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Source | Xiao Ke Life With the deepening of global aging, the economic burden of Alzheimer's disease continues to increase, reaching US$305 billion in 2020
.
At present, about 11% of people over the age of 65 have Alzheimer's disease, and the proportion of people over the age of 85 is as high as 42%
.
The accumulation of amyloid (Aβ) and microtubule-associated protein (Tau) is considered to be the main pathological mechanism of Alzheimer's disease, but drug development against this mechanism is indeed difficult
.
There is an urgent need to discover new therapeutic mechanisms in Alzheimer's disease research
.
On January 6, 2022, the research group of Evandro Fei Fang from the University of Oslo in Norway and the research group of Jiahong Lu from the University of Macau published a paper entitled: Amelioration of Alzheimer's disease pathology by mitophagy inducers identified in Nature Biomedical Engineering.
Research paper on via machine learning and a cross-species workflow
.
This study screened a large number of small molecules based on machine learning and found two lead compounds with the potential to treat Alzheimer's disease
.
Xie Chenglong of the First Affiliated Hospital of Wenzhou Medical University, Zhuang Xuxu of the University of Macau, Deruizhi Yao Niu Zhangming, and Ai Ruixue of the University of Oslo in Norway are the co-first authors of this article.
Fang Fei of the University of Oslo, Norway and Lu Jiahong of the University of Macau are the co-corresponding authors
.
Fang Fei's group published a paper in Nature Neuroscience in 2019 demonstrating that impaired mitochondrial clearance mechanisms play a key role in the pathogenesis of Alzheimer's disease
.
Mitophagy is a mechanism that selectively removes damaged mitochondria through autophagy during cell evolution.
Timely removal of damaged mitochondria plays an important role in maintaining normal cellular functions
.
In neurons of Alzheimer's disease patients, when β-amyloid 1-42 oligomers and microtubule-related proteins accumulate, mitochondria are damaged, and slightly damaged mitochondria undergo fission and fusion to ensure the internal environment of some progeny mitochondria Severely damaged mitochondria are removed by selective mitophagy by being coated with autophagosomes
.
When this function is blocked, significant dysfunctions such as mitochondrial transport and abnormal dynamics appear in neurons, leading to aggravated pathological changes in Alzheimer's disease
.
Thus, enhancing mitophagy inhibited β-amyloid 1-42 oligomers and microtubule-associated protein aggregation and reversed cognitive deficits in models of Alzheimer's disease
.
The regulation of mitophagy may provide new approaches for the treatment of Alzheimer's disease
.
However, mitophagy activators are scarce at present, and there is especially a lack of safe mitophagy activators: they do not cause damage to healthy mitochondria by themselves
.
Therefore, more efficient agonist discovery protocols are needed
.
Modern drug development is expensive, including the screening of compounds for biological activity
.
After the discovery of lead compounds, scientists conduct drug design and compound synthesis based on experience, molecular biologists test compound activity, repeatedly optimize and screen, and finally discover clinical candidate compounds.
This process often takes 10-20 years
.
However, only 12% can eventually get FDA certification
.
Nowadays, with the accumulation of various relevant data, virtual screening of drugs through artificial intelligence (AI) is expected to replace traditional active screening methods, which can not only accelerate intermediate steps, but also greatly reduce R&D costs, while improving drug screening.
precision
.
Fang Fei's team and its collaborators are committed to applying AI for high-efficiency and low-cost screening in the early stage, and performing traditional wet laboratory validation (cells, nematodes, and mice) in the later stage to improve the accuracy of screening drugs.
The combination of the two parts can accelerate the development of drugs.
The design ideas can be applied not only in Alzheimer's disease, but also in various medical fields, providing more inspiration for other research groups
.
In this study, a new AI technique was established and applied to drug screening: representation learning based on machine learning of 1D, 2D and 3D information for each molecule
.
The pre-trained data comes from a total of 19 million small molecule data from ChEMBL and ZINC
.
The pre-trained representation model comprehensively considers the information of various dimensions of molecules, including one-dimensional sequence information (SMILES), two-dimensional molecular topological similarity, and three-dimensional spatial information
.
Based on the vectors obtained by the pre-trained model, the natural small molecules have great structural diversity and are a good source for drug discovery
.
The research group of Jiahong Lu from the University of Macau has long focused on the discovery and pharmacological activity research of natural small molecule autophagy regulators derived from traditional Chinese medicine, and has established a compound library of natural small molecules including alkaloids, flavonoids, terpenoids and other types of compounds
.
The research team clustered and filtered a total of 3724 natural small molecules in the natural small molecule database of the University of Macau
.
A total of 18 natural small molecules entered the wet laboratory validation stage
.
This study validated the autophagy-inducing ability of these small-molecule compounds using human HeLa cell models, nematodes, and mouse animal models
.
The researchers finally obtained two lead small-molecule compounds, kaempferol and emodin: capable of inducing significant autophagy in human cells, nematodes, and the nervous system of mice
.
