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Related Concept Videos

Antibody Structure01:10

Antibody Structure

61.1K
Overview
Antibodies, also known as immunoglobulins (Ig), are essential players of the adaptive immune system. These antigen-binding proteins are produced by B cells and make up 20 percent of the total blood plasma by weight. In mammals, antibodies fall into five different classes, which each elicits a different biological response upon antigen binding.
The Y-Shaped Structure of Antibodies Consists of Four Polypeptide Chains
Antibodies consist of four polypeptide chains: two identical heavy...
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Conserved Binding Sites01:49

Conserved Binding Sites

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Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally...
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Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
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Improving antibody thermostability based on statistical analysis of sequence and structural consensus data.

Lei Jia1, Mani Jain1, Yaxiong Sun1

  • 1Discovery Research, Amgen, Thousand Oaks, CA 91320, USA.

Antibody Therapeutics
|August 15, 2022
PubMed
Summary
This summary is machine-generated.

A new data science method enhances Monoclonal Antibody (MAb) thermostability prediction by integrating 3D structural analysis with sequence methods. This approach improves MAb engineering for better efficacy and manufacturing.

Keywords:
consensuscovariancemonoclonal antibodystructurethermostability

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Area of Science:

  • Biotechnology
  • Protein Engineering
  • Immunology

Background:

  • Monoclonal Antibodies (MAbs) are increasingly used as therapeutics due to high specificity.
  • Low thermostability of MAbs poses challenges in efficacy, manufacturing, and delivery.
  • Improving MAb stability is crucial for therapeutic applications.

Purpose of the Study:

  • To develop an improved method for predicting Monoclonal Antibody (MAb) thermostability.
  • To guide protein engineers in designing more thermally stable MAbs.
  • To enhance the efficacy and manufacturability of MAb therapeutics.

Main Methods:

  • Developed a novel MAb-specific method combining consensus sequence analysis with a 3D structural layer.
  • Analyzed conserved residue pairs in over 800 MAb 3D structures.
  • Integrated consensus sequence and structural residue pair covariance methods into an in-house application.

Main Results:

  • The new method significantly reduces false positives compared to consensus sequence methods alone.
  • Achieved success in designing MAb engineering panels for biologics programs.
  • Demonstrated improved prediction performance for MAb thermostability.

Conclusions:

  • A data science-based approach integrating structural and sequence data effectively predicts MAb thermostability.
  • This method offers a significant advantage in MAb engineering for developing stable therapeutic molecules.
  • The developed application aids in designing stable MAbs, impacting biologics programs.