Antigenic Structure Research Articles

Current basic research in normothermic machine perfusion.

Background Normothermic machine perfusion (NMP) is gradually being introduced into clinical transplantation to improve the quality of organs and increase utilisation. This review details current understanding of the underlying mechanistic effects of NMP in the heart, lung, liver and kidney. It also considers recent advancements to extend the perfusion interval in these organs and the use of NMP to introduce novel therapeutic interventions, with a focus on organ modulation. Summary The re-establishment of circulation during NMP leads to the upregulation of inflammatory and immune mediators, similar to an ischaemia reperfusion injury (IRI) response. The level of injury is determined by the condition of the organ, but inflammation may also be exacerbated by the passenger leucocytes that emerge from the organ during perfusion. There is evidence that damaged organs can recover and that prolonged NMP may be advantageous. In the liver, successful 7 day NMP has been achieved. The delivery of therapeutic agents to an organ can aid repair and be used to modify the organ to reduce immunogenicity or change the structure of the blood group antigens to create a universal donor blood group organ. Key messages The application of NMP in organ transplantation is a growing area of research and is increasingly being used in the clinic. In the future NMP may offer the opportunity to change practice. If organs can be preserved for days on an NMP system, transplantation may become an elective rather than an emergency procedure. The ability to introduce therapies during NMP is an effective way to treat an organ and avoid the complexity of treating the recipient.

Hydrolysates of mare's milk proteins. Immunochemical and physico-chemical characteristics

In recent years, the attention of specialists has been attracted by a significant increase in allergic diseases, especially among children. Enzymatic hydrolysis with the participation of peptidases is considered the most effective measure to reduce the allergenicity of milk proteins. The study of the features of protein proteolysis by various enzymes, aimed at establishing optimal process parameters, is the subject of research in the production of hydrolysates with specified properties: a certain peptide and amino acid profile, reduced antigenic properties. At the same time, for a correct preclinical assessment of the safety and potential effectiveness of specialized food products, it is not enough only to determine the molecular weight distribution of peptide fractions in the composition. A necessary additional and informative indicator of reducing the potential allergenicity of the hydrolysate is the degree of preservation of the antigenic properties of the initial protein (residual antigenicity), determined by immunochemical methods. The preparation and subsequent comprehensive assessment of enzymatic hydrolysates of mare's milk proteins is of considerable interest, since, according to the results of clinical studies, it was suggested that upon allergy to cow's milk proteins mare's milk can be considered hypoallergenic. The purpose of this work was to obtain enzymatic hydrolysates of mare's milk proteins using domestic enzymes and their further physico-chemical and immunochemical characteristics. The object of the study was mare's milk protein obtained from skimmed mare's milk powder as a protein substrate. Two samples of enzymes from various manufacturers of the Russian Federation were used in the work. The results of the conducted studies show that the peptide profiles of hydrolysates vary greatly depending on the enzyme used, however, the multiplicity of antigenicity reduction practically does not depend on the nature of the enzyme, and does not depend on an increase in the enzyme/substrate ratio. The peptide profile and the multiplicity of reducing the antigenicity of hydrolysates of mare's milk proteins are influenced by ultrafiltration treatment of the obtained hydrolysates, which allows reducing the content of antigenic structures in the final product by several orders of magnitude.

Vaccine-induced human monoclonal antibodies to PfRH5 show broadly neutralizing activity against P. falciparum clinical isolates

