Antibody Design and Humanization via In Silico Modeling

Area of Science:

• Biotechnology
• Immunology
• Structural Biology

Background:

• Antibody humanization is crucial for therapeutic applications, but traditional sequence-based methods often lead to reduced antigen binding.
• This reduction is attributed to the incompatibility of mouse complementarity-determining regions (CDRs) with non-native human framework scaffolds.
• Structural mismatches and loss of key residues can cause humanization failures.

Purpose of the Study:

• To describe antibody humanization using homology modeling and framework shuffling.
• To highlight the advantages of structure-guided approaches over sequence-based methods.
• To explain how homology modeling can restore antibody function and binding affinity.

Main Methods:

• Creation of a homology model for the variable fragment of mouse antibodies.
• Sequence alignment of the mouse model with human germline sequences.
• Rational mutation and energy minimization to identify and resolve steric clashes and restore function.

Main Results:

• Homology modeling accounts for the tertiary structure and fold of antibodies.
• Structure-guided humanization identifies and corrects steric clashes introduced by sequence changes.
• Rational design can potentially restore antigen binding affinity lost during humanization.

Conclusions:

• Homology model-guided antibody humanization offers a more robust approach than traditional sequence-based methods.
• This structure-based strategy can overcome limitations and reduce humanization failures.
• It enables the restoration of antibody function, particularly antigen binding affinity.