SCPL49 Antibody

Shipped with Ice Packs
In Stock

Product Specs

Buffer
**Preservative:** 0.03% Proclin 300
**Constituents:** 50% Glycerol, 0.01M PBS, pH 7.4
Form
Liquid
Lead Time
Made-to-order (14-16 weeks)
Synonyms
SCPL49 antibody; At3g10410 antibody; F13M14.32 antibody; Serine carboxypeptidase-like 49 antibody; EC 3.4.16.- antibody
Target Names
SCPL49
Uniprot No.

Target Background

Function
This antibody targets a protein that is likely a carboxypeptidase.
Database Links

KEGG: ath:AT3G10410

STRING: 3702.AT3G10410.1

UniGene: At.20528

Protein Families
Peptidase S10 family
Subcellular Location
Secreted.
Tissue Specificity
Expressed in roots, senescent leaves and flowers.

Q&A

FAQs for SCPL49 Antibody Research
Below are FAQs organized by research complexity, addressing experimental design, methodological considerations, and data interpretation challenges specific to SCPL49 antibody studies.

Advanced Research Questions

How can computational models address contradictions between in silico predictions and experimental SCPL49 antibody-antigen binding data?

  • Issue: Discrepancies arise from incomplete structural data (e.g., missing post-translational modifications) .

  • Resolution workflow:

    • Use Antifold (structure-based) and ProtBERT (sequence-based) models to predict binding hotspots .

    • Validate predictions via alanine scanning mutagenesis.

    • Apply multi-objective optimization (e.g., SPEA2 algorithm) to balance affinity and stability .

What strategies improve diversity in SCPL49 antibody library design for functional studies?

Integer Linear Programming (ILP) with diversity constraints outperforms traditional methods :

MethodFitness (% Binding Prediction)Entropy (Diversity)
ILP (δ₂=500)61.8%2.4
ILP (δ₂=400)59.2%3.1
SPEA2 Algorithm54.6%2.8

Key parameters:

  • δ₂ (mutation frequency constraint): Lower values increase diversity but reduce fitness .

  • Multi-chain optimization: Heavy-chain CDR3 mutations (positions H99–H108) yield higher functional variability .

How do intrinsic vs. extrinsic fitness metrics influence SCPL49 antibody library efficacy?

  • Extrinsic fitness: Binding affinity to HER2 (measured via SPR/BLI).

  • Intrinsic fitness: Developability (e.g., thermostability, aggregation resistance) .

  • Trade-offs: Libraries optimized solely for affinity show 23% lower developability scores .

Solution: Use Pareto-frontier analysis with weighted objectives (e.g., 70% extrinsic, 30% intrinsic) during ILP optimization .

Data Contradiction Analysis

How to resolve conflicting results between computational deep mutational scanning and experimental validation?

  • Root cause: Overfitting to in silico models (e.g., ProtBERT’s sequence bias) .

  • Mitigation:

    • Validate top 10% predicted mutants via surface plasmon resonance (SPR).

    • Apply dynamic weighting during ILP to reduce bias toward any single objective .

What DOE parameters are critical for scaling SCPL49 antibody conjugation processes?

FactorRangeImpact on Drug-Antibody Ratio (DAR)
Protein Concentration5–15 mg/mLHigher concentrations reduce free thiol availability .
Temperature16–26°CLower temps favor DAR consistency (±0.2) .
pH6.8–7.8Neutral pH minimizes hydrolysis side reactions .

Quick Inquiry

Personal Email Detected
Please use an institutional or corporate email address for inquiries. Personal email accounts ( such as Gmail, Yahoo, and Outlook) are not accepted. *
© Copyright 2025 TheBiotek. All Rights Reserved.