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Functional Characteristics Derived from the Structural Design of Bispecific Antibodies
- Han, Jaehee;
- Lim, Su Yeon;
- Kim, Yeongbeom;
- Jeong, Deokhwa;
- Kim, Hyun-Ouk;
- ... Ha, Suk-Jin;
- ... Park, Jeong-Ann;
- ... Lim, Kwang Suk;
- 외 1명
WEB OF SCIENCE
1SCOPUS
1초록
Bispecific antibodies (bsAbs) are engineered to recognize either two distinct antigens or two different epitopes on the same antigen within a single molecule. This design varies according to the intended indication and mechanism of action; the factors considered during design are critical determinants of antigen binding, pharmacological activity, productivity, and safety. In this review, bsAbs are classified into fragment-based formats and Fc-containing IgG-like formats, with the latter further divided into symmetric and asymmetric architectures. Based on this structural framework, we discuss how key design parameters-including valency, epitope geometry, affinity and binding kinetics, and linker architecture-influence avidity, immune synapse formation, receptor clustering, signaling modulation, and toxicity profiles. We further compare preclinical and clinical examples across representative target combinations, including CD19 & times; CD3, CD20 & times; CD3, BCMA & times; CD3, HER2 & times; HER2, and EGFR & times; MET, to illustrate how different molecular formats yield distinct therapeutic outcomes even when the target combinations are similar. By linking structural classification with mechanism-based interpretation and within-target comparisons, this framework relates individual design variables directly to their preclinical and clinical consequences. Finally, we describe how the energy-based molecular modeling platform Rosetta and the deep-learning-based structure-prediction system AlphaFold are applied to support interface optimization, chain-pairing control, epitope geometry prediction, and structure-guided candidate prioritization. Overall, this review can provide a structure-function framework for bsAb design by integrating key structural determinants, their functional consequences, and emerging AI-based predictive strategies to facilitate the selection of optimal molecular architectures for specific therapeutic applications.
키워드
- 제목
- Functional Characteristics Derived from the Structural Design of Bispecific Antibodies
- 저자
- Han, Jaehee; Lim, Su Yeon; Kim, Yeongbeom; Jeong, Deokhwa; Kim, Hyun-Ouk; Ha, Suk-Jin; Park, Jeong-Ann; Won, Young-Wook; Lim, Kwang Suk
- 발행일
- 2026-08-07
- 유형
- Review
- 저널명
- Pharmaceuticals
- 권
- 19
- 호
- 8
- 언어
- ENG
- 출판사
- MDPI
- 발행국가
- 스위스
- ISSN
- E 1424-8247