Vaccines to the Plasmodium falciparum reticulocyte binding-like protein homologue 5 (PfRH5) target the blood-stage of the parasite life cycle. PfRH5 has the potential to trigger the production of strain-transcendent antibodies and has proven its efficacy both in pre-clinical and early clinical studies. Vaccine-induced monoclonal antibodies (mAbs) to PfRH5 showed promising outcomes against cultured P. falciparum laboratory strains from distinct geographic areas. Here, we assessed the functional impact of vaccine-induced anti-PfRH5 mAbs on more genetically diverse P. falciparum clinical isolates. We used mAbs previously isolated from single B cells of UK adult PfRH5 vaccinees and used ex-vivo growth inhibition activity (GIA) assays to assess their efficacy against P. falciparum clinical isolates. Next-generation sequencing (NGS) was used to assess the breadth of genetic diversity in P. falciparum clinical isolates and to infer the genotype/phenotype relationship involved in antibody susceptibility. We showed a dose-dependent inhibition of clinical isolates with three main GIA groups: high, medium and low. Except for one isolate, our data show no significant differences in the mAb GIA profile between P. falciparum clinical isolates and the 3D7 reference strain, which harbors the vaccine allele. We also observed an additive relationship for mAb combinations, whereby the combination of GIA-low and GIA-medium antibodies resulted in increased GIA, having important implications for the contribution of specific clones within polyclonal IgG responses. While our NGS analysis showed the occurrence of novel mutations in the pfrh5 gene, these mutations were predicted to have little or no functional impact on the antigen structure or recognition by known mAbs. Our present findings complement earlier reports on the strain transcendent potential of anti-PfRH5 mAbs and constitute, to our knowledge, the first report on the susceptibility of P. falciparum clinical isolates from natural infections to vaccine-induced human mAbs to PfRH5.

Discovery, recognized antigenic structures, and evolution of cross-serotype broadly neutralizing antibodies from porcine B-cell repertoires against foot-and-mouth disease virus.

It is a great challenge to isolate the broadly neutralizing antibodies (bnAbs) against foot-and-mouth disease virus (FMDV) due to its existence as seven distinct serotypes without cross-protection. Here, by vaccination of pig with FMDV serotype O and A whole virus antigens, we obtained 10 bnAbs against serotypes O, A and/or Asia1 by dissecting 216 common clonotypes of two serotype O and A specific porcine B-cell receptor (BCR) gene repertoires containing total 12720 B cell clones, indicating the induction of cross-serotype bnAbs after sequential vaccination with serotypes O and A antigens. The majority of porcine bnAbs (9/10) were derived from terminally differentiated B cells of different clonal lineages, which convergently targeted the conserved "RGDL" motif on structural protein VP1 of FMDV by mimicking receptor recognition to inhibit viral attachment to cells. Cryo-EM complex structures revealed that the other bnAb pOA-2 specifically targets a novel inter-pentamer antigen structure surrounding the viral three-fold axis, with a highly conserved determinant at residue 68 on VP2. This unique binding pattern enabled cross-serotype neutralization by destabilizing the viral particle. The evolutionary analysis of pOA-2 demonstrated its origin from an intermediate B-cell, emphasizing the crucial role of somatic hypermutations (SHMs) in balancing the breadth and potency of neutralization. However, excessive SHMs may deviate from the trajectory of broad neutralization. This study provides a strategy to uncover bnAbs against highly mutable pathogens and the cross-serotype antigenic structures to explore broadly protective FMDV vaccine.

Pertussis is still not a completely controlled infection

The lecture focuses on pertussis, an infection managed by specific preventive measures, which continues to threaten both child and maternal health, as well as overall healthcare system. Despite high vaccination rates, pertussis remains an “under-controlled” infection and a significant contributor to childhood morbidity and mortality. Moreover, in many countries, the incidence of pertussis is clearly rising among both children and adults, with a notable proportion of cases occurring in vaccinated individuals. This increase may be associated with changes in the antigenic structure of the pathogen, the limited duration of post-vaccination immunity, reduced vaccination coverage, and the use of more sensitive laboratory diagnostic methods. The lecture addresses modern aspects of the etiopathogenesis, epidemiology, clinical presentation, diagnosis, treatment, and prevention of pertussis. Given the rising incidence of this infection in Russia and several other countries in 2023, the information presented will be especially valuable for practitioners, particularly family doctors.

MVSF-AB: Accurate antibody-antigen binding affinity prediction via multi-view sequence feature learning.