In addition, the researchers found that kaempferol and emodin had very significant ameliorating effects on neurodegenerative changes in Alzheimer's disease mice, including inhibition of Alzheimer's disease pathological conditions (extracellular β-amyloid deposits, Intracellular Aβ1-42, and microtubule-associated protein aggregation) and enhance learning and memory
.
The study received positive reviews from international peers
.
Li-Huei Tsai, MIT, an international authority on Alzheimer's disease research and a professor in the Department of Brain and Cognitive Sciences at the Massachusetts Institute of Technology, pointed out: "This study used cutting-edge machine learning algorithms to successfully discover new neurons that induce mitochondrial autophagy.
The candidate drugs were screened by computer, and then validated in multiple systems using cells, Caenorhabditis elegans, and mouse models expressing human P301L Tau protein, and finally two small-molecule compounds, kaempferol and emodin, were found
.
Interestingly, these mitophagy-inducing agents can effectively improve neuronal function, reduce Alzheimer's disease-related pathological changes, and enhance learning and memory in animal models
.
Therefore, this study was screened by computer drugs, and through multiple systematic validation, thereby identifying an effective inducer of mitophagy
.
Furthermore, their study illustrates the therapeutic value of mitophagy in neuronal protection and improving memory function
.
'' Norwegian University of Science and Technology (NTNU) International Brain Science Research authority Professor Menno Witter said, "This is an impressive multidisciplinary paper, and Fang Fei's team very convincingly demonstrates a new method for screening drugs for neurodegenerative diseases.
.
This method is based on artificial intelligence to initially screen candidate compounds that induce the clearance of damaged mitochondria in cells and animal models
.
It is well known that abnormal mitochondrial autophagy is closely related to aging
.
In this study, the authors finally found that two compounds can induce mitophagy and improve memory function in animal models
.
Although further studies on drug specificity are needed, the current results provide a very promising therapeutic avenue for neurodegeneration and aging
.
'' In conclusion, this study established a virtual screening algorithm based on AI fusion of multi-dimensional molecular information, and successfully screened multiple autophagy inducers combined with biological experimental verification to improve the accuracy of AI screening for Alzheimer's disease
.
This study further confirms the potential of enhancing autophagy mechanism in Alzheimer's disease treatment, and at the same time proposes a feasible AI-based solution for the rapid development of Alzheimer's disease drugs
.
Paper link: https:// Open for reprinting, welcome to forward to Moments and WeChat groups
.
At present, about 11% of people over the age of 65 have Alzheimer's disease, and the proportion of people over the age of 85 is as high as 42%
.
The accumulation of amyloid (Aβ) and microtubule-associated protein (Tau) is considered to be the main pathological mechanism of Alzheimer's disease, but drug development against this mechanism is indeed difficult
.
There is an urgent need to discover new therapeutic mechanisms in Alzheimer's disease research
.
On January 6, 2022, the research group of Evandro Fei Fang from the University of Oslo in Norway and the research group of Jiahong Lu from the University of Macau published a paper entitled: Amelioration of Alzheimer's disease pathology by mitophagy inducers identified in Nature Biomedical Engineering.
Research paper on via machine learning and a cross-species workflow
.
This study screened a large number of small molecules based on machine learning and found two lead compounds with the potential to treat Alzheimer's disease
.
Xie Chenglong of the First Affiliated Hospital of Wenzhou Medical University, Zhuang Xuxu of the University of Macau, Deruizhi Yao Niu Zhangming, and Ai Ruixue of the University of Oslo in Norway are the co-first authors of this article.
Fang Fei of the University of Oslo, Norway and Lu Jiahong of the University of Macau are the co-corresponding authors
.
Fang Fei's group published a paper in Nature Neuroscience in 2019 demonstrating that impaired mitochondrial clearance mechanisms play a key role in the pathogenesis of Alzheimer's disease
.
Mitophagy is a mechanism that selectively removes damaged mitochondria through autophagy during cell evolution.
Timely removal of damaged mitochondria plays an important role in maintaining normal cellular functions
.
In neurons of Alzheimer's disease patients, when β-amyloid 1-42 oligomers and microtubule-related proteins accumulate, mitochondria are damaged, and slightly damaged mitochondria undergo fission and fusion to ensure the internal environment of some progeny mitochondria Severely damaged mitochondria are removed by selective mitophagy by being coated with autophagosomes
.
When this function is blocked, significant dysfunctions such as mitochondrial transport and abnormal dynamics appear in neurons, leading to aggravated pathological changes in Alzheimer's disease
.
Thus, enhancing mitophagy inhibited β-amyloid 1-42 oligomers and microtubule-associated protein aggregation and reversed cognitive deficits in models of Alzheimer's disease
.
The regulation of mitophagy may provide new approaches for the treatment of Alzheimer's disease
.
