Source 1primary paper2018Nature Communications
Toolkit/computational design strategy
computational design strategy
Taxonomy: Technique Branch / Method. Workflows sit above the mechanism and technique branches rather than replacing them.
Summary
This computational design strategy combines in silico design with biophysical experiments to improve the response kinetics of protein conformational switches. In the cited 2018 Nature Communications study, it was applied to an engineered protein-based Ca2+ sensor and rationally accelerated its response into the range of fast physiological Ca2+ fluctuations.
Usefulness & Problems
Why this is useful
The method is useful for tuning the temporal performance of engineered protein switches when native or prior designs respond too slowly for dynamic biological signals. The source literature further suggests that the strategy may be generalizable to other protein conformational switches beyond the demonstrated Ca2+ sensor.
Problem solved
It addresses the problem of slow response times in engineered protein conformational switches. In the reported application, the strategy improved the kinetics of a protein-based Ca2+ sensor so that its switching better matched fast physiological Ca2+ dynamics.
Problem links
Need conditional recombination or state switching
DerivedThis computational design strategy combines in silico design with biophysical experiments to improve the response kinetics of protein conformational switches. In the cited study, it was used to rationally optimize an engineered protein-based Ca2+ sensor, increasing switching rates and bringing response times into the range of fast physiological Ca2+ fluctuations.
Taxonomy & Function
Primary hierarchy
Technique Branch
Method: A concrete computational method used to design, rank, or analyze an engineered system.
Techniques
Computational DesignTarget processes
recombinationImplementation Constraints
cofactor dependency: cofactor requirement unknownencoding mode: genetically encodedimplementation constraint: context specific validationoperating role: builderswitch architecture: uncaging
The available evidence indicates that the approach was implemented through a synergistic combination of computational design and biophysical experiments. The supplied material does not specify software, structural inputs, mutational design rules, assay formats, or expression and delivery constraints.
The supplied evidence documents one application to an engineered Ca2+ sensor, but does not provide broader validation across multiple switch classes or target processes. Generalizability to other conformational switches is presented as a possibility rather than an independently established result.
Validation
Cell-freeBacteriaMammalianMouseHumanTherapeuticIndep. Replication
Supporting Sources
Ranked Claims
The computational design strategy may aid in optimizing the kinetics of other protein conformational switches.
Our computational design strategy is general and may aid in optimizing the kinetics of other protein conformational switches.
The computational design strategy may aid in optimizing the kinetics of other protein conformational switches.
Our computational design strategy is general and may aid in optimizing the kinetics of other protein conformational switches.
The computational design strategy may aid in optimizing the kinetics of other protein conformational switches.
Our computational design strategy is general and may aid in optimizing the kinetics of other protein conformational switches.
The computational design strategy may aid in optimizing the kinetics of other protein conformational switches.
Our computational design strategy is general and may aid in optimizing the kinetics of other protein conformational switches.
The computational design strategy may aid in optimizing the kinetics of other protein conformational switches.
Our computational design strategy is general and may aid in optimizing the kinetics of other protein conformational switches.
The computational design strategy may aid in optimizing the kinetics of other protein conformational switches.
Our computational design strategy is general and may aid in optimizing the kinetics of other protein conformational switches.
The computational design strategy may aid in optimizing the kinetics of other protein conformational switches.
Our computational design strategy is general and may aid in optimizing the kinetics of other protein conformational switches.
The computational design strategy may aid in optimizing the kinetics of other protein conformational switches.
Our computational design strategy is general and may aid in optimizing the kinetics of other protein conformational switches.
The computational design strategy may aid in optimizing the kinetics of other protein conformational switches.
Our computational design strategy is general and may aid in optimizing the kinetics of other protein conformational switches.
The computational design strategy may aid in optimizing the kinetics of other protein conformational switches.
Our computational design strategy is general and may aid in optimizing the kinetics of other protein conformational switches.
The computational design strategy may aid in optimizing the kinetics of other protein conformational switches.
Our computational design strategy is general and may aid in optimizing the kinetics of other protein conformational switches.