Predicting the binding affinity between antigens and antibodies accurately is crucial for assessing therapeutic antibody effectiveness and enhancing antibody engineering and vaccine design. Traditional machine learning methods have been widely used for this purpose, relying on interfacial amino acids' structural information. Nevertheless, due to technological limitations and high costs of acquiring structural data, the structures of most antigens and antibodies are unknown, and sequence-based methods have gained attention. Existing sequence-based approaches designed for protein-protein affinity prediction exhibit a significant drop in performance when applied directly to antibody-antigen affinity prediction due to imbalanced training data and lacking design in the model framework specifically for antibody-antigen, hindering the learning of key features of antibodies and antigens. Therefore, we propose MVSF-AB, a Multi-View Sequence Feature learning for accurate Antibody-antigen Binding affinity prediction. MVSF-AB designs a multi-view method that fuses semantic features and residue features to fully utilize the sequence information of antibody-antigen and predicts the binding affinity. Experimental results demonstrate that MVSF-AB outperforms existing approaches in predicting unobserved natural antibody-antigen affinity and maintains its effectiveness when faced with mutant strains of antibodies. Datasets we used and source code are available on our public GitHub repository https://github.com/TAI-Medical-Lab/MVSF-AB.

Generation and epitope mapping of novel neutralizing monoclonal antibodies against glycoprotein E2 of CSFV

Classical swine fever virus (CSFV) is a highly contagious and economically important pathogen threatening pig industry worldwide, the envelope glycoprotein E2 of CSFV is the dominant antigen inducing strong antiviral neutralizing immunity. In this study, 7 monoclonal antibodies (mAbs) with neutralizing potency were generated using E2 protein of CSFV Shimen strain (SM) expressed by eukaryotic cells. Their reactivity with 116 CSFV strains in cell cultures and E2 proteins of 10 subgenotypes in western blots showed different CSFV spectrums they recognized. Of them, three (HCL-001, HCL-005 and HCL-010) reacted with all CSFV subgenotypes, while HCL-014 and HCL-002 reacted with most CSFV strains, except for some variants in genotype 2.3. In contrast, mAb HCL-009 reacted only with a few subgenotype 1.1 strains including SM, field strains and some vaccine strains. Interestingly, mAb HCL-018 reacted only with SM and field subgenotype 1.1 strains, not with any vaccine strains. Further epitope mapping using chimeric and site-directed mutated E2 proteins showed that HCL-001, HCL-005 and HCL-010 recognized a conservative epitope motif 143SPT145,L147, and HCL-002 recognized a conformational epitope with key aa motifs of 95GDD97,157RX(D/E)K(R)XFXXR164. HCL-014 recognized a new conservative epitope with key aa motifs of 41D,58XNVVXRR64. HCL-009 and HCL-018 recognized the epitope with key aa motifs of 36D,40ND41,45KXI47 and 69LHXGXLLT76, respectively. Taken together, present study has provided not only new insights into the antigenic structure of E2 protein, but also key reagents for antigenic characterization of CSFV strains and development of antibody assay for evaluation of the vaccination efficacy.

Towards the accurate modelling of antibody-antigen complexes from sequence using machine learning and information-driven docking.

Antibody-antigen complex modelling is an important step in computational workflows for therapeutic antibody design. While experimentally determined structures of both antibody and the cognate antigen are often not available, recent advances in machine learning-driven protein modelling have enabled accurate prediction of both antibody and antigen structures. Here, we analyse the ability of protein-protein docking tools to use machine learning generated input structures for information-driven docking. In an information-driven scenario, we find that HADDOCK can generate accurate models of antibody-antigen complexes using an ensemble of antibody structures generated by machine learning tools and AlphaFold2 predicted antigen structures. Targeted docking using knowledge of the complementary determining regions on the antibody and some information about the targeted epitope allows the generation of high-quality models of the complex with reduced sampling, resulting in a computationally cheap protocol that outperforms the ZDOCK baseline. The source code of HADDOCK3 is freely available at github.com/haddocking/haddock3. The code to generate and analyse the data is available at github.com/haddocking/ai-antibodies. The full runs, including docking models from all modules of a workflow have been deposited in our lab collection (data.sbgrid.org/labs/32/1139) at the SBGRID data repository.

