Antibody Humanization via VH-VL Orientation Prediction
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Solution Overview
Problem
Current antibody humanization methods face challenges in preserving the VH-VL domain orientation, which affects antibody specificity and affinity, and are resource-intensive and inefficient in selecting suitable humanized variants.
Innovation Solution
A fast sequence-based method that predicts VH-VL-interdomain orientation using six absolute ABangle parameters to graft specificity determining residues onto a human antibody framework, improving the selection of humanized antibodies by maintaining similar VH-VL orientation to the parent antibody.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional antibody humanization methods are used, then humanized antibodies can be produced, but the VH-VL domain orientation deviates from the parent antibody, affecting specificity and affinity
Solution Approach 1:
The patent applies parameter changes by using six absolute ABangle parameters (three rotation angles and three translation distances) to precisely control and predict the VH-VL domain orientation. This quantitative approach allows the humanized antibody to maintain the same spatial relationship between VH and VL domains as the parent antibody, thereby preserving both orientation reliability and binding precision
Solution Approach 2:
The patent replaces traditional empirical or structure-based modeling methods with a sequence-based prediction system. By using sequence information to directly predict the six ABangle parameters, the method eliminates the need for complex structural mechanics calculations while achieving accurate orientation preservation
2Reliability
If comprehensive screening methods are used to select humanized variants, then binding activity can be optimized, but the process becomes resource-intensive and inefficient
Solution Approach 1:
The patent applies preliminary action by predicting the VH-VL orientation parameters before actual antibody production and screening. This allows researchers to pre-select candidate humanized antibodies with predicted orientations matching the parent antibody, significantly reducing the number of candidates that need to be experimentally screened while ensuring binding activity optimization
Solution Approach 2:
The patent uses sequence information as a copy or proxy for structural information. By analyzing amino acid sequences to predict the six ABangle parameters, the method creates a computational model that replicates the structural orientation without requiring actual structural determination or extensive experimental screening
Data Source
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AI summary
Herein is reported a method for selecting one or more variant antibody Fv fragments derived from a parent antibody Fv fragment comprising the steps of i) generating a multitude of variant antibody Fv fragments by grafting/transferring one or more specificity determining residues from the parent antibody Fv fragment on an acceptor antibody Fv fragment, whereby each variant antibody Fv fragment of the multitude of variant antibody Fv fragments differs from the other variant antibody Fv fragments by at least one amino acid residue, ii) determining the VH- VL-orientation for the parent Fv fragment and for each of the variant antibody Fv fragments of the multitude of variant antibody Fv fragments based on a sequence fingerprint of the antibody Fv fragment, and iii) selecting those variant antibody Fv fragments that have the smallest difference in the VH-VL-orientation compared to the parent antibody's VH-VL-orientation and thereby selecting one or more variant antibody Fv fragments derived from a parent antibody Fv fragment, whereby the one or more variant antibody Fv fragments bind to the same antigen as the parent antibody Fv fragment.