Chiral metallo-supramolecular complexes selectively recognize human telomeric G-quadruplex DNA

Here, we report the first example that one enantiomer of a supramolecular cylinder can selectively stabilize human telomeric G-quadruplex DNA. The P-enantiomer of this cylinder has a strong preference for G-quadruplex over duplex DNA and, in the presence of sodium, can convert G-quadruplexes from an antiparallel to a hybrid structure. The compound's chiral selectivity and its ability to discriminate quadruplex DNA have been studied by DNA melting, circular dichroism, gel electrophoresis, fluorescence spectroscopy and S1 nuclease cleavage. The chiral supramolecular complex has both small molecular chemical features and the large size of a zinc-finger-like DNA-binding motif. The complex is also convenient to synthesize and separate enantiomers. These results provide new insights into the development of chiral anticancer agents for targeting G-quadruplex DNA

Bionic Duplication of Fresh Navodon septentrionalis

Biomimetic superhydrophobic surface was fabricated by replicating topography of the fresh fish skin surface of Navodon septentrionalis with polydimethylsiloxane (PDMS) elastomer. A two-step replicating method was developed to make the surface structure of the fresh fish skin be replicated with high fidelity. After duplication, it was found that the static contact angle of the replica was as large as 173°. Theoretic analysis based on Young's and Cassie-Baxter (C-B) model was performed to explain the relationship between structure and hydrophobicity

Accurate, uncertainty-aware classification of molecular chemical motifs from multi-modal X-ray absorption spectroscopy

Accurate classification of molecular chemical motifs from experimental measurement is an important problem in molecular physics, chemistry and biology. In this work, we present neural network ensemble classifiers for predicting the presence (or lack thereof) of 41 different chemical motifs on small molecules from simulated C, N and O K-edge X-ray absorption near-edge structure (XANES) spectra. Our classifiers not only reach a maximum average class-balanced accuracy of 0.99 but also accurately quantify uncertainty. We also show that including multiple XANES modalities improves predictions notably on average, demonstrating a "multi-modal advantage" over any single modality. In addition to structure refinement, our approach can be generalized for broad applications with molecular design pipelines

Stereochemistry and amyloid inhibition : asymmetric triplex metallohelices enantioselectively bind to Aβ peptide

Stereochemistry is vital for pharmaceutical development and can determine drug efficacy. Herein, 10 pairs of asymmetric triplex metallohelix enantiomers as a library were used to screen inhibitors of amyloid β (Aβ) aggregation via a fluorescent cell–based high-throughput method. Intriguingly, Λ enantiomers show a stronger inhibition effect than Δ enantiomers. In addition, the metallohelices with aromatic substituents are more effective than those without, revealing that these groups play a key role in the Aβ interaction. Fluorescence stopped-flow kinetic studies indicate that binding of the Λ enantiomer to Aβ is much faster than that of the Δ enantiomer. Furthermore, studies in enzyme digestion, isothermal titration calorimetry, nuclear magnetic resonance, and computational docking demonstrate that the enantiomers bind to the central hydrophobic α-helical region of Aβ13–23, although with different modes for the Λ and Δ enantiomers. Finally, an in vivo study showed that these metallohelices extend the life span of the Caenorhabditis elegans CL2006 strain by attenuating Aβ-induced toxicity. Our work will shed light on the design and screening of a metal complex as an amyloid inhibitor against Alzheimer’s disease

Lightshow: a Python package for generating computational x-ray absorption spectroscopy input files

First-principles computational spectroscopy is a critical tool for interpreting experiment, performing structure refinement, and developing new physical understanding. Systematically setting up input files for different simulation codes and a diverse class of materials is a challenging task with a very high barrier-to-entry, given the complexities and nuances of each individual simulation package. This task is non-trivial even for experts in the electronic structure field and nearly formidable for non-expert researchers. Lightshow solves this problem by providing a uniform abstraction for writing computational x-ray spectroscopy input files for multiple popular codes, including FEFF, VASP, OCEAN, EXCITING and XSPECTRA. Its extendable framework will also allow the community to easily add new functions and to incorporate new simulation codes.Comment: 3 pages, 1 figure, software can be found open source under the BSD-3-clause license at https://github.com/AI-multimodal/Lightsho

Uncertainty-aware predictions of molecular X-ray absorption spectra using neural network ensembles

As machine learning (ML) methods continue to be applied to a broad scope of problems in the physical sciences, uncertainty quantification is becoming correspondingly more important for their robust application. Uncertainty aware machine learning methods have been used in select applications, but largely for scalar properties. In this work, we showcase an exemplary study in which neural network ensembles are used to predict the X-ray absorption spectra of small molecules, as well as their point-wise uncertainty, from local atomic environments. The performance of the resulting surrogate clearly demonstrates quantitative correlation between errors