However, mitophagy activators are scarce at present, and there is especially a lack of safe mitophagy activators: they do not cause damage to healthy mitochondria by themselves
.
Therefore, more efficient agonist discovery protocols are needed
.
Modern drug development is expensive, including the screening of compounds for biological activity
.
After the discovery of lead compounds, scientists conduct drug design and compound synthesis based on experience, molecular biologists test compound activity, repeatedly optimize and screen, and finally discover clinical candidate compounds.
This process often takes 10-20 years
.
However, only 12% can eventually get FDA certification
.
Nowadays, with the accumulation of various relevant data, virtual screening of drugs through artificial intelligence (AI) is expected to replace traditional active screening methods, which can not only accelerate intermediate steps, but also greatly reduce R&D costs, while improving drug screening.
precision
.
Fang Fei's team and its collaborators are committed to applying AI for high-efficiency and low-cost screening in the early stage, and performing traditional wet laboratory validation (cells, nematodes, and mice) in the later stage to improve the accuracy of screening drugs.
The combination of the two parts can accelerate the development of drugs.
The design ideas can be applied not only in Alzheimer's disease, but also in various medical fields, providing more inspiration for other research groups
.
In this study, a new AI technique was established and applied to drug screening: representation learning based on machine learning of 1D, 2D and 3D information for each molecule
.
The pre-trained data comes from a total of 19 million small molecule data from ChEMBL and ZINC
.
The pre-trained representation model comprehensively considers the information of various dimensions of molecules, including one-dimensional sequence information (SMILES), two-dimensional molecular topological similarity, and three-dimensional spatial information
.
Based on the vectors obtained by the pre-trained model, the natural small molecules have great structural diversity and are a good source for drug discovery
.
The research group of Jiahong Lu from the University of Macau has long focused on the discovery and pharmacological activity research of natural small molecule autophagy regulators derived from traditional Chinese medicine, and has established a compound library of natural small molecules including alkaloids, flavonoids, terpenoids and other types of compounds
.
The research team clustered and filtered a total of 3724 natural small molecules in the natural small molecule database of the University of Macau
.
A total of 18 natural small molecules entered the wet laboratory validation stage
.
This study validated the autophagy-inducing ability of these small-molecule compounds using human HeLa cell models, nematodes, and mouse animal models
.
The researchers finally obtained two lead small-molecule compounds, kaempferol and emodin: capable of inducing significant autophagy in human cells, nematodes, and the nervous system of mice
.
In addition, the researchers found that kaempferol and emodin had very significant ameliorating effects on neurodegenerative changes in Alzheimer's disease mice, including inhibition of Alzheimer's disease pathological conditions (extracellular β-amyloid deposits, Intracellular Aβ1-42, and microtubule-associated protein aggregation) and enhance learning and memory
.
The study received positive reviews from international peers
.
Li-Huei Tsai, MIT, an international authority on Alzheimer's disease research and a professor in the Department of Brain and Cognitive Sciences at the Massachusetts Institute of Technology, pointed out: "This study used cutting-edge machine learning algorithms to successfully discover new neurons that induce mitochondrial autophagy.
The candidate drugs were screened by computer, and then validated in multiple systems using cells, Caenorhabditis elegans, and mouse models expressing human P301L Tau protein, and finally two small-molecule compounds, kaempferol and emodin, were found
.
Interestingly, these mitophagy-inducing agents can effectively improve neuronal function, reduce Alzheimer's disease-related pathological changes, and enhance learning and memory in animal models
.
Therefore, this study was screened by computer drugs, and through multiple systematic validation, thereby identifying an effective inducer of mitophagy
.
Furthermore, their study illustrates the therapeutic value of mitophagy in neuronal protection and improving memory function
.
'' Norwegian University of Science and Technology (NTNU) International Brain Science Research authority Professor Menno Witter said, "This is an impressive multidisciplinary paper, and Fang Fei's team very convincingly demonstrates a new method for screening drugs for neurodegenerative diseases.
.
This method is based on artificial intelligence to initially screen candidate compounds that induce the clearance of damaged mitochondria in cells and animal models
.
It is well known that abnormal mitochondrial autophagy is closely related to aging
.
In this study, the authors finally found that two compounds can induce mitophagy and improve memory function in animal models
.
Although further studies on drug specificity are needed, the current results provide a very promising therapeutic avenue for neurodegeneration and aging
.
'' In conclusion, this study established a virtual screening algorithm based on AI fusion of multi-dimensional molecular information, and successfully screened multiple autophagy inducers combined with biological experimental verification to improve the accuracy of AI screening for Alzheimer's disease
.
This study further confirms the potential of enhancing autophagy mechanism in Alzheimer's disease treatment, and at the same time proposes a feasible AI-based solution for the rapid development of Alzheimer's disease drugs
.
Paper link: https:// Open for reprinting, welcome to forward to Moments and WeChat groups
