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We characterise the structural properties of the quasi-liquid layer (QLL) at two low-index ice surfaces in the presence of sodium chloride (Na+/Cl-) ions by molecular dynamics simulations. We find that the presence of a high surface density of Na+/Cl- pairs changes the surface melting behaviour from step-wise to gradual melting. The ions lead to an overall increase of the thickness and the disorder of the QLL, and to a low-temperature roughening transition of the air-ice interface. The local molecular structure of the QLL is similar to that of liquid water, and the differences between the basal and primary prismatic surface are attenuated by the presence of Na+/Cl- pairs. These changes modify the crystal growth rates of different facets and the solvation environment at the surface of sea-water ice with a potential impact on light scattering and environmental chemical reactions.
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Predicting UV-visible absorption spectra is essential to understand photochemical processes and design energy materials. Quantum chemical methods can deliver accurate calculations of UV-visible absorption spectra, but they are computationally expensive, especially for large systems or when one computes line shapes from thermal averages. Here, we present an approach to predict UV-visible absorption spectra of solvated aromatic molecules by quantum chemistry (QC) and machine learning (ML). We show that a ML model, trained on the high-level QC calculation of the excitation energy of a set of aromatic molecules, can accurately predict the line shape of the lowest-energy UV-visible absorption band of several related molecules with less than 0.1 eV deviation with respect to reference experimental spectra. Applying linear decomposition analysis on the excitation energies, we unveil that our ML models probe vertical excitations of these aromatic molecules primarily by learning the atomic environment of their phenyl rings, which align with the physical origin of the π âπ* electronic transition. Our study provides an effective workflow that combines ML with quantum chemical methods to accelerate the calculations of UV-visible absorption spectra for various molecular systems.
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Aprendizado de Máquina , Espectrofotometria UltravioletaRESUMO
Glioblastoma multiforme (GBM) is the most common and deadliest form of brain tumor and remains amongst the most difficult cancers to treat. Brevican (Bcan), a central nervous system (CNS)-specific extracellular matrix protein, is upregulated in high-grade glioma cells, including GBM. A Bcan isoform lacking most glycosylation, dg-Bcan, is found only in GBM tissues. Here, dg-Bcan is explored as a molecular target for GBM. In this study, we screened a d-peptide library to identify a small 8-amino acid dg-Bcan-Targeting Peptide (BTP) candidate, called BTP-7 that binds dg-Bcan with high affinity and specificity. BTP-7 is preferentially internalized by dg-Bcan-expressing patient-derived GBM cells. To demonstrate GBM targeting, we radiolabeled BTP-7 with 18F, a radioisotope of fluorine, and found increased radiotracer accumulation in intracranial GBM established in mice using positron emission tomography (PET) imaging. dg-Bcan is an attractive molecular target for GBM, and BTP-7 represents a promising lead candidate for further development into novel imaging agents and targeted therapeutics.
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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.
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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.
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Guaiacol , Gelo , Fotólise , Luz Solar , ÁguaRESUMO
Molecular targeting using ligands specific to disease markers has shown great promise for early detection and directed therapy. Bead-based combinatorial libraries have served as powerful tools for the discovery of novel targeting agents. Screening platforms employing magnetic capture have been used to achieve rapid and efficient identification of high-affinity ligands from one-bead-one-compound (OBOC) libraries. Traditional manual methodologies to isolate magnetized "hit" beads are tedious and lack accuracy, and existing instruments to expedite bead sorting tend to be costly and complex. Here, we describe the design and construction of a simple and inexpensive microfluidic magnetic sorting device using standard photolithography and soft lithography approaches to facilitate high-throughput isolation of magnetized positive hit beads from combinatorial libraries. We have demonstrated that the device is able to sort magnetized beads with superior accuracy compared to conventional manual sorting approaches. This chip offers a very convenient yet inexpensive alternative for screening OBOC libraries.
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Técnicas de Química Combinatória/métodos , Magnetismo , Microfluídica/métodos , Bibliotecas de Moléculas Pequenas , Biomarcadores , Ensaios de Triagem em Larga Escala/métodos , Humanos , Ligantes , MicroesferasRESUMO
BACKGROUND: α3ß1 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 α3ß1 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 α3ß1 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 α3ß1 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.
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Combinatorial one-bead-one-compound (OBOC) peptide library screening has proven to be a powerful tool for identification of small molecules, peptides, or peptidomimetics against a variety of specific targets such as cell surface receptors, protein kinases, proteases, and phosphatases. With each bead displaying many copies of a single chemical entity, millions of compounds can be rapidly synthesized and screened with whole-cell binding on-bead functional assays. Here we describe the methodology for the synthesis, screening, and sequence deconvolution of an OBOC peptide library analyzed for affinity to a cancer cell line.
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Ensaios de Triagem em Larga Escala/métodos , Biblioteca de Peptídeos , Animais , Linhagem Celular Tumoral , HumanosRESUMO
One-bead-one-compound (OBOC) combinatorial library screening has been broadly utilized for the last two decades to identify small molecules, peptides or peptidomimetics targeting variable screening probes such as cell surface receptors, bacteria, protein kinases, phosphatases, proteases etc. In previous screening methods, library beads were suspended in solution and screened against one single probe. Only the positive beads were tracked and isolated for additional screens and finally selected for chemical decoding. During this process, the remaining negative beads were not tracked and discarded. Here we report a novel bead immobilization method such that a bead library array can be conveniently prepared and screened in its entirety, sequentially many times with a series of distinct probes. This method not only allows us to increase the screening efficiency but also permits us to determine the binding profile of each and every library bead against a large number of target receptors. As proof of concept, we serially screened a random OBOC disulfide containing cyclic heptapeptide library with three water soluble dyes as model probes: malachite green, bromocresol purple and indigo carmine. This multiplicative screening approach resulted in a rapid determination of the binding profile of each and every bead respective to each of the three dyes. Beads that interacted with malachite green only, bromocresol purple only, or both indigo carmine and bromocresol purple were isolated, and their peptide sequences were determined with microsequencer. Ultimately, the novel OBOC multiplicative screening approach could play a key role in the enhancement of existing on-bead assays such as whole cell binding, bacteria binding, protein binding, posttranslational modifications etc. with increased efficiency, capacity, and specificity.