The computational design strategy may aid in optimizing the kinetics of other protein conformational switches.
Our computational design strategy is general and may aid in optimizing the kinetics of other protein conformational switches.
The computational design strategy may aid in optimizing the kinetics of other protein conformational switches.
Our computational design strategy is general and may aid in optimizing the kinetics of other protein conformational switches.
The computational design strategy may aid in optimizing the kinetics of other protein conformational switches.
Our computational design strategy is general and may aid in optimizing the kinetics of other protein conformational switches.
The computational design strategy may aid in optimizing the kinetics of other protein conformational switches.
Our computational design strategy is general and may aid in optimizing the kinetics of other protein conformational switches.
The computational design strategy may aid in optimizing the kinetics of other protein conformational switches.
Our computational design strategy is general and may aid in optimizing the kinetics of other protein conformational switches.
The computational design strategy may aid in optimizing the kinetics of other protein conformational switches.
Our computational design strategy is general and may aid in optimizing the kinetics of other protein conformational switches.
A computational design strategy combined with biophysical experiments rationally improved the response time of an engineered protein-based Ca2+ sensor.
Here we apply a computational design strategy in synergistic combination with biophysical experiments to rationally improve the response time of an engineered protein-based Ca2+-sensor
A computational design strategy combined with biophysical experiments rationally improved the response time of an engineered protein-based Ca2+ sensor.
Here we apply a computational design strategy in synergistic combination with biophysical experiments to rationally improve the response time of an engineered protein-based Ca2+-sensor
A computational design strategy combined with biophysical experiments rationally improved the response time of an engineered protein-based Ca2+ sensor.
Here we apply a computational design strategy in synergistic combination with biophysical experiments to rationally improve the response time of an engineered protein-based Ca2+-sensor
A computational design strategy combined with biophysical experiments rationally improved the response time of an engineered protein-based Ca2+ sensor.
Here we apply a computational design strategy in synergistic combination with biophysical experiments to rationally improve the response time of an engineered protein-based Ca2+-sensor
A computational design strategy combined with biophysical experiments rationally improved the response time of an engineered protein-based Ca2+ sensor.
Here we apply a computational design strategy in synergistic combination with biophysical experiments to rationally improve the response time of an engineered protein-based Ca2+-sensor
A computational design strategy combined with biophysical experiments rationally improved the response time of an engineered protein-based Ca2+ sensor.
Here we apply a computational design strategy in synergistic combination with biophysical experiments to rationally improve the response time of an engineered protein-based Ca2+-sensor
A computational design strategy combined with biophysical experiments rationally improved the response time of an engineered protein-based Ca2+ sensor.
Here we apply a computational design strategy in synergistic combination with biophysical experiments to rationally improve the response time of an engineered protein-based Ca2+-sensor
A computational design strategy combined with biophysical experiments rationally improved the response time of an engineered protein-based Ca2+ sensor.
Here we apply a computational design strategy in synergistic combination with biophysical experiments to rationally improve the response time of an engineered protein-based Ca2+-sensor
A computational design strategy combined with biophysical experiments rationally improved the response time of an engineered protein-based Ca2+ sensor.
Here we apply a computational design strategy in synergistic combination with biophysical experiments to rationally improve the response time of an engineered protein-based Ca2+-sensor
A computational design strategy combined with biophysical experiments rationally improved the response time of an engineered protein-based Ca2+ sensor.
Here we apply a computational design strategy in synergistic combination with biophysical experiments to rationally improve the response time of an engineered protein-based Ca2+-sensor
A computational design strategy combined with biophysical experiments rationally improved the response time of an engineered protein-based Ca2+ sensor.
Here we apply a computational design strategy in synergistic combination with biophysical experiments to rationally improve the response time of an engineered protein-based Ca2+-sensor
A computational design strategy combined with biophysical experiments rationally improved the response time of an engineered protein-based Ca2+ sensor.
Here we apply a computational design strategy in synergistic combination with biophysical experiments to rationally improve the response time of an engineered protein-based Ca2+-sensor
A computational design strategy combined with biophysical experiments rationally improved the response time of an engineered protein-based Ca2+ sensor.
