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Artificial intelligence accelerates the identification of nature-derived potent LOXL2 inhibitors
Xiaowei Jia1, Meng Liu2, Yushi Tang1
1School of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China.
Abstract:
The role of LOXL2 in cancer has been widely demonstrated, but current therapies targeting LOXL2 are not yet fully developed. We believe that selective nature-derived inhibition of LOXL2 may provide a better therapeutic approach for the treatment of cancer. Therefore, we adopted a comprehensive approach combining deep learning and traditional computer-aided drug design methods to screen LOXL2 selective inhibitors. Bioactivity and affinity of the potential LOXL2 inhibitors were determined by molecular docking and virtual screening. At the same time, we experimentally tested the effect of potential LOXL2 inhibitors on cancer cells. Validation showed that it could inhibit proliferation and migration, promote apoptosis of CT26 cells, and reduce the expression level of LOXL2 protein. As a result, we identified a potent LOXL2 inhibitor: the natural product Forsythoside A, and demonstrated that Forsythoside A has an inhibitory effect on tumors.
Insights
Researchers identified Forsythoside A, a natural compound, as a potent inhibitor of lysyl oxidase-like 2 (LOXL2) protein. This discovery offers a promising new avenue for developing targeted cancer therapies by blocking tumor growth and spread.
Area of Science:
- Oncology
- Biochemistry
- Computational Chemistry
Background:
- Lysyl oxidase-like 2 (LOXL2) plays a significant role in cancer progression.
- Existing therapies targeting LOXL2 are still under development.
- Nature-derived inhibitors offer a potential therapeutic strategy for cancer treatment.
Purpose of the Study:
- To screen for selective LOXL2 inhibitors using a combination of deep learning and computer-aided drug design.
- To evaluate the anti-cancer effects of identified inhibitors.
- To identify a potent, nature-derived LOXL2 inhibitor for cancer therapy.
Main Methods:
- Utilized deep learning and traditional computer-aided drug design for inhibitor screening.
- Employed molecular docking and virtual screening to assess bioactivity and affinity.
- Conducted experimental validation on cancer cells (CT26) to assess inhibitory effects.
Main Results:
- Identified Forsythoside A, a natural product, as a potent LOXL2 inhibitor.
- Forsythoside A demonstrated inhibition of cancer cell proliferation and migration.
- Forsythoside A promoted apoptosis in CT26 cells and reduced LOXL2 protein expression.
- Confirmed Forsythoside A's inhibitory effect on tumors.
Conclusions:
- Forsythoside A is a potent natural inhibitor of LOXL2.
- Forsythoside A exhibits significant anti-cancer properties.
- This natural product represents a promising candidate for novel cancer therapeutics targeting LOXL2.
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