Designing novel linagliptin analogs through combined generative artificial intelligence, molecular docking, molecular dynamics simulation, and binding energy estimation for targeting fibroblast activation protein

Mingsong Shi, Zhi Yang, Yuhan Yang, Junxian Chen, Chuandong He, Xiaoan Li

Open source

DOI
10.3389/fchem.2026.1848970
Published
2026-09-09
Container
Frontiers in Chemistry
Publisher
Frontiers Media SA
Open access
unknown

Credibility signals

uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

Cite this work

BibTeX

@article{allodium:10.3389/fchem.2026.1848970,
  title = {Designing novel linagliptin analogs through combined generative artificial intelligence, molecular docking, molecular dynamics simulation, and binding energy estimation for targeting fibroblast activation protein},
  author = {Mingsong Shi and Zhi Yang and Yuhan Yang and Junxian Chen and Chuandong He and Xiaoan Li},
  year = {2026},
  journal = {Frontiers in Chemistry},
  doi = {10.3389/fchem.2026.1848970},
  url = {https://doi.org/10.3389/fchem.2026.1848970}
}

RIS

TY  - JOUR
TI  - Designing novel linagliptin analogs through combined generative artificial intelligence, molecular docking, molecular dynamics simulation, and binding energy estimation for targeting fibroblast activation protein
AU  - Mingsong Shi
AU  - Zhi Yang
AU  - Yuhan Yang
AU  - Junxian Chen
AU  - Chuandong He
AU  - Xiaoan Li
PY  - 2026
JO  - Frontiers in Chemistry
DO  - 10.3389/fchem.2026.1848970
UR  - https://doi.org/10.3389/fchem.2026.1848970
ER  - 

APA

Shi, M., Yang, Z., Yang, Y., Chen, J., He, C., & Li, X. (2026). Designing novel linagliptin analogs through combined generative artificial intelligence, molecular docking, molecular dynamics simulation, and binding energy estimation for targeting fibroblast activation protein. Frontiers in Chemistry. https://doi.org/10.3389/fchem.2026.1848970

Source records