Light-responsive and Protic Ruthenium Compounds Bearing Bathophenanthroline and Dihydroxybipyridine Ligands Achieve Nanomolar Toxicity towards Breast Cancer Cells†.
Olaitan E OladipupoSpenser R BrownRobert W LambJessica L GrayColin G CameronAlexa R DeRegnaucourtNicholas A WardJames Fletcher HallYifei XuCourtney M PetersenFengrui QuAmbar B ShresthaMatthew K ThompsonMarco BonizzoniCharles Edwin WebsterSherri A McFarlandYonghyun KimElizabeth T PapishPublished in: Photochemistry and photobiology (2021)
We report new ruthenium complexes bearing the lipophilic bathophenanthroline (BPhen) ligand and dihydroxybipyridine (dhbp) ligands which differ in the placement of the OH groups ([(BPhen)2 Ru(n,n'-dhbp)]Cl2 with n = 6 and 4 in 1A and 2A , respectively). Full characterization data are reported for 1A and 2A and single crystal X-ray diffraction for 1A . Both 1A and 2A are diprotic acids. We have studied 1A , 1B , 2A , and 2B (B = deprotonated forms) by UV-vis spectroscopy and 1 photodissociates, but 2 is light stable. Luminescence studies reveal that the basic forms have lower energy 3 MLCT states relative to the acidic forms. Complexes 1A and 2A produce singlet oxygen with quantum yields of 0.05 and 0.68, respectively, in acetonitrile. Complexes 1 and 2 are both photocytotoxic toward breast cancer cells, with complex 2 showing EC50 light values as low as 0.50 μM with PI values as high as >200 vs. MCF7. Computational studies were used to predict the energies of the 3 MLCT and 3 MC states. An inaccessible 3 MC state for 2B suggests a rationale for why photodissociation does not occur with the 4,4'-dhbp ligand. Low dark toxicity combined with an accessible 3 MLCT state for 1 O2 generation explains the excellent photocytotoxicity of 2.
Keyphrases
- breast cancer cells
- ionic liquid
- energy transfer
- high resolution
- oxidative stress
- case control
- clinical trial
- molecular dynamics
- genome wide
- single cell
- density functional theory
- computed tomography
- cancer therapy
- big data
- dna methylation
- machine learning
- magnetic resonance imaging
- artificial intelligence
- dual energy
- oxide nanoparticles
- data analysis