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In-Silico Analyses of Molecular Force Sensors for Mechanical Characterization of Biological Systems
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ABSTRACT
Mechanical forces play key roles in biological processes such as cell migration and sensory perception. In recent years molecular force sensors have been developed as tools for
in situ
force measurements. Here we use all-atom steered molecular dynamics simulations to predict and study the relationship between design parameters and mechanical properties for three types of molecular force sensors commonly used in cellular biological research: two peptide-and one DNA-based. The peptide-based sensors consist of a pair of fluorescent proteins, which can undergo Förster resonance energy transfer (FRET), linked by spider silk (GPGGA)
n
or synthetic (GGSGGS)
n
disordered regions. The DNA-based sensor consists of two fluorophore-labeled strands of DNA that can be unzipped or sheared upon force application with a FRET signal as readout of dissociation. We simulated nine sensors, three of each kind. After equilibration, flexible peptide linkers of three different lengths were stretched by applying forces to their N-and C-terminal Cα atoms in opposite directions. Similarly, we equilibrated a DNA-based sensor and pulled on the phosphate atom of the terminal guanine of one strand and a selected phosphate atom on the other strand in the opposite direction. These simulations were performed at constant velocity (0.01 nm/ns – 10 nm/ns) and constant force (10 pN – 500 pN) for all versions of the sensors. Our results show how the force response of these sensors depends on their length, sequence, configuration and loading rate. Mechanistic insights gained from simulations analyses indicate that interpretation of experimental results should consider the influence of transient formation of secondary structure in peptide-based sensors and of overstretching in DNA-based sensors. These predictions can guide optimal fluorophore choice and facilitate the rational design of new sensors for use in protein, DNA, hybrid systems, and molecular devices.
STATEMENT OF SIGNIFICANCE
Biomolecular structures involved in various biological processes, including muscle function and sensory perception, generate, convey, and respond to mechanical forces.
In-vivo
accurate measurement of these forces is challenging but needed to understand biological function. Here we present a comprehensive computational analysis of three different types of molecular force sensors used to report pico-Newton level forces in biomolecular systems. Our atom-level simulation predictions provide mechanistic insight that can facilitate experimental data interpretation, selection of sensor design parameters, and the development of new force sensors tailored to specific applications and environments.
Title: In-Silico
Analyses of Molecular Force Sensors for Mechanical Characterization of Biological Systems
Description:
ABSTRACT
Mechanical forces play key roles in biological processes such as cell migration and sensory perception.
In recent years molecular force sensors have been developed as tools for
in situ
force measurements.
Here we use all-atom steered molecular dynamics simulations to predict and study the relationship between design parameters and mechanical properties for three types of molecular force sensors commonly used in cellular biological research: two peptide-and one DNA-based.
The peptide-based sensors consist of a pair of fluorescent proteins, which can undergo Förster resonance energy transfer (FRET), linked by spider silk (GPGGA)
n
or synthetic (GGSGGS)
n
disordered regions.
The DNA-based sensor consists of two fluorophore-labeled strands of DNA that can be unzipped or sheared upon force application with a FRET signal as readout of dissociation.
We simulated nine sensors, three of each kind.
After equilibration, flexible peptide linkers of three different lengths were stretched by applying forces to their N-and C-terminal Cα atoms in opposite directions.
Similarly, we equilibrated a DNA-based sensor and pulled on the phosphate atom of the terminal guanine of one strand and a selected phosphate atom on the other strand in the opposite direction.
These simulations were performed at constant velocity (0.
01 nm/ns – 10 nm/ns) and constant force (10 pN – 500 pN) for all versions of the sensors.
Our results show how the force response of these sensors depends on their length, sequence, configuration and loading rate.
Mechanistic insights gained from simulations analyses indicate that interpretation of experimental results should consider the influence of transient formation of secondary structure in peptide-based sensors and of overstretching in DNA-based sensors.
These predictions can guide optimal fluorophore choice and facilitate the rational design of new sensors for use in protein, DNA, hybrid systems, and molecular devices.
STATEMENT OF SIGNIFICANCE
Biomolecular structures involved in various biological processes, including muscle function and sensory perception, generate, convey, and respond to mechanical forces.
In-vivo
accurate measurement of these forces is challenging but needed to understand biological function.
Here we present a comprehensive computational analysis of three different types of molecular force sensors used to report pico-Newton level forces in biomolecular systems.
Our atom-level simulation predictions provide mechanistic insight that can facilitate experimental data interpretation, selection of sensor design parameters, and the development of new force sensors tailored to specific applications and environments.
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I'm J. Justin Gooding, founding Co-Director of the Australian Centre for NanoMedicine. I'm here to talk about sensors, what's happening scientifically, and their applications in health, environmental and food monitoring. AMA!
I'm J. Justin Gooding, founding Co-Director of the Australian Centre for NanoMedicine. I'm here to talk about sensors, what's happening scientifically, and their applications in health, environmental and food monitoring. AMA!
Hi Reddit! I’m a Scientia Professor at UNSW in New South Wales,
Australia. I co-founded and co-direct the Australian Centre for
NanoMedicine (ACN), a group that brings together exp...

