Microscale Thermophoresis as a Screening Tool to Predict Melanin Binding of Drugs.
Laura HellinenSina BahrpeymaAnna-Kaisa RimpeläMarja HagströmMika ReinisaloArto UrttiPublished in: Pharmaceutics (2020)
Interactions between drugs and melanin pigment may have major impacts on pharmacokinetics. Therefore, melanin binding can modify the efficacy and toxicity of medications in ophthalmic and other disease of pigmented tissues, such as melanoma. As melanin is present in many pigmented tissues in the human body, investigation of pigment binding is relevant in drug discovery and development. Conventionally, melanin binding assays have been performed using an equilibrium binding study followed by chemical analytics, such as LC/MS. This approach is laborious, relatively slow, and limited to facilities with high performance quantitation instrumentation. We present here a screening of melanin binding with label-free microscale thermophoresis (MST) that utilizes the natural autofluorescence of melanin. We determined equilibrium dissociation constants (Kd) of 11 model compounds with melanin nanoparticles. MST categorized the compounds into extreme (chloroquine, penicillin G), high (papaverine, levofloxacin, terazosin), intermediate (timolol, nadolol, quinidine, propranolol), and low melanin binders (atropine, methotrexate, diclofenac) and displayed good correlation with binding parameter values obtained with the conventional binding study and LC/MS analytics. Further, correlation was seen between predicted melanin binding in human retinal pigment epithelium and choroid (RPE-choroid) and Kd values obtained with MST. This method represents a useful and fast approach for classification of compounds regarding melanin binding. Thus, the method can be utilized in various fields, including drug discovery, pharmacokinetics, and toxicology.
Keyphrases
- drug discovery
- dna binding
- binding protein
- endothelial cells
- mass spectrometry
- big data
- low dose
- high dose
- molecular dynamics
- molecular dynamics simulations
- deep learning
- induced pluripotent stem cells
- liquid chromatography
- artificial intelligence
- tandem mass spectrometry
- single cell
- basal cell carcinoma
- walled carbon nanotubes