Infants Infected with Respiratory Syncytial Virus Generate Potent Neutralizing Antibodies that Lack Somatic Hypermutation.

Respiratory syncytial virus (RSV) is a leading cause of infant mortality, and there are currently no licensed vaccines to protect this vulnerable population. A comprehensive understanding of infant antibody responses to natural RSV infection would facilitate vaccine development. Here, we isolated more than 450 RSV fusion glycoprotein (F)-specific antibodies from 7 RSV-infected infants and found that half of the antibodies recognized only two antigenic sites. Antibodies targeting both sites showed convergent sequence features, and structural studies revealed the molecular basis for their recognition of RSV F. A subset of antibodies targeting one of these sites displayed potent neutralizing activity despite lacking somatic mutations, and similar antibodies were detected in RSV-naive B cell repertoires, suggesting that expansion of these B cells in infants may be possible with suitably designed vaccine antigens. Collectively, our results provide fundamental insights into infant antibody responses and a framework for the rational design of age-specific RSV vaccines.

Simultaneous inhibition of MarR by salicylate and efflux pumps by curcumin sensitizes colistin resistant clinical isolates of Enterobacteriaceae.

Carbapenem resistant Enterobacteriaceae (CRE) infection has been widely treated with last resort antibiotics like colistin. Resistance to colistin has further jeopardized the situation. We have previously reported a combination of MarR inhibitor - salicylate (Sal) and an efflux pump inhibitor (BC1) that successfully restored colistin (Col) sensitivity in multidrug and colistin resistant clinical isolate of E. coli U3790. Since synthetic compounds usually fail during drug development initiatives, we attempted to replace synthetic efflux pump inhibitor (BC1) with plant metabolite as efflux pump inhibitor to restore colistin sensitivity in CRE. Screening 13 plant metabolites, we narrowed on curcumin (CUR) to effectively inhibit efflux in both colistin resistant E. coli U3790 and K. pneumoniae BC936. Combination of Col + CUR showed a remarkable reversal in colistin MIC by 128 fold and 32 fold in E. coli U3790 and K. pneumoniae BC936 respectively. Studies with knock out mutant strains of AcrAB-TolC pump components show that curcumin's efflux inhibition is partly mediated by acrB. Thus, curcumin reduced colistin MIC well below the CLSI breakpoint (<2 µg/ml). Curcumin also exhibited synergy with colistin against most of the clinical isolates of Enterobacteriaceae tested. Efficiency of Col + Sal + CUR was evident in time kill curve analysis, which displayed a 6 log and a 4 log decline in CFU/ml by 24 h in U3790 and BC936 strains respectively. In vivo intramuscular fish infection studies showed that the triad combination reduced the bacterial bioburden of E. coli U3790 by 2.6 log and that of K. pneumoniae BC936 by 1.6 log. Hence, our study shows the efficacy of inhibiting MarR by salicylate and inhibiting efflux pump with curcumin restores colistin sensitivity in colistin resistant Enterobacteriaceae in vitro and in vivo.

Off-on Fluorescent Sensor from On-off Sensor: Exploiting Silver Nanoparticles Influence on the Organic Fluorophore Fluorescence.

Turn-off fluorescence of organic fluorophore, 2-{[4-(2H-Naphtho[1,2-d][1,2,3]triazol-2-yl)-phenyl]carboxylic acid (NTPC), with metal ions (Fe(3+), Cu(2+), Pb(2+)) was converted into turn-on fluorescent sensor for biologically important Zn(2+), Cu(2+) and Fe(3+) metal ions in aqueous solution at ppb level by exploiting strong fluorescence quenching phenomena of metal nanoparticles when organic fluorophores assembled in the vicinity of metallic surface. Amino acid attached phenolic ligands (L) were used as reducing as well as functional capping agents in the synthesis of silver nanoparticles (AgNPs). The hydrogen bonding functionality of L facilitated the assembling of NTPC in the vicinity of metallic surfaces that leads to complete quenching of NTPC fluorescence. The strong and selective coordination of L with metal ions (Zn(2+), Cu(2+) and Fe(3+)) separates the NTPC from the AgNPs surface that turn-on the NTPC fluorescence. HR-TEM and absorption studies confirm the metal coordination with L and separation of NTPC from the AgNPs surface. Mn(2+) showed selective red shifting of NTPC fluorescence after 12 h with all sample. Effects of different amino acid attached phenolic ligands were explored in the metal ion sensitivity and selectivity. This approach demonstrates the multifunctional utility of metal NPs in the development of turn-on fluorescence sensor for paramagnetic heavy metal ions in aqueous solution. ᅟ

Multi-state modeling of antibody-antigen complexes with SAXS profiles and deep-learning models.

