Computational Antibody Design with Python: Modeling Sequences, Structures, and Developability for Therapeutic Antibodies

Reactive PublishingThis book provides a practical introduction to computational methods for antibody and biologic drug design using Python. It focuses on the core technical workflows used in modern therapeutic antibody engineering, from sequence analysis through structural modeling and developability assessment.Readers will learn how to: - Work with antibody sequences and structures in Python- Perform sequence-structure modeling and analysis- Evaluate affinity-related properties- Assess key developability characteristics such as stability, solubility, and aggregation risk- Apply computational approaches to guide antibody engineering decisionsThe material is organized around clear, reproducible Python examples and workflows suitable for computational biologists, bioinformaticians, and scientists working in biologics discovery or development. Emphasis is placed on practical implementation rather than theoretical abstraction, enabling readers to build and adapt pipelines for their own antibody design projects.The book assumes intermediate familiarity with Python and basic molecular biology concepts. No prior experience with specialized antibody modeling software is required.