The Autonomous Fusion Activity of Human Cytomegalovirus Glycoprotein B Is Regulated by Its Carboxy-Terminal Domain.

The human cytomegalovirus (HCMV) glycoprotein B (gB) is the viral fusogen required for entry into cells and for direct cell-to-cell spread of the virus. We have previously demonstrated that the exchange of the carboxy-terminal domain (CTD) of gB for the CTD of the structurally related fusion protein G of the vesicular stomatitis virus (VSV-G) resulted in an intrinsically fusion-active gB variant (gB/VSV-G). In this present study, we employed a dual split protein (DSP)-based cell fusion assay to further characterize the determinants of fusion activity in the CTD of gB. We generated a comprehensive library of gB CTD truncation mutants and identified two mutants, gB-787 and gB-807, which were fusion-competent and induced the formation of multinucleated cell syncytia in the absence of other HCMV proteins. Structural modeling coupled with site-directed mutagenesis revealed that gB fusion activity is primarily mediated by the CTD helix 2, and secondarily by the recruitment of cellular SH2/WW-domain-containing proteins. The fusion activity of gB-807 was inhibited by gB-specific monoclonal antibodies (MAbs) targeting the antigenic domains AD-1 to AD-5 within the ectodomain and not restricted to MAbs directed against AD-4 and AD-5 as observed for gB/VSV-G. This finding suggested a differential regulation of the fusion-active conformational state of both gB variants. Collectively, our findings underscore a pivotal role of the CTD in regulating the fusogenicity of HCMV gB, with important implications for understanding the conformations of gB that facilitate membrane fusion, including antigenic structures that could be targeted by antibodies to block this essential step in HCMV infection.

Guiding Diffusion Models for Antibody Sequence and Structure Co-design with Developability Properties

Recent advances in deep generative methods have allowed antibody sequence and structure co-design. This study addresses the challenge of tailoring the highly variable complementarity-determining regions (CDRs) in antibodies to fulfill developability requirements. We introduce a guidance approach that integrates property information into the antibody design process using diffusion probabilistic models. This approach allows us to simultaneously design CDRs conditioned on antigen structures while considering critical properties like solubility and folding stability. Our property-guided diffusion model offers versatility by accommodating diverse property constraints, presenting a promising avenue for computational antibody design in therapeutic applications. Published by the American Physical Society 2024

EpiScan: accurate high-throughput mapping of antibody-specific epitopes using sequence information

The identification of antibody-specific epitopes on virus proteins is crucial for vaccine development and drug design. Nonetheless, traditional wet-lab approaches for the identification of epitopes are both costly and labor-intensive, underscoring the need for the development of efficient and cost-effective computational tools. Here, EpiScan, an attention-based deep learning framework for predicting antibody-specific epitopes, is presented. EpiScan adopts a multi-input and single-output strategy by designing independent blocks for different parts of antibodies, including variable heavy chain (VH), variable light chain (VL), complementary determining regions (CDRs), and framework regions (FRs). The block predictions are weighted and integrated for the prediction of potential epitopes. Using multiple experimental data samples, we show that EpiScan, which only uses antibody sequence information, can accurately map epitopes on specific antigen structures. The antibody-specific epitopes on the receptor binding domain (RBD) of SARS coronavirus 2 (SARS-CoV-2) were located by EpiScan, and the potentially valuable vaccine epitope was identified. EpiScan can expedite the epitope mapping process for high-throughput antibody sequencing data, supporting vaccine design and drug development. Availability: For the convenience of related wet-experimental researchers, the source code and web server of EpiScan are publicly available at https://github.com/gzBiomedical/EpiScan.

The Role of Metal Nanoparticles in the Pathogenesis of Stone Formation.

