Computational Protein Design for Thermal Stability
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Solution Overview
Problem
Current methods for computational protein design struggle to predictably introduce multiple mutations in large proteins that enhance stability without disrupting function, often resulting in low prediction accuracy and ineffective stabilization, especially for proteins with low thermal denaturation temperatures and high misfolding rates.
Innovation Solution
A computational method that uses structural and ancestral data to design non-naturally occurring amino acid sequences with at least six substitutions, focusing on core mutations and interactions that stabilize the protein structure, while maintaining or improving thermal stability, solubility, and expression levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If computational algorithms predict single-point mutations to stabilize proteins, then stability improvement is attempted, but prediction accuracy is low (misclassify deleterious mutations as stabilizing with ~20% probability)
Solution Approach 1:
The patent segments the protein structure into core and non-core regions, and segments the mutation analysis into single-point and combinatorial mutations. By focusing computational predictions on core regions and evaluating combinations of mutations rather than single points, the method improves prediction accuracy by breaking down the complex prediction problem into manageable segments that can be evaluated systematically.
Solution Approach 2:
The patent performs preliminary computational screening of large combinatorial mutant libraries before experimental validation. By using computational algorithms to pre-evaluate numerous mutation combinations and filter out deleterious ones, the method performs the action of mutation selection in advance, reducing the probability of misclassification and improving overall prediction reliability.
2Stability of the object's composition
If multiple mutations are introduced to stabilize protein structure, then thermal stability increases, but function may be reduced or abrogated due to stability-activity trade-off
Solution Approach 1:
The patent applies local quality by focusing stabilizing mutations specifically on core regions of the protein structure while leaving functional regions unchanged. By making different parts of the protein have different properties (core regions modified for stability, functional regions preserved), the method achieves thermal stabilization without compromising functional activity.
Solution Approach 2:
The patent uses ancestral sequence reconstruction to create copies of ancient protein versions that naturally possessed both stability and function. By copying sequences from evolutionary ancestors and incorporating them into modern proteins, the method transfers the dual properties of stability and functionality that were optimized by natural selection over evolutionary time.
3Stability of the object's composition
If large combinatorial mutants are predicted to enhance stability, then stability improvement is achieved, but existing methods cannot predict mutants without deleterious mutations that disrupt structure
Solution Approach 1:
The patent performs preliminary computational evaluation of large combinatorial mutant libraries to identify and filter out mutants with deleterious mutations before they are synthesized or tested experimentally. By evaluating structural integrity predictions in advance, the method prevents the introduction of mutants that would disrupt protein structure, ensuring only structurally sound candidates proceed to experimental validation.
Solution Approach 2:
The patent uses computational algorithms as an intermediary between the desire for enhanced stability and the risk of structural disruption. The computational tools act as a mediator that evaluates potential mutants, predicts their structural consequences, and selects only those combinations that enhance stability while maintaining structural integrity, bridging the gap between stability enhancement goals and structural preservation requirements.
4Adaptability or versatility
If proteins are produced in non-natural conditions (elevated temperatures, non-physiological pH, proteases), then research and biotechnology applications are enabled, but production and activity are nullified or reduced
Solution Approach 1:
The patent applies parameter changes by systematically modifying amino acid sequences at core positions to alter protein physical properties. By changing sequence parameters (amino acid composition, charge distribution, hydrophobicity) in specific regions, the method adjusts the protein's stability parameters to withstand non-natural conditions such as elevated temperatures and non-physiological pH, enabling broader application ranges.
Solution Approach 2:
The patent performs preliminary computational prediction and selection of stabilizing mutations before experimental production under non-natural conditions. By pre-adapting the protein sequence through computational design to anticipate stress conditions, the method prepares the protein in advance to withstand elevated temperatures, extreme pH, and proteolytic degradation, ensuring production and activity are maintained rather than nullified.
Data Source
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AI summary
A method for designing and selecting a protein having a stabilized structure compared to a corresponding wild type protein, and proteins having at least six amino acid substitutions with respect to a corresponding wild type protein, designed for improved thermal stability, improved specific activity and/or improved expression levels, are provided herein.