Home » Health » KAIST develops sensor protein that can easily detect atypical proteins… “Early diagnosis of Alzheimer’s disease”

KAIST develops sensor protein that can easily detect atypical proteins… “Early diagnosis of Alzheimer’s disease”

Used to detect peptides that cause brain diseases such as dementia and Parkinson’s disease

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Research schematic. (Top, left) Schematic diagram of a sensor protein that can cause a change in fluorescence signal at the same time as it binds to an atypical protein. It is designed so that the fluorescence wavelength of the chromophore changes when one beta sheet is removed from the beta barrel-structured green fluorescent protein and an atypical protein binds to that position in the form of a beta sheet. (Top, right) Sensor protein and amyloid-β ) Crystal structure of a complex in which a specific sequence fragment of Real-time tracking of interactions between amyloid-β) and astrocyte membranes

Intrinsically disordered proteins, which exist without a fixed three-dimensional structure, are known to cause neurological diseases such as Alzheimer’s and Parkinson’s diseases, cancer, cardiovascular diseases, and metabolic diseases.

Therefore, if they can be quickly detected and analyzed, it can not only prevent the progression of the disease and improve the patient’s prognosis through early diagnosis, but can also be of great help in uncovering the pathological mechanism and further developing treatments.

KAIST announced on the 8th that Professor Kim Hak-seong’s research team in the Department of Life Sciences succeeded in designing a sensor protein that can easily detect atypical proteins.

Proteins have a specific three-dimensional structure and perform various functions in vivo. In fact, 44% of human proteins are atypical proteins whose structure changes depending on the situation, and perform more diverse functions than regular proteins with a fixed structure.

However, atypical proteins do not have a fixed structure, making analysis and functional studies of these proteins very difficult.

The research team focused on the fact that atypical proteins have a specific amino acid sequence that forms a beta strand, a protein secondary structure, and developed a new type of sensor protein that emits a signal only when it binds complementary to this specific sequence. A design method was established.

The research team removed one beta strand of green fluorescent protein (GFP) that exists in nature and used computer and directed evolution methods to create a sensor protein that changes the wavelength spectrum of the fluorescent protein chromophore when a specific sequence of the atypical protein binds. developed.

The research team developed a sensor protein that can detect intracellular beta-amyloid, which causes Alzheimer’s, as one of the representative atypical proteins, and was able to track and image its interaction with the cell membrane in real time.

Previously, a complex multi-step preprocessing process was required to analyze atypical proteins, which caused the atypical proteins themselves to be greatly modified, which led to many limitations in the analysis and functional studies of actual atypical proteins.

However, the sensor protein developed this time can detect atypical proteins very easily and quickly by simply mixing them with atypical proteins, and is expected to greatly contribute to future atypical protein analysis and related disease research.

This study was published in the international academic journal ‘JACS Au’ in Volume 3, Issue 11, dated October 26, and was selected as the cover paper.

Dr. Taegeun Yoo, the first author, said, “Atypical proteins without a fixed structure have been very difficult targets for the design and development of sensor proteins compared to regular proteins.” He added, “This study provides a new way to analyze atypical proteins and study related pathological mechanisms.” “We will be able to suggest strategies.”

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Cover paper image of the international academic journal ‘JACS Au’
Cover paper image of the international academic journal ‘JACS Au’

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2023-12-07 23:14:37

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