The process of stone formation in the human body remains incompletely understood, which requires clinical and laboratory studies and the formulation of a new endogenous, nanotechnological concept of the mechanism of origin and formation of crystallization centers. Previously, the mechanism of sialolithiasis was considered a congenital disease associated with the pathology of the ducts in the structure of the glands themselves. To date, such morphological changes of congenital nature can be considered from the position of the intrauterine formation of endogenous bacterial infections complicated by the migration of antigenic structures initiating the formation of crystallization centers. The present work is devoted to the study of the morphology and composition of stones obtained as a result of surgical interventions for sialolithiasis. Presumably, nanoparticles of metals and other chemical compounds can be structural components of crystallization centers or incorporated into the conditions of chronic endogenous inflammation and the composition of antigenic structures, in complexes with protein and bacterial components. X-ray microtomography, X-ray fluorescence analysis, scanning transmission electron microscopy and microanalysis, mass spectrometry, and Raman spectroscopy were used to study the pathogenesis of stone formation. Immunoglobulins (Igs) of classes A and G, as well as nanoparticles of metals Pb, Fe, Cr, and Mo, were found in the internal structure of the stones. The complex of antigenic structures was an ovoid calcified layered matrix of polyvid microbial biofilms, with the inclusion of metal nanoparticles and chemical elements, as well as immunoglobulins. The obtained results of clinical and laboratory studies allow us to broaden the view on the pathogenesis of stone formation and suggest that the occurrence of the calcification of antigenic structures may be associated with the formation of IgG4-associated disease.

Dissecting the Enterococcal Polysaccharide Antigen (EPA) structure to explore innate immune evasion and phage specificity

Streptococci, Lactococci and Enterococci all produce L-rhamnose-containing cell wall polysaccharides which define Lancefield serotypes and represent promising candidates for the design of glycoconjugate vaccines. The L-rhamnose containing Enterococcal Polysaccharide Antigen (EPA), produced by the opportunistic pathogen Enterococcus faecalis, plays a critical role in normal growth, division, biofilm formation, antimicrobial resistance, phage susceptibility, and innate immune evasion. Despite the critical role of this polymer in E. faecalis physiology and host-pathogen interactions, little information is available on its structure and biosynthesis. Here, using an NMR approach, we elucidate the structure of EPA and propose a model for biosynthesis. We report the structure of the EPA-peptidoglycan linkage unit and reveal an unprecedented complexity of the EPA rhamnose backbone and decoration subunits. Finally, we explore the impact of several EPA structural modifications on innate immune evasion and recognition by bacteriophages. This work represents a first step towards the functional characterisation of EPA and the rational design of therapeutic strategies against a group of important pathogens.

A comparison of antibody-antigen complex sequence-to-structure prediction methods and their systematic biases.

The ability to accurately predict antibody-antigen complex structures from their sequences could greatly advance our understanding of the immune system and would aid in the development of novel antibody therapeutics. There have been considerable recent advancements in predicting protein-protein interactions (PPIs) fueled by progress in machine learning (ML). To understand the current state of the field, we compare six representative methods for predicting antibody-antigen complexes from sequence, including two deep learning approaches trained to predict PPIs in general (AlphaFold-Multimer and RoseTTAFold), two composite methods that initially predict antibody and antigen structures separately and dock them (using antibody-mode ClusPro), local refinement in Rosetta (SnugDock) of globally docked poses from ClusPro, and a pipeline combining homology modeling with rigid-body docking informed by ML-based epitope and paratope prediction (AbAdapt). We find that AlphaFold-Multimer outperformed other methods, although the absolute performance leaves considerable room for improvement. AlphaFold-Multimer models of lower quality display significant structural biases at the level of tertiary motifs (TERMs) toward having fewer structural matches in non-antibody-containing structures from the Protein Data Bank (PDB). Specifically, better models exhibit more common PDB-like TERMs at the antibody-antigen interface than worse ones. Importantly, the clear relationship between performance and the commonness of interfacial TERMs suggests that the scarcity of interfacial geometry data in the structural database may currently limit the application of ML to the prediction of antibody-antigen interactions.

Computational Methods to Predict Conformational B-Cell Epitopes.

