Fibronectin Type III Libraries for Stable Binding
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Solution Overview
Problem
Current methods for creating synthetic libraries of scaffold binding proteins, such as those based on the fibronectin Type III domain, face challenges including high frequencies of unproductive variants, protein architecture destabilization, and inefficient candidate screening due to stochastic techniques like random mutagenesis and gene shuffling.
Innovation Solution
A systematic approach using bioinformatics-led design to construct natural-variant combinatorial libraries of fibronectin Type 3 domain polypeptides, where loop regions are engineered with specific substitutions to maximize scaffold stability and minimize non-immunogenic substitutions, allowing for tailored library size and efficient screening for desired binding activities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If random mutagenesis and gene shuffling are used to create sequence diversity in scaffold binding proteins, then sequence diversity is achieved, but protein architecture destabilization occurs and thermal stability decreases
Solution Approach 1:
The FN3 domain is segmented into framework regions (beta strands A-G) and loop regions (BC, DE, FG). Diversity is introduced only in the loop regions while the framework regions remain unchanged, thereby achieving sequence diversity without destabilizing the protein architecture. This segmentation allows independent optimization of diversity and stability.
Solution Approach 2:
Different regions of the protein are assigned different qualities: the framework regions maintain fixed, stable sequences to preserve structural integrity, while the loop regions are engineered with diverse sequences to provide binding specificity. This local differentiation resolves the contradiction by concentrating diversity where it is needed without compromising overall stability.
2Reliability
If indiscriminate substitutions are introduced to optimize affinity, then binding affinity is improved, but thermal stability decreases
Solution Approach 1:
Affinity optimization is localized to the loop regions (BC, DE, FG) which are responsible for ligand binding, while the framework regions that determine thermal stability are kept unchanged. This allows affinity improvement without sacrificing thermal stability, as the substitutions are confined to regions where they will not disrupt the overall protein fold.
3Adaptability or versatility
If exceedingly large libraries are constructed to comprehensively explore sequence diversity, then sequence diversity coverage is improved, but screening efficiency decreases
Solution Approach 1:
The library construction is segmented such that only the loop regions are diversified while the framework remains constant. This approach generates a manageable library size that can be comprehensively screened, as the fixed framework ensures that all variants maintain proper folding and stability, reducing the number of non-productive variants.
Solution Approach 2:
The framework regions are pre-selected and fixed before library construction to ensure proper protein folding and stability. This preliminary action filters out potentially unstable variants before screening, thereby improving screening efficiency by reducing the proportion of non-productive variants that would otherwise require to be screened.
Data Source
AI summary
Walk-through mutagenesis and natural-variant combinatorial fibronectin Type III (FN3) polypeptide libraries are described, along with their method of construction and use. Also disclosed are a number of high binding affinity polypeptides selected by screening the libraries against a variety of selected antigens.