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A Curated Graphene Quantum Dot-Porphyrin-Based Photosensitizer for Effective Singlet Oxygen Generation through Energy Transfer.

Riya SinhaOdhavia Sahil JaykishanPradipta Purkayastha
Published in: Langmuir : the ACS journal of surfaces and colloids (2023)
Porphyrin-based photosensitizers are proven generators of reactive oxygen species (ROS), such as singlet oxygen, and used as anti-cancer therapeutic agents. However, most of these compounds suffer from potential drawbacks due to limited photostability, hydrophobicity, aggregation propensity, and low cellular uptake. Ultrasmall fluorescent graphene quantum dots (GQDs) have emerged as the next-generation carriers for drugs and have gained reputation in the pharmaceutical domain. Considering the various limiting factors in porphyrin-based ROS generation and cellular internalization, here, we have developed a method to generate tetrakis( m -nitrophenyl) porphyrin (TNPP)-GQD exciplexes. This allows resonance energy transfer (RET) from GQDs to TNPP. The calculated overlap integrals for GQD-TNPP and AGQD-TNPP (1.001 × 10 18 and 1.257 × 10 17 M -1 cm -1 nm 4 , respectively) assured 95 and 71% energy transfer. The optimum donor-acceptor distances in these couples are 59.82 and 62.65 Å, respectively, which yielded the rate constant of RET as 4.09 and 0.56 ns -1 , respectively. The efficient RET helped in subsequent generation of singlet oxygen. The singlet oxygen quantum yields (SOQY) of around 0.435 and 0.464 for GQD-TNPP and AGQD-TNPP, respectively, are comparable to those of different porphyrin derivatives where the SOQY ranges from 0.55 to 0.70 when used with Triton X-100. The data show that non-conjugated amine- and amide-functionalized GQDs (AGQDs) are better candidates in this case because of the special properties of the amine groups. The systems could be excited at 450 nm for FRET, which favors biological usage.
Keyphrases
  • energy transfer
  • quantum dots
  • photodynamic therapy
  • reactive oxygen species
  • sensitive detection
  • cell death
  • dna damage
  • artificial intelligence
  • deep learning
  • electronic health record
  • fluorescent probe
  • iron oxide