Key Functions of Antibody, Nanobody, and Protein Engineering
https://www.biotechnologyreviews.com/p/multi-specific-antibodies-msabs-a
1. Antibody Affinity Maturation (Optimizing Binding Strength)
Antibodies and nanobodies undergo directed evolution to enhance binding affinity to their target antigens.
Example: Phage display and yeast display are widely used to generate higher-affinity variants by introducing mutations in the complementarity-determining regions (CDRs) of antibodies.
2. Nanobody Engineering for Stability & Small-Scale Targeting
Nanobodies (single-domain antibodies, VHHs) are engineered for increased thermal stability, solubility, and deeper tissue penetration due to their small size (~15 kDa) compared to traditional antibodies (~150 kDa).
Example: Camelid-derived nanobodies have been engineered for crossing the blood-brain barrier to target neurodegenerative disease proteins like tau and α-synuclein.
3. Antibody-Drug Conjugates (ADCs) for Targeted Therapy
Engineered antibodies are chemically conjugated to cytotoxic drugs, allowing targeted drug delivery to cancer cells while sparing healthy tissue.
Example: Trastuzumab emtansine (Kadcyla), an ADC targeting HER2-positive breast cancer, delivers a potent chemotherapeutic only to HER2-expressing cells.
4. Bispecific and Multispecific Antibodies
Bispecific antibodies (BsAbs) are engineered to recognize two different antigens or epitopes, improving therapeutic precision.
Example: Blinatumomab (Blincyto) links CD3 on T cells and CD19 on leukemia cells, enhancing targeted immune killing.
Multispecific antibodies extend this concept further, targeting multiple epitopes on a single antigen or multiple cell types.
5. Protein Engineering for Enhanced Half-Life and Fc Modifications
Engineering the Fc region of antibodies extends their half-life, enhances effector functions (e.g., ADCC, CDC), or reduces immune system interactions.
Example: Fc mutations (e.g., YTE mutations) in Efgartigimod and Daratumumab improve antibody stability and persistence in circulation.
6. Computational Design and AI-Driven Antibody Discovery
AI and computational protein modeling tools (AlphaFold, Rosetta, DeepMind) help predict antibody structures, optimize binding sites, and accelerate de novo antibody design.
Example: AI-designed synthetic antibodies are being developed to rapidly target emerging viral threats like coronaviruses and influenza strains.
Antibody & Protein Engineering in Biotech & Therapeutics
Engineered antibodies and proteins are transforming immunotherapy, targeted drug delivery, and precision medicine, with applications in cancer, infectious diseases, autoimmune disorders, and neurodegeneration.
We have multiple articles covering antibody & protein engineering in depth.
