Selectivity Approaches in Therapeutic Antibody Design

Protein therapeutics, particularly antibody-based therapies, have emerged as a cornerstone in modern disease treatment, offering key advantages over small molecules, including superior target specificity, longer half-life, and expanded target accessibility. Recent advances in artificial intelligence and generative modeling have accelerated the de novo design of peptide binders, expanding therapeutic formats and precision. This perspective highlights strategies to enhance antibody selectivity during design and preclinical development, linking structural modifications to functional signaling and therapeutic response. It also emphasizes the engineering of conditionally active antibodies and probodies that exploit features of the tumor microenvironment to improve safety and efficacy. Additionally, the article explores the structural and mechanistic diversity of clinically relevant antibodies, including anti-CD20 and anti-PD1, and examines antibody-drug conjugates, focusing on their cytotoxic payloads and eight distinct linker classes. Collectively, these strategies exemplify how structural innovation drives tumor selectivity and therapeutic precision, advancing the next generation of immunotherapeutics.