Some organic pollutants in snowpacks undergo faster photodegradation than in solution. One possible explanation for such effect is that their UV-visible absorption spectra are shifted toward lower energy when the molecules are adsorbed at the air-ice interface. However, such bathochromic shift is difficult to measure experimentally. Here, we employ a multiscale/multimodel approach that combines classical and first-principles molecular dynamics, quantum chemical methods, and statistical learning to compute the light absorption spectra of two phenolic molecules in different solvation environments at the relevant thermodynamic conditions. Our calculations provide an accurate estimate of the bathochromic shift of the lowest-energy UV-visible absorption band when these molecules are adsorbed at the air-ice interface, and they shed light into its molecular origin.

Snowpacks contain a wide variety of inorganic and organic compounds, including some that absorb sunlight and undergo direct photoreactions. How the rates of these reactions in, and on, ice compare to rates in water is unclear: some studies report similar rates, while others find faster rates in/on ice. Further complicating our understanding, there is conflicting evidence whether chemicals react more quickly at the air-ice interface compared to in liquid-like regions (LLRs) within the ice. To address these questions, we measured the photodegradation rate of guaiacol (2-methoxyphenol) in various sample types, including in solution, in ice, and at the air-ice interface of nature-identical snow. Compared to aqueous solution, we find modest rate constant enhancements (increases of 3- to 6-fold) in ice LLRs, and much larger enhancements (of 17- to 77-fold) at the air-ice interface of nature-identical snow. Our computational modeling suggests the absorption spectrum for guaiacol red-shifts and increases on ice surfaces, leading to more light absorption, but these changes explain only a small portion (roughly 2 to 9%) of the observed rate constant enhancements in/on ice. This indicates that increases in the quantum yield are primarily responsible for the increased photoreactivity of guaiacol on ice; relative to solution, our results suggest that the quantum yield is larger by a factor of roughly 3-6 in liquid-like regions and 12-40 at the air-ice interface.

Background

α3β1 integrin is overexpressed in several types of human cancer and is associated with poor prognosis, metastasis, and resistance to cancer treatment. We previously identified a cyclic peptide ligand LXY1 that specifically binds to the α3β1 integrin on human glioblastoma U-87MG cells. Here, we optimized LXY1 through one-bead one-compound combinatorial library screening and site-specific modifications to improve its in vivo binding property.

Methods

Three bead libraries were synthesized and whole-cell binding assays were performed. The binding capacity of individual peptide ligands against different tumor cells was determined by flow cytometry and confirmed by optical imaging. A complex joining biotinylated ligand with streptavidin-Cy5.5 was used for in vivo target imaging in both subcutaneous and orthotopic U-87MG xenograft mouse models.

Results

LXY30, a cyclic peptide with the sequence cdG-Phe(3,5-diF)-G-Hyp-NcR, emerged as the most potent and selective ligand for the α3 subunit of α3β1 integrin with improved in vitro and in vivo tumor-targeting effects compared to LXY1 in U-87MG cells. LXY30 is considerably stable in plasma as demonstrated in an in vitro stability study in 90 % human plasma. LXY30 also binds to several other known α3β1 integrin-expressing glioblastoma, lung, and breast cancer cell lines with various affinities.

Conclusions

Our data support further investigating the role of LXY30 as a human tumor-targeting peptide ligand for systemic and intracranial delivery of imaging agents and cancer therapeutics.