Here we apply a computational design strategy in synergistic combination with biophysical experiments to rationally improve the response time of an engineered protein-based Ca2+-sensor
A computational design strategy combined with biophysical experiments rationally improved the response time of an engineered protein-based Ca2+ sensor.
Here we apply a computational design strategy in synergistic combination with biophysical experiments to rationally improve the response time of an engineered protein-based Ca2+-sensor
A computational design strategy combined with biophysical experiments rationally improved the response time of an engineered protein-based Ca2+ sensor.
Here we apply a computational design strategy in synergistic combination with biophysical experiments to rationally improve the response time of an engineered protein-based Ca2+-sensor
A computational design strategy combined with biophysical experiments rationally improved the response time of an engineered protein-based Ca2+ sensor.
Here we apply a computational design strategy in synergistic combination with biophysical experiments to rationally improve the response time of an engineered protein-based Ca2+-sensor
A computational design strategy combined with biophysical experiments rationally improved the response time of an engineered protein-based Ca2+ sensor.
Here we apply a computational design strategy in synergistic combination with biophysical experiments to rationally improve the response time of an engineered protein-based Ca2+-sensor
The optimized sensor achieved response times on the order of fast physiological Ca2+ fluctuations.
achieving response times on the order of fast physiological Ca2+ fluctuations
response time on the order of fast physiological Ca2+ fluctuations
The optimized sensor achieved response times on the order of fast physiological Ca2+ fluctuations.
achieving response times on the order of fast physiological Ca2+ fluctuations
response time on the order of fast physiological Ca2+ fluctuations
The optimized sensor achieved response times on the order of fast physiological Ca2+ fluctuations.
achieving response times on the order of fast physiological Ca2+ fluctuations
response time on the order of fast physiological Ca2+ fluctuations
The optimized sensor achieved response times on the order of fast physiological Ca2+ fluctuations.
achieving response times on the order of fast physiological Ca2+ fluctuations
response time on the order of fast physiological Ca2+ fluctuations
The optimized sensor achieved response times on the order of fast physiological Ca2+ fluctuations.
achieving response times on the order of fast physiological Ca2+ fluctuations
response time on the order of fast physiological Ca2+ fluctuations
The optimized sensor achieved response times on the order of fast physiological Ca2+ fluctuations.
achieving response times on the order of fast physiological Ca2+ fluctuations
response time on the order of fast physiological Ca2+ fluctuations
The optimized sensor achieved response times on the order of fast physiological Ca2+ fluctuations.
achieving response times on the order of fast physiological Ca2+ fluctuations
response time on the order of fast physiological Ca2+ fluctuations
The optimized sensor achieved response times on the order of fast physiological Ca2+ fluctuations.
achieving response times on the order of fast physiological Ca2+ fluctuations
response time on the order of fast physiological Ca2+ fluctuations
The optimized sensor achieved response times on the order of fast physiological Ca2+ fluctuations.
achieving response times on the order of fast physiological Ca2+ fluctuations
response time on the order of fast physiological Ca2+ fluctuations
The optimized sensor achieved response times on the order of fast physiological Ca2+ fluctuations.
achieving response times on the order of fast physiological Ca2+ fluctuations
response time on the order of fast physiological Ca2+ fluctuations
The identified mutations increased switching rates by as much as 32-fold.
our strategy identifies mutations that increase switching rates by as much as 32-fold
switching rate increase 32 fold
The identified mutations increased switching rates by as much as 32-fold.
our strategy identifies mutations that increase switching rates by as much as 32-fold
switching rate increase 32 fold
The identified mutations increased switching rates by as much as 32-fold.
our strategy identifies mutations that increase switching rates by as much as 32-fold
switching rate increase 32 fold
The identified mutations increased switching rates by as much as 32-fold.
our strategy identifies mutations that increase switching rates by as much as 32-fold
switching rate increase 32 fold
The identified mutations increased switching rates by as much as 32-fold.
