental identification of antibodies that recognize different parts of the antigen, e.g., to support classification of immune responses or to help select among different antibody candidates. I developed a geometry-based algorithm to generate variants to address these design problems, seeking to maximize utility subject to experimental constraints. During the design process, the algorithm accounts for and balances the effects of candidate mutations on antibody recognition and on antigen stability. In retrospective case studies, the algorithm demonstrated promising precision, recall, and robustness of finding good designs. This work represents the first algorithm to systematically design antigen variants for characterization and evasion of polyclonal antibody responses

Optimization Algorithms for Site-directed Protein Recombination Experiment Planning

Site-directed protein recombination produces improved and novel protein variants by recombining sequence fragments from parent proteins. The resulting hybrids accumulate multiple mutations that have been evolutionarily accepted together. Subsequent screening or selection identifies hybrids with desirable characteristics. In order to increase the hit rate of good variants, this thesis develops experiment planning algorithms to optimize protein recombination experiments. First, to improve the frequency of generating novel hybrids, a metric is developed to assess the diversity among hybrids and parent proteins. Dynamic programming algorithms are then created to optimize the selection of breakpoint locations according to this metric. Second, the trade-off between diversity and stability in recombination experiment planning is studied, recognizing that diversity requires changes from parent proteins, which may also disrupt important residue interactions necessary for protein stability. Accordingly, methods based on dynamic programming are developed to provide combined optimization of diversity and stability, finding optimal breakpoints such that no other experiment plan has better performance in both aspects simultaneously. Third, in order to support protein recombination with heterogeneous structures and focus on functionally important regions, a general framework for protein fragment swapping is developed. Differentiating source and target parents, and swappable regions within them, fragment swapping enables asymmetric, selective site-directed recombination. Two applications of protein fragment swapping are studied. In order to generate hybrids inheriting functionalities from both source and target proteins by fragment swapping, a method based on integer programming selects optimal swapping fragments to maximize the predicted stability and activity of hybrids in the resulting library. In another application, human source protein fragments are swapped into therapeutic exogenous target protein to minimize the occurrence of peptides that trigger immune response. A dynamic programming method is developed to optimize fragment selection for both humanity and functionality, resulting in therapeutically active variants with decreased immunogenicity

Mammalian Cell Line Development Platform for Recombinant Protein Production: Expanding the Protein Expression Toolbox for Research and Drug Discovery Applications

Recombinant proteins have revolutionized the biomedical industry, providing therapeutics for life-threatening diseases and protein reagents for research applications. BioMarin Pharmaceutical Inc. develops recombinant protein therapeutics to treat rare diseases including lysosomal storage disorders (LSDs), a group of about 50 individually rare disorders together affecting 1 in 8,000 live births. With an increase in the number of novel therapeutics in our drug discovery pipeline, there is a high demand to produce a variety of recombinant proteins for early-stage drug development projects. In order to equip our protein production process with the tools and capability for diverse protein expression, it is valuable to expand our expression toolbox with high-expressing platforms. The goal of this project is to expand to our current expression platforms by developing a murine myeloma based expression system with SP2/0 cells as a host. Since the SP2/0 cell line is amongst the most commonly used cell lines for therapeutic and reagent protein production, developing a SP2/0 expression system may offer additional benefits to our recombinant protein production needs including: expression of difficultto-express proteins, improving titers, and extending recombinant cell line stability. A lysosomal enzyme therapeutic candidate is expressed in the SP2/0 cells as a proof-of-concept for developing this protein expression platform. To this end, we have shown that SP2/0 cells can be grown to a high density in commercially available serum-free media with a doubling time of less than twenty four hours. A clone isolation strategy was used to pick the top clone expressing high levels of recombinant protein. Using the highest expressing clone, we developed a high yielding bioprocess at a two liter scale to demonstrate the utility of this system for generating recombinant proteins at large scale. Furthermore, the therapeutic properties of the recombinant protein expressed in SP2/0 cells are similar to the recombinant protein expressed in Chinese hamster ovary (CHO) cell lines, demonstrating similar uptake into diseased cells (Kuptake values) and binding affinity to the receptor responsible for drug mediated cellular uptake. Thus, the SP2/0 expression system proves to be a valuable addition to our expression toolbox for the production of research-grade protein therapeutics for cell-based assays