Antibodies are an established class of human therapeutics. Epitope characterization is an important part of therapeutic antibody discovery. However, structural characterization of antibody-antigen complexes remains challenging. On the one hand, X-ray crystallography or cryo-electron microscopy provide atomic resolution characterization of the epitope, but the data collection process is typically long and the success rate is low. On the other hand, computational methods for modeling antibody-antigen structures from the individual components frequently suffer from a high false positive rate, rarely resulting in a unique solution. Recent deep learning models for structure prediction are also successful in predicting protein-protein complexes. However, they do not perform well for antibody-antigen complexes. Small Angle X-ray Scattering (SAXS) is a reliable technique for rapid structural characterization of protein samples in solution albeit at low resolution. Here, we present an integrative approach for modeling antigen-antibody complexes using the antibody sequence, antigen structure, and experimentally determined SAXS profiles of the antibody, antigen, and the complex. The method models antibody structures using a novel deep-learning approach, NanoNet. The structures of the antibodies and antigens are represented using multiple 3D conformations to account for compositional and conformational heterogeneity of the protein samples that are used to collect the SAXS data. The complexes are predicted by integrating the SAXS profiles with scoring functions for protein-protein interfaces that are based on statistical potentials and antibody-specific deep-learning models. We validated the method via application to four Fab:EGFR and one Fab:PCSK9 antibody:antigen complexes with experimentally available SAXS datasets. The integrative approach returns accurate predictions (interface RMSD<4Å) in the top five predictions for four out of five complexes (respective interface RMSD values of 1.95, 2.18, 2.66 and 3.87Å), providing support for the utility of such a computational pipeline for epitope characterization during therapeutic antibody discovery.

BBD optimized antioxidants of Crotalaria candicans and its nanoconjugates, exert potent in vivo anti-biofilm effects against MRSA.

Crotalaria genus is extensively dispersed in tropical and subtropical provinces, and it is found to harbor antioxidant flavonoids. Response surface methodology-based optimization was carried out for the purpose of efficient extraction involving a suitable solvent which can maximize the yield along with higher total phenolic content and total flavonoid content (TFC). Optimization conditions for extraction of C.candicans flavonoids (CCF) based on variables such as solvent, solid-solvent ratio and extraction temperature were evaluated. The optimized conditions were found as Solvent i.e., Aqueous-ethanol (53.42%), Solid-solvent ratio (1:15.83 w/v) and temperature (44.42 °C) and resulted to obtain the TFC as 176.23 mg QRET/g C. candicans extract with the yield 27.42 mg CCF/g (C. candicans dry weight). LC-MS analysis of CCF, revealed the presence of seven major flavonoids. The antioxidant flavonoids were further used to functionalize the zero-valent silver (ZVAgF) and copper (ZVCuF) nanoparticles. The ZVAgF and ZVCuF were investigated using UV-Vis spectrophotometry, FT-IR spectroscopy and X-ray diffractometry to confirm the presence of the zero valent metals and possible functional groups which capped the elemental metal. Further transmission electron microscopy, dynamic light scattering method and zeta-potential studies were done to understand their respective structural and morphological properties. The efficacy of the as-prepared ZVAgF/ZVCuF as antibiofilm agents on Methicillin-resistant Staphylococcus aureus (MRSA) with the mechanism studies have been explored. The MRSA-colony count from the infection zebrafish (in vivo) model, portrayed a reduction of > 1.9 fold for ZVCuF and > twofold for ZVAgF, with no alteration in liver morphology when treated with ZVAgF, implying that the nanoparticles were safe and biocompatible.

Antibodies as drugs-a Keystone Symposia report.

