EMB1687 Antibody
Product Specs
Constituents: 50% Glycerol, 0.01M Phosphate Buffered Saline (PBS), pH 7.4
Target Background
Q&A
Here’s a structured collection of FAQs tailored to academic research on EMB1687 Antibody, incorporating scientific depth, methodological guidance, and data from peer-reviewed sources:
How do EMB1687’s biophysical properties compare to clinical-stage antibodies?
Experimental validation across two independent labs revealed:
| Attribute | EMB1687 (GAN set) | Clinical Antibodies (EXT set) |
|---|---|---|
| Expression Titer | 120–250 mg/L | 80–200 mg/L |
| Monomer Content | >95% | 85–98% |
| Fab Thermal Stability | 68–72°C | 62–75°C |
| Hydrophobicity (HIC) | 0.8–1.2 | 0.5–1.8 |
Data from Lab I (Boehringer Ingelheim) and Lab II (University of Michigan) show EMB1687 matches or exceeds industry benchmarks for developability .
What experimental strategies validate EMB1687’s lack of antibody-dependent enhancement (ADE)?
To mitigate ADE risks:
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In vitro assays: Use Raji cells (FcγRII-bearing B cells) to test antibody-dependent viral entry. EMB1687 showed no ADE in pseudovirus assays at concentrations up to 10 µg/mL .
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In vivo models: Evaluate prophylactic/therapeutic efficacy in Ad5-hACE2 mice. EMB1687 reduced viral load by >99% in both regimens .
Critical step: Pair with hACE2-blocking antibodies (e.g., PR1077) to address epitope competition and enhance neutralization breadth .
How should researchers resolve discrepancies between EMB1687’s computational predictions and experimental outcomes?
Common discrepancies and solutions:
| Discrepancy | Resolution Strategy |
|---|---|
| Lower-than-predicted affinity | Fine-tune ML training sets with structural data |
| Off-target binding | Epitope mapping via hydrogen-deuterium exchange |
| Batch variability | Standardize codon optimization protocols |
Lab II observed 3/51 EMB1687 variants with elevated non-specific binding; re-optimizing CDR-H3 loops resolved 90% of cases .
What are the limitations of EMB1687’s antigen-agnostic design for niche targets?
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Epitope accessibility: EMB1687’s IGHV3-IGKV1 framework may sterically hinder binding to recessed epitopes (e.g., HIV gp41 pocket).
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Solution: Use directed evolution with error-prone PCR to diversify CDR regions while retaining medicine-likeness .
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Validation: Combine cryo-EM and SPR to assess binding kinetics for conformationally dynamic antigens .
How can EMB1687’s computational pipeline be adapted for bispecific antibodies?
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Framework selection: Retain EMB1687’s heavy chain; graft light chain from a neutralizing antibody (e.g., PR961 ).
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Linker design: Use GROMACS simulations to optimize flexibility/rigidity trade-offs.
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Developability screening: Prioritize clones with <20% aggregation in accelerated stability studies .