NEXT-GENERATION SEQUENCING AND MOTIF GRAFTING APPLICATIONS IN SYNTHETIC ANTIBODY DISCOVERY

The overall objective of this PhD project was to develop and validate methods for advancing the applications of two techniques, next-generation sequencing (NGS) and motif grafting, in synthetic antibody discovery. In the first part of this project, we developed an NGS-assisted antibody discovery platform by integrating phage-displayed single-framework synthetic antigen- binding fragment (Fab) libraries with Ion Torrent sequencing. We constructed a new single- framework synthetic Fab library containing 8.5 billion unique Fab clones, and validated its functionality by generating high affinity Fabs against Notch and Jagged receptors. We developed a rapid and simple method to link and sequence all diversified complementarity-determining regions (CDRs) in phage Fab pools without losing the CDR pairing information. We identified and reconstructed low-frequency rare Fab clones from NGS information in a reliable and high- throughput manner. In some cases, reconstructed rare clones (frequency ~0.1%) showed higher affinity and better specificity than high-frequency top clones isolated by Sanger sequencing, highlighting the importance of NGS in synthetic antibody discovery. In the second part of this project, we employed motif grafting to semi-rationally design phage-displayed synthetic Fab libraries that are biased towards interacting with a specific site on a receptor. We used structural information on the epidermal growth factor receptor (EGFR) homo-dimerization interaction to design a structure-guided Fab library that was biased towards interacting with domain II of EGFR. We used this structure-guided Fab library to obtain Fabs against the EGFR extracellular domain. For comparison, we used a naïve synthetic Fab library to generate an anti-EGFR Fab whose binding overlapped with the Fab isolated from the structure-guided Fab library. Both Fabs possessed low-nM binding values for recombinant and cell-surface EGFR and inhibited EGF- mediated EGFR activation. Epitope mapping showed that domain II is partially responsible for the interaction of Fabs with EGFR. Further, both Fabs target unique epitopes that are different from previously validated epitopes on EGFR. In total, this PhD project resulted in novel methods for discovering synthetic antibodies using NGS and motif grafting techniques, three functional Fab libraries and numerous high-affinity Fabs against Notch, Jagged and EGF receptors

Development of Novel Zika and Anthrax Viral Nanoparticle Vaccines

Vaccines protect against numerous infectious diseases and prevent millions of deaths annually, but there are still many infectious diseases for which no licensed vaccine exists. Developing a new vaccine requires balancing safety and efficacy, and viral nanoparticle (VNP) vaccines possess both of these characteristics. The work herein demonstrates how tobacco mosaic virus (TMV) nanoparticles can serve as a platform to create candidate vaccines for Zika virus (ZIKV) and anthrax. In the first study, a ZIKV-specific epitope was genetically fused to TMV to create a safe and inexpensive vaccine that proved highly immunogenic in mice and led to the discovery of ZIKV-specific neutralizing antibodies that may have applications in therapeutics and diagnostics. In the second study, anthrax toxin domains were expressed, purified, and conjugated to the outer surface of modified TMV nanoparticles. These VNPs were readily recognized by anthrax immune serum, but further studies will be necessary to ascertain their ability to induce a protective immune response. As demonstrated in these studies, genetic fusions and chemical conjugations to TMV each have distinct benefits and limitations. However, both methods result in the production of TMV-based VNPs, in which the TMV virion acts as both a scaffold and delivery mechanism, ensuring that the foreign antigens are taken up by DCs, transported to lymph nodes, and stimulate robust, antigen-specific B and T cell responses. In summation, this work shows how TMV VNPs displaying exogenous antigens can be used to create novel vaccines against both viral and bacterial pathogens

Modulation of immune responses using adjuvants to facilitate therapeutic vaccination