Therapeutic antibodies have broad indications across diverse disease states, such as oncology, autoimmune diseases, and infectious diseases. New research continues to identify antibodies with therapeutic potential as well as methods to improve upon endogenous antibodies and to design antibodies de novo. On April 27-30, 2022, experts in antibody research across academia and industry met for the Keystone symposium "Antibodies as Drugs" to present the state-of-the-art in antibody therapeutics, repertoires and deep learning, bispecific antibodies, and engineering.

Metal nanoparticles functionalized with nutraceutical Kaempferitrin from edible Crotalaria juncea, exert potent antimicrobial and antibiofilm effects against Methicillin-resistant Staphylococcus aureus.

Kaempferitrin (KF), a flavonol glycoside, was isolated from the edible plant Crotalaria juncea. Optimization for the synthesis of silver (AgNPs) and copper (CuNPs) nanoparticles using C. juncea extract and kaempferitrin were attempted for the first time. A detailed study on size and stability analysis have been reported. Efficacy of KF@AgNPs and KF@CuNPs against biofilm formation and planktonic mode of growth on methicillin-resistant Staphylococcus aureus (MRSA) along with possible mechanisms has been explored. Release of Cu(II) upon prolonged treatment with KF@CuNPs in the presence of MRSA was quantified through Alizarin red test, indicating the antibacterial effect is initiated by the CuNPs itself. Time kill curve depicted both the NPs have similar kill kinetics to curtail the pathogen and imaging with Crystal violet assay, Fluorescent live dead imaging and SEM analysis revealed a 60% reduction in biofilm formation at the Sub-MIC concentration of KF@AgNPs and KF@CuNPs. Furthermore, the membrane permeability and cell surface hydrophobicity were altered in the presence of both the NPs. The colony count from the in vivo infection zebrafish model in the treatment group showed a decline of > 1.8 fold for KF@AgNPs and > two fold for KF@CuNPs. Toxicity studies did not reveal any abnormality in liver and brain enzyme levels. Liver morphology images show no severe cytological alterations when treated with KF@AgNPs and were almost similar to the normal liver. Thus, KF@AgNPs was nontoxic and caused significant reduction in biofilm formation in MRSA, also reduced bacterial bioburden in the infected zebrafish, which has the potential to be explored in higher animal models.

Sustainable valorization of meat processing wastewater with synergetic eutectic mixture based purification of R-Phycoerythrin from porphyrium cruentium.

Wastewater effluent from meat processing industries are enriched with nutrients but remain underutilized. Therefore, an efficient method was administered by employing this resource for the cultivation of Porphyreum cruentium. The cultured biomass was exposed to a one-step disruption and selective purification method using a protic deep eutectic solvent to obtain a commercially significant pigment, R-Phycoerythrin (R-PE). Six protic deep eutectic solvents (pDES) were synthesized and their thermophysical activity determined. A synergy between microwave and cavitation (MACE-DLPME) has been achieved for the effective recovery of these membrane proteins. The addition of pDES provides the selective medium for the concentration of R-PE. Optimization of the MACE-DLPME method yields 95.9% (w/w) of R-PE. Preparative size exclusion chromatography resulted in (28 µg/g) of R-PE. Further ultra-purification by anion exchange chromatography enhances the purity fold of R-PE to 125. The resulting ultrapure fraction exhibits enhanced anti-platelet activity (1.56 mg/g ascorbic acid equivalent).

Toward high-resolution homology modeling of antibody Fv regions and application to antibody-antigen docking.

High-resolution homology models are useful in structure-based protein engineering applications, especially when a crystallographic structure is unavailable. Here, we report the development and implementation of RosettaAntibody, a protocol for homology modeling of antibody variable regions. The protocol combines comparative modeling of canonical complementarity determining region (CDR) loop conformations and de novo loop modeling of CDR H3 conformation with simultaneous optimization of V(L)-V(H) rigid-body orientation and CDR backbone and side-chain conformations. The protocol was tested on a benchmark of 54 antibody crystal structures. The median root mean square deviation (rmsd) of the antigen binding pocket comprised of all the CDR residues was 1.5 A with 80% of the targets having an rmsd lower than 2.0 A. The median backbone heavy atom global rmsd of the CDR H3 loop prediction was 1.6, 1.9, 2.4, 3.1, and 6.0 A for very short (4-6 residues), short (7-9), medium (10-11), long (12-14) and very long (17-22) loops, respectively. When the set of ten top-scoring antibody homology models are used in local ensemble docking to antigen, a moderate-to-high accuracy docking prediction was achieved in seven of fifteen targets. This success in computational docking with high-resolution homology models is encouraging, but challenges still remain in modeling antibody structures for sequences with long H3 loops. This first large-scale antibody-antigen docking study using homology models reveals the level of "functional accuracy" of these structural models toward protein engineering applications.