our strategy identifies mutations that increase switching rates by as much as 32-fold
switching rate increase 32 fold
The identified mutations increased switching rates by as much as 32-fold.
our strategy identifies mutations that increase switching rates by as much as 32-fold
switching rate increase 32 fold
The identified mutations increased switching rates by as much as 32-fold.
our strategy identifies mutations that increase switching rates by as much as 32-fold
switching rate increase 32 fold
The identified mutations increased switching rates by as much as 32-fold.
our strategy identifies mutations that increase switching rates by as much as 32-fold
switching rate increase 32 fold
The identified mutations increased switching rates by as much as 32-fold.
our strategy identifies mutations that increase switching rates by as much as 32-fold
switching rate increase 32 fold
The identified mutations increased switching rates by as much as 32-fold.
our strategy identifies mutations that increase switching rates by as much as 32-fold
switching rate increase 32 fold
The identified mutations increased switching rates by as much as 32-fold.
our strategy identifies mutations that increase switching rates by as much as 32-fold
switching rate increase 32 fold
The identified mutations increased switching rates by as much as 32-fold.
our strategy identifies mutations that increase switching rates by as much as 32-fold
switching rate increase 32 fold
The identified mutations increased switching rates by as much as 32-fold.
our strategy identifies mutations that increase switching rates by as much as 32-fold
switching rate increase 32 fold
The identified mutations increased switching rates by as much as 32-fold.
our strategy identifies mutations that increase switching rates by as much as 32-fold
switching rate increase 32 fold
The identified mutations increased switching rates by as much as 32-fold.
our strategy identifies mutations that increase switching rates by as much as 32-fold
switching rate increase 32 fold
The identified mutations increased switching rates by as much as 32-fold.
our strategy identifies mutations that increase switching rates by as much as 32-fold
switching rate increase 32 fold
The identified mutations increased switching rates by as much as 32-fold.
our strategy identifies mutations that increase switching rates by as much as 32-fold
switching rate increase 32 fold
Approval Evidence
1 source3 linked approval claimsfirst-pass slug computational-design-strategy
Here we apply a computational design strategy in synergistic combination with biophysical experiments
Source:
generalizabilitysupports
The computational design strategy may aid in optimizing the kinetics of other protein conformational switches.
Our computational design strategy is general and may aid in optimizing the kinetics of other protein conformational switches.
Source:
performance improvementsupports
A computational design strategy combined with biophysical experiments rationally improved the response time of an engineered protein-based Ca2+ sensor.
Here we apply a computational design strategy in synergistic combination with biophysical experiments to rationally improve the response time of an engineered protein-based Ca2+-sensor
Source:
rate increasesupports
The identified mutations increased switching rates by as much as 32-fold.
our strategy identifies mutations that increase switching rates by as much as 32-fold
Source:
Comparisons
Source-backed strengths
The cited study reports a rational improvement in response time rather than an unspecified empirical optimization. A key validated outcome is that the optimized Ca2+ sensor reached response times on the order of fast physiological Ca2+ fluctuations.
Source:
Here we apply a computational design strategy in synergistic combination with biophysical experiments to rationally improve the response time of an engineered protein-based Ca2+-sensor
Compared with engineered focal adhesion kinase two-input gate
computational design strategy and engineered focal adhesion kinase two-input gate address a similar problem space because they share recombination.
Shared frame: shared target processes: recombination; shared mechanisms: conformational uncaging, conformational_uncaging
Strengths here: looks easier to implement in practice.
Compared with LHCII N-terminal domain
computational design strategy and LHCII N-terminal domain address a similar problem space because they share recombination.
Shared frame: shared target processes: recombination; shared mechanisms: conformational uncaging, conformational_uncaging
Strengths here: looks easier to implement in practice.
Compared with LOV2-based photoswitches
computational design strategy and LOV2-based photoswitches address a similar problem space because they share recombination.
Shared frame: shared target processes: recombination; shared mechanisms: conformational uncaging, conformational_uncaging
Strengths here: looks easier to implement in practice.
Relative tradeoffs: appears more independently replicated.
Ranked Citations
- 1.