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Related Concept Videos

Targeted Cancer Therapies02:57

Targeted Cancer Therapies

The targeted cancer therapies, also known as “molecular targeted therapies,” take advantage of the molecular and genetic differences between the cancer cells and the normal cells. It needs a thorough understanding of the cancer cells to develop drugs that can target specific molecular aspects that drive the growth, progression, and spread of cancer cells without affecting the growth and survival of other normal cells in the body.
There are several types of targeted therapies against specific...
Targeted Cancer Therapies02:57

Targeted Cancer Therapies

The targeted cancer therapies, also known as “molecular targeted therapies,” take advantage of the molecular and genetic differences between the cancer cells and the normal cells. It needs a thorough understanding of the cancer cells to develop drugs that can target specific molecular aspects that drive the growth, progression, and spread of cancer cells without affecting the growth and survival of other normal cells in the body.
There are several types of targeted therapies against specific...
Combination Therapies and Personalized Medicine02:50

Combination Therapies and Personalized Medicine

Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...
Adaptive Mechanisms in Cancer Cells02:53

Adaptive Mechanisms in Cancer Cells

Cancer cells accumulate genetic changes at an abnormally rapid rate due to the defects in the DNA repair mechanisms. From an evolutionary perspective, such genetic instability is advantageous for cancer development. Mutant cell lines accumulate a series of beneficial mutations that contribute to their progression into cancer.
Some of the advantages that cancer cells have on normal cells include - enhanced ability to divide without terminally differentiating, induce new blood vessel formation,...
Adaptive Mechanisms in Cancer Cells02:53

Adaptive Mechanisms in Cancer Cells

Cancer cells accumulate genetic changes at an abnormally rapid rate due to the defects in the DNA repair mechanisms. From an evolutionary perspective, such genetic instability is advantageous for cancer development. Mutant cell lines accumulate a series of beneficial mutations that contribute to their progression into cancer.
Some of the advantages that cancer cells have on normal cells include - enhanced ability to divide without terminally differentiating, induce new blood vessel formation,...
Cancer Therapies02:49

Cancer Therapies

Cancer therapies are various modes of treatment, such as surgery, radiation therapy, and chemotherapy that are administered to cancer patients.
However, cancer treatments can pose several challenges, as therapies used to kill cancer cells are generally also toxic to normal cells. Moreover, cancer cells mutate rapidly and can develop resistance to chemical agents or radiation therapy. Besides, all types of cancer cells may not respond to the same therapy. Some cancer cells respond to one...

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  3. Machine Learning-optimized Single-atom Catalysts Enable Microenvironment-adaptive Chemodynamic-bioorthogonal Cancer Therapy.
  1. Home
  3. Machine Learning-optimized Single-atom Catalysts Enable Microenvironment-adaptive Chemodynamic-bioorthogonal Cancer Therapy.

Related Experiment Video

Shear Assay Protocol for the Determination of Single-Cell Material Properties
08:19

Shear Assay Protocol for the Determination of Single-Cell Material Properties

Published on: May 19, 2023

Machine Learning-Optimized Single-Atom Catalysts Enable Microenvironment-Adaptive Chemodynamic-Bioorthogonal Cancer

Xiangxuan Chao1, Zitong Zhao1, Chengming Du1

  • 1Materdicine Lab, School of Life Sciences, Shanghai University, Shanghai, China.

Advanced Materials (Deerfield Beach, Fla.)
|June 12, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

Machine learning guided the design of stable iron single-atom catalysts (Fe-N5 SAs) for enhanced chemodynamic therapy (CDT). These catalysts effectively treat tumors by generating hydroxyl radicals and activating prodrugs in situ.

Keywords:
bioorthogonal chemistrychemodynamic catalysismachine learningsingle atom catalystsynergy therapy

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Harnessing the Bioorthogonal Inverse Electron Demand Diels-Alder Cycloaddition for Pretargeted PET Imaging
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Harnessing the Bioorthogonal Inverse Electron Demand Diels-Alder Cycloaddition for Pretargeted PET Imaging

Published on: February 3, 2015

Area of Science:

  • Biomedical Engineering
  • Materials Science
  • Catalysis

Background:

  • Chemodynamic therapy (CDT) shows promise for cancer treatment by utilizing the tumor microenvironment (TME).
  • Catalyst stability and activity in the TME's acidic and reductive conditions are significant challenges.
  • Developing robust catalysts is crucial for effective CDT.

Purpose of the Study:

  • To design and synthesize a programmable dual-catalytic platform for enhanced cancer therapy.
  • To overcome the limitations of traditional catalysts in the TME using machine learning.
  • To create stable and highly active iron single-atom catalysts (Fe-N5 SAs).

Main Methods:

  • Utilized machine learning for predictive modeling and quantitative structure-performance relationship establishment.
  • Employed atomic-level precision for the rational synthesis of Fe-N5 SAs.
  • Investigated the dual-catalytic activity (CDT and bioorthogonal) of Fe-N5 SAs in the TME.

    • Main Results:

    • Fe-N5 SAs demonstrated superior chemodynamic reactivity and stability in the TME.
    • Efficient conversion of hydrogen peroxide to hydroxyl radicals for tumor ablation was observed.
    • In situ prodrug activation and doxorubicin synthesis under physiological conditions were achieved.
    • Synergistic CDT-bioorthogonal therapy resulted in enhanced antitumor efficacy.

    Conclusions:

    • Established a machine learning-guided framework for designing single-atom catalysts.
    • Demonstrated the potential of Fe-N5 SAs for stimulus-free, combinatorial cancer therapy.
    • Expanded the application of metal catalysis in biomedical fields.