Deamidation and isomerization liability analysis of 131 clinical-stage antibodies.

Contemporary in vivo and in vitro discovery platform technologies greatly increase the odds of identifying high-affinity monoclonal antibodies (mAbs) towards essentially any desired biologically relevant epitope. Lagging discovery throughput is the ability to select for highly developable mAbs with drug-like properties early in the process. Upstream consideration of developability metrics should reduce the frequency of failures in later development stages. As the field moves towards incorporating biophysical screening assays in parallel to discovery processes, similar approaches should also be used to ensure robust chemical stability. Optimization of chemical stability in the early stages of discovery has the potential to reduce complications in formulation development and improve the potential for successful liquid formulations. However, at present, our knowledge of the chemical stability characteristics of clinical-stage therapeutic mAbs is fragmented and lacks comprehensive comparative assessment. To address this knowledge gap, we produced 131 mAbs with amino acid sequences corresponding to the variable regions of clinical-stage mAbs, subjected these to low and high pH stresses and identified the resulting modifications at amino acid-level resolution via tryptic peptide mapping. Among this large set of mAbs, relatively high frequencies of asparagine deamidation events were observed in CDRs H2 and L1, while CDRs H3, H2 and L1 contained relatively high frequencies of instances of aspartate isomerization.

Modeling the structure of mAb 14B7 bound to the anthrax protective antigen.

The anthrax protective antigen (PA) is a key component of the tripartite anthrax toxin. Monoclonal antibody (mAb) 14B7 and its engineered, affinity-matured variants have been shown to be effective in blocking PA binding to cellular receptors and mitigating anthrax toxicity. Here, we perform computational structural modeling of the mAb 14B7-PA interaction. Our objectives are to determine the structure of the 14B7-PA complex, to deduce a structural explanation for the affinity maturation from the docking models, and to study the effect of inaccuracies in the antibody homology model on docking. We used the RosettaDock program to dock PA with the mAb 14B7 crystal structure or homology model. Our simulations generate two distinct binding orientations consistent with experimental residue mutations that diminish 14B7-PA binding. Furthermore, the models suggest new site-directed mutations to positively identify one of these two solutions as the correct 14B7-PA docking orientation. The models indicate that PA regions 648-660 and 712-720 may be important for 14B7 binding in addition to the known PA epitope, and the binding interfaces are similar to that seen in the PA complex with cellular receptor CMG2. Antibody residues involved in affinity maturation do not contact the antigen in the docking models, suggesting that affinity maturation in the 14B7 family does not result from direct enhancements of antibody-antigen contacts. Docking the homology model produces low-resolution representations of the crystal structure docking orientations, but homology model docking is frustrated by antibody H3 loop conformation errors. This work demonstrates the usefulness and limitations of computational structure prediction for the development of antibody therapeutics, and reemphasizes the need for flexible backbone docking algorithms to achieve high-resolution docking using homology models.

Structural model of the mAb 806-EGFR complex using computational docking followed by computational and experimental mutagenesis.

In this work, we combined computational protein-protein docking with computational and experimental mutagenesis to predict the structure of the complex formed by monoclonal antibody 806 (mAb 806) and the epidermal growth factor receptor (EGFR). We docked mAb 806, an antitumor antibody, to its epitope of EGFR residues 287-302. Potential mAb 806-EGFR orientations were generated, and computational mutagenesis was used to filter them according to their agreement with experimental mutagenesis data. Further computational mutagenesis suggested additional mutations, which were tested to arrive at a final structure that was most consistent with experimental mutagenesis data. We propose that this is the EGFR-mAb 806 structure, in which mAb 806 binds to an untethered form of the receptor, consistent with published experimental results. The steric hindrance created by the antibody near the EGFR dimer interface interferes with receptor dimerization, and we postulate this as the structural origin for the antitumor effect of mAb 806.