Accurate computational prediction of B-cell epitopes can greatly enhance biomedical research and rapidly advance efforts to develop therapeutics, monoclonal antibodies, vaccines, and immunodiagnostic reagents. Previous research efforts have primarily focused on the development of computational methods to predict linear epitopes rather than conformational epitopes; however, the latter is much more biologically predominant. Several conformational B-cell epitope prediction methods have recently been published, but their predictive performances are weak. Here, we present a review of the latest computational methods and assess their performances on a diverse test set of 29 non-redundant unbound antigen structures. Our results demonstrate that ISPIPab performs better than most methods and compares favorably with other recent antigen-specific methods. Finally, we suggest new strategies and opportunities to improve computational predictions of conformational B-cell epitopes.

ETIOPATHOGENETIC REASONING OF URETHRAL MICROBIOTA REHABILITATION IN PATIENTS WITH ACUTE INFECTIOUS URETHRITIS

The microbiota of the male genitourinary tract is a complex dynamic system that has not been sufficiently studied. Unlike the microbiome of the female urethral mucosa, which is constantly changing, the taxonomic composition and population level of the male urethral microbiome is more stable and independent of age. The aim of the study. To improve the results of treatment of patients with inflammatory processes of the urethra by determining the taxonomic composition, population level and microscopic indicators of the "macroorganism-microbiome" ecosystem of the microbiota of the urethra in men with acute urethritis.Material and methods. The taxonomic composition and population level of the first portion of urine of 69 sexually mature men (average age 34.8±7.14 years) with acute infectious (nonspecific) urethritis were investigated. Isolation of conditionally pathogenic bacteria was carried out by the bacteriological method using optimal nutrient media, their pH, temperature and cultivation time for each taxon. The identification of isolated pure cultures was carried out according to morphological, tinctorial, cultural, biochemical properties, as well as signs of pathogenicity and antigenic structure. To determine the mechanisms of colonization of the mucous membrane of the urethra by conditionally pathogenic microorganisms, the microecological method was used.Research results. According to the taxonomic composition and the level of microecological indicators of the "macroorganism-microbiome" ecosystem of the urethra microbiota (Margalef's species richness index, Whittaker's species diversity index, and Simpson's and Berger-Parker's species dominance indices), vulgar (common), hemolytic, and enteropathogenic Escherichia coli, coagulase-positive staphylococcus. The leading role in the formation of urethritis is played by ordinary enterobacteria - E. coli, a slightly smaller etiological role in the formation of urethritis in men belongs to S. aureus (less by 17.83%), E. coli Hly+ (less by 28.35%), enteropathogenic Escherichia coli (by 83.12%). Other microorganisms have a minimal etiological role. Conclusions. Acute urethritis in men is a polyetiological disease. Enterobacteria E. coli, E. coli Hly+, enteropathogenic Escherichia coli, K. pneumoniae, S. aureus, S. epidermidis, S. viridans are involved in the formation of the inflammatory process of the urethra. The leading causative agents of acute urethritis in men are E. coli, S. aureus, E. coli Hly+, enteropathogenic escherichia, which belong to uropathogenic escherichia.

Structure, biosynthesis and regulation of the T1 antigen, a phase-variable surface polysaccharide conserved in many Salmonella serovars

The bacterial genus Salmonella includes diverse isolates with multiple variations in the structure of the main polysaccharide component (O antigen) of membrane lipopolysaccharides. In addition, some isolates produce a transient (T) antigen, such as the T1 polysaccharide identified in the 1960s in an isolate of Salmonella enterica Paratyphi B. The structure and biosynthesis of the T1 antigen have remained enigmatic. Here, we use biophysical, biochemical and genetic methods to show that the T1 antigen is a complex linear glycan containing tandem homopolymeric domains of galactofuranose and ribofuranose, linked to lipid A–core, like a typical O antigen. T1 is a phase-variable antigen, regulated by recombinational inversion of the promoter upstream of the T1 genetic locus through a mechanism not observed for other bacterial O antigens. The T1 locus is conserved across many Salmonella isolates, but is mutated or absent in most typhoidal serovars and in serovar Enteritidis.

Different roles of the heterodimer architecture of galectin-4 in selective recognition of oligosaccharides and lipopolysaccharides having ABH antigens

The dimeric architecture of tandem-repeat type galectins, such as galectin-4 (Gal-4), modulates their biological activities, although the underlying molecular mechanisms have remained elusive. Emerging evidence show that tandem-repeat galectins play an important role in innate immunity by recognizing carbohydrate antigens present on the surface of certain pathogens, which very often mimic the structures of the human self-glycan antigens. Herein, we have analyzed the binding preferences of the C-domain of Gal-4 (Gal-4C) toward the ABH-carbohydrate histo-blood antigens with different core presentations and their recognition features have been rationalized by using a combined experimental approach including NMR, solid-phase and hemagglutination assays, and molecular modeling. The data show that Gal-4C prefers A over B antigens (two-fold in affinity), contrary to the N-domain (Gal-4N), although both domains share the same preference for the type-6 presentations. The behavior of the full-length Gal-4 (Gal-4FL) tandem-repeat form has been additionally scrutinized. Isothermal titration calorimetry and NMR data demonstrate that both domains within full-length Gal-4 bind to the histo-blood antigens independently of each other, with no communication between them. In this context, the heterodimeric architecture does not play any major role, apart from the complementary A and B antigen binding preferences. However, upon binding to a bacterial lipopolysaccharide containing a multivalent version of an H-antigen mimetic as O-antigen, the significance of the galectin architecture was revealed. Indeed, our data point to the linker peptide domain and the F-face of the C-domain as key elements that provide Gal-4 with the ability to cross-link multivalent ligands, beyond the glycan binding capacity of the dimer.

RAbDesFlow: a novel workflow for computational recombinant antibody design for healthcare engineering.

Recombinant antibodies (rAbs) have emerged as a promising solution to tackle antigen specificity, enhancement of immunogenic potential and versatile functionalization to treat human diseases. The development of single chain variable fragments has helped accelerate treatment in cancers and viral infections, due to their favorable pharmacokinetics and human compatibility. However, designing rAbs is traditionally viewed as a genetic engineering problem, with phage display and cell free systems playing a major role in sequence selection for gene synthesis. The process of antibody engineering involves complex and time-consuming laboratory techniques, which demand substantial resources and expertise. The success rate of obtaining desired antibody candidates through experimental approaches can be modest, necessitating iterative cycles of selection and optimization. With ongoing advancements in technology, in silico design of diverse antibody libraries, screening and identification of potential candidates for in vitro validation can be accelerated. To meet this need, we have developed rAbDesFlow, a unified computational workflow for recombinant antibody engineering with open-source programs and tools for ease of implementation. The workflow encompasses five computational modules to perform antigen selection, antibody library generation, antigen and antibody structure modeling, antigen-antibody interaction modeling, structure analysis, and consensus ranking of potential antibody sequences for synthesis and experimental validation. The proposed workflow has been demonstrated through design of rAbs for the ovarian cancer antigen Mucin-16 (CA-125). This approach can serve as a blueprint for designing similar engineered molecules targeting other biomarkers, allowing for a simplified adaptation to different cancer types or disease-specific antigens.

Apoplast-Extraction Based Method to Improve the Purity of Plant Produced Recombinant Protein.

Plants are a newly developing eukaryotic expression system being explored to produce therapeutic proteins. Purification of recombinant proteins from plants is one of the most critical steps in the production process. Typically, proteins were purified from total soluble proteins (TSP), and the presence of miscellaneous intracellular proteins and cytochromes poses challenges for subsequent protein purification steps. Moreover, most therapeutic proteins like antigens and antibodies are secreted to obtain proper glycosylation, and the presence of incompletely modified proteins leads to inconsistent antigen or antibody structures. This work introduces a more effective method to obtain highly purified recombinant proteins from the plant apoplastic space. The recombinant Green fluorescent protein (GFP) is engineered to be secreted into the apoplast of Nicotiana benthamiana and is then extracted using an infiltration-centrifugation method. The GFP-His from the extracted apoplast is then purified by nickel affinity chromatography. In contrast to the traditional methods from TSP, purification from the apoplast produces highly purified recombinant proteins. This represents an important technological improvement for plant production systems.