Publsher's version (útgefin grein)Therapeutic vaccination offers great promise as an intervention for a diversity of infectious and non-infectious conditions. Given that most chronic health conditions are thought to have an immune component, vaccination can at least in principle be proposed as a therapeutic strategy. Understanding the nature of protective immunity is of vital importance, and the progress made in recent years in defining the nature of pathological and protective immunity for a range of diseases has provided an impetus to devise strategies to promote such responses in a targeted manner. However, in many cases, limited progress has been made in clinical adoption of such approaches. This in part results from a lack of safe and effective vaccine adjuvants that can be used to promote protective immunity and/or reduce deleterious immune responses. Although somewhat simplistic, it is possible to divide therapeutic vaccine approaches into those targeting conditions where antibody responses can mediate protection and those where the principal focus is the promotion of effector and memory cellular immunity or the reduction of damaging cellular immune responses as in the case of autoimmune diseases. Clearly, in all cases of antigen-specific immunotherapy, the identification of protective antigens is a vital first step. There are many challenges to developing therapeutic vaccines beyond those associated with prophylactic diseases including the ongoing immune responses in patients, patient heterogeneity, and diversity in the type and stage of disease. If reproducible biomarkers can be defined, these could allow earlier diagnosis and intervention and likely increase therapeutic vaccine efficacy. Current immunomodulatory approaches related to adoptive cell transfers or passive antibody therapy are showing great promise, but these are outside the scope of this review which will focus on the potential for adjuvanted therapeutic active vaccination strategies.This article/publication is based upon work from COST Action CA16231 ENOVA (European Network of Vaccine Adjuvants), supported by COST (European Cooperation in Science and Technology—www.cost.eu).Peer Reviewe

In vitro expanded human CD4+CD25+ regulatory T cells suppress effector T cell proliferation.

Regulatory T cells (Tregs) have been shown to be critical in the balance between autoimmunity and tolerance and have been implicated in several human autoimmune diseases. However, the small number of Tregs in peripheral blood limits their therapeutic potential. Therefore, we developed a protocol that would allow for the expansion of Tregs while retaining their suppressive activity. We isolated CD4+CD25 hi cells from human peripheral blood and expanded them in vitro in the presence of anti-CD3 and anti-CD28 magnetic Xcyte Dynabeads and high concentrations of exogenous Interleukin (IL)-2. Tregs were effectively expanded up to 200-fold while maintaining surface expression of CD25 and other markers of Tregs: CD62L, HLA-DR, CCR6, and FOXP3. The expanded Tregs suppressed proliferation and cytokine secretion of responder PBMCs in co-cultures stimulated with anti-CD3 or alloantigen. Treg expansion is a critical first step before consideration of Tregs as a therapeutic intervention in patients with autoimmune or graft-versus-host disease

The modulatory effects of flavonoids on the enzymatic activities of transglutaminase2

To date, a gluten-free diet is the only accepted form of therapy for coeliac disease (CD). Because of the important role of transglutaminase2 enzyme in the initiation of coeliac disease (CD).This study was aimed at the identification of TG2 inhibitors from natural sources, as a potential intervention in CD therapy. The natural products chosen for this study were dietary flavonoids. Kaempferol, morin, and quercetin displayed inhibition on hr TG2 (human recombinant transglutaminase 2) and in fewer extent gplTG2 (Guinea pig transglutaminase2) amine incorporation activity. However, the majority of flavonoids showed a trend of inhibitions (>50% of inhibition at 1.25, 12.5 and125µM) on the cross-linking activity of hrTG2.The flavonoids used did not show a significant inhibitory effect on the amount of ammonia released in the deamidating activity of hrTG2. A novel method for purification of flavonoids from food extracts was developed, using Immobilized Metal Ion Affinity Chromatography (IMAC). In addition, a BCA assay was optimised in a novel quantification method using quercetin as a standard flavonoid. In addition, to the pure flavonoids, flavonoids were extracted from different food samples. In the TG2 amine incorporation activity, all of food extracts display a significant inhibition effect towards the hrTG2 and gplTG2 (20-50% of inhibition). While in the TG2 cross-linking activity, the majority of food extracts did display an inhibition effect on the gpl TG2 cross-linking activity (50-70% of inhibition), but only the Strawberry and kale extract had an effect on hrTG2 activity (40-50% of inhibition). In the deamidation assay, no food extracts showed inhibition. A cell-based fluorescence assay confirmed the TG2 inhibitory characteristic of kaempferol on HT29 cell lines. This was among the first studies to examine the effects of flavonoids on the activity of TG2. The inhibition of transglutaminase 2 (TG2) deamidating activity can be considered as a potential therapeutic target in the treatment of coeliac disease (CD). All current TG2 assays measure amine incorporation, none can specifically measure TG2 deamidating activity because there would be little or no deamidation in the presence of an amine. A novel deamidating assay has been developed using o-pthaldehyde (OPA) to measure the ammonia released in deamidation. This assay demonstrated that the TG2 deamidation of Vicia faba storage proteins and gliadin peptides was enhanced by presence calcium and inhibited by EDTA