In this section
@inproceedings{Hu:2024:10.1109/EMBC53108.2024.10782410,
author = {Hu, J and Wu, P and Li, Q and Wang, S and Xiao, X and Niu, Z and Wang, B and Yang, G},
doi = {10.1109/EMBC53108.2024.10782410},
pages = {1--7},
title = {A Smart Strategy for Photoresponsive Molecules: Utilizing Generative Pre-trained Transformer and TDDFT Calculations in Drug Delivery.},
url = {http://dx.doi.org/10.1109/EMBC53108.2024.10782410},
year = {2024}
}
TY - CPAPER
AB - Photoresponsive drug delivery stands as a pivotal frontier in smart drug administration, leveraging the non-invasive, stable, and finely tunable nature of light-triggered methodologies. The Generative Pre-trained Transformer (GPT) has been employed for generating molecular structures. In our study, we harnessed GPT-2 on the QM7b dataset to refine a UV-GPT model with adapters, enabling the generation of molecules responsive to UV light excitation. Utilizing the Coulomb matrix as a molecular descriptor, we predicted the excitation wavelengths of these molecules. Furthermore, we validated the excited state properties through Quantum chemical simulations. The synergy of these findings underscores the successful application of GPT technology in this critical domain.
AU - Hu,J
AU - Wu,P
AU - Li,Q
AU - Wang,S
AU - Xiao,X
AU - Niu,Z
AU - Wang,B
AU - Yang,G
DO - 10.1109/EMBC53108.2024.10782410
EP - 7
PY - 2024///
SP - 1
TI - A Smart Strategy for Photoresponsive Molecules: Utilizing Generative Pre-trained Transformer and TDDFT Calculations in Drug Delivery.
UR - http://dx.doi.org/10.1109/EMBC53108.2024.10782410
UR - https://www.ncbi.nlm.nih.gov/pubmed/40040000
ER -
For enquiries about the MRI Physics Collective, please contact:
Mary Finnegan
Senior MR Physicist at the Imperial College Healthcare NHS Trust
Pete Lally
Assistant Professor in Magnetic Resonance (MR) Physics at Imperial College
Jan Sedlacik
MR Physicist at the Robert Steiner MR Unit, Hammersmith Hospital Campus