Incorporating biochemical information and backbone flexibility in RosettaDock for CAPRI rounds 6-12.

In CAPRI rounds 6-12, RosettaDock successfully predicted 2 of 5 unbound-unbound targets to medium accuracy. Improvement over the previous method was achieved with computational mutagenesis to select decoys that match the energetics of experimentally determined hot spots. In the case of Target 21, Orc1/Sir1, this resulted in a successful docking prediction where RosettaDock alone or with simple site constraints failed. Experimental information also helped limit the interacting region of TolB/Pal, producing a successful prediction of Target 26. In addition, we docked multiple loop conformations for Target 20, and we developed a novel flexible docking algorithm to simultaneously optimize backbone conformation and rigid-body orientation to generate a wide diversity of conformations for Target 24. Continued challenges included docking of homology targets that differ substantially from their template (sequence identity <50%) and accounting for large conformational changes upon binding. Despite a larger number of unbound-unbound and homology model binding targets, Rounds 6-12 reinforced that RosettaDock is a powerful algorithm for predicting bound complex structures, especially when combined with experimental data.

Broad epitope coverage of a human in vitro antibody library.

Successful discovery of therapeutic antibodies hinges on the identification of appropriate affinity binders targeting a diversity of molecular epitopes presented by the antigen. Antibody campaigns that yield such broad "epitope coverage" increase the likelihood of identifying candidates with the desired biological functions. Accordingly, epitope binning assays are employed in the early discovery stages to partition antibodies into epitope families or "bins" and prioritize leads for further characterization and optimization. The collaborative program described here, which used hen egg white lysozyme (HEL) as a model antigen, combined 3 key capabilities: 1) access to a diverse panel of antibodies selected from a human in vitro antibody library; 2) application of state-of-the-art high-throughput epitope binning; and 3) analysis and interpretation of the epitope binning data with reference to an exhaustive set of published antibody:HEL co-crystal structures. Binning experiments on a large merged panel of antibodies containing clones from the library and the literature revealed that the inferred epitopes for the library clones overlapped with, and extended beyond, the known structural epitopes. Our analysis revealed that nearly the entire solvent-exposed surface of HEL is antigenic, as has been proposed for protein antigens in general. The data further demonstrated that synthetic antibody repertoires provide as wide epitope coverage as those obtained from animal immunizations. The work highlights molecular insights contributed by increasingly higher-throughput binning methods and their broad utility to guide the discovery of therapeutic antibodies representing a diverse set of functional epitopes.

CAPRI rounds 3-5 reveal promising successes and future challenges for RosettaDock.

CAPRI Rounds 3, 4, and 5 are the first public test of the published RosettaDock algorithm. The targets cover a wide range of sizes and shapes. For most targets, published biological information indicated the region of the binding site on at least one docking partner. The RosettaDock algorithm produced high accuracy predictions for three targets, medium-accuracy predictions for two targets, and an acceptable prediction for one target. RosettaDock predicted all five targets with less than 450 residues to high or medium accuracy, but it predicted only one of seven targets with above 450 residues to acceptable accuracy. RosettaDock's high-accuracy predictions for small to moderately large targets reveal the predictive power and fidelity of the algorithm, especially the high-resolution refinement and scoring protocol. In addition, RosettaDock can predict complexes from at least one homology-modeled docking partner with comparable accuracy to unbound cases of similar size. Larger targets present a more intensive sampling problem, and some large targets present repulsive barriers to entering the binding site. Ongoing improvements to RosettaDock's low-resolution search may alleviate this problem. This first public test suggests that RosettaDock can be useful in a significant range of applications in biochemistry and cell biology.

Rheology and microscopic topology of entangled polymeric liquids.

The viscoelastic properties of high molecular weight polymeric liquids are dominated by topological constraints on a molecular scale. In a manner similar to that of entangled ropes, polymer chains can slide past but not through each other. Tube models of polymer dynamics and rheology are based on the idea that entanglements confine a chain to small fluctuations around a primitive path that follows the coarse-grained chain contour. Here we provide a microscopic foundation for these highly successful phenomenological models. We analyze the topological state of polymeric liquids in terms of primitive paths and obtain parameter-free, quantitative predictions for the plateau modulus, which agree with experiment for all major classes of synthetic polymers.