ANTISOMA

ANTISOMA reduces intrinsic aggregation propensity of monoclonal antibodies (mAbs) by automated amino acid substitutions to enhance protein stability while preserving epitope-binding and therapeutic function.

Key Features:

• Aggregation reduction: Targets and reduces intrinsic protein aggregation propensity in monoclonal antibodies.
• Automated amino acid substitution: Implements an automated amino acid substitution approach to propose point mutations.
• Point mutation identification: Identifies potential point mutations within antibody sequences.
• Computational evaluation: Leverages computational algorithms to systematically evaluate substitutions and predict their impact on protein stability and aggregation.
• Epitope-binding preservation: Assesses substitutions to avoid compromising epitope-binding ability of the mAb.
• Applicability to human- and murine-derived mAbs: Applies the approach specifically to human- and murine-derived monoclonal antibodies.
• Stability-focused redesign: Enables redesign of mAbs to achieve enhanced stability profiles that can extend in vivo lifespan and improve therapeutic performance.

Scientific Applications:

• mAb therapeutic stabilization: Enhancing physicochemical stability of monoclonal antibody therapeutics to reduce aggregation.
• Preclinical antibody engineering: Guiding sequence-level substitutions during antibody design and optimization workflows.
• Improving in vivo performance: Designing substitutions aimed at extending in vivo lifespan and improving therapeutic performance of human- and murine-derived mAbs.

Methodology:

Identify potential point mutations within antibody sequences and apply an automated amino acid substitution approach; use computational algorithms to evaluate each substitution and predict impacts on protein stability and aggregation while ensuring epitope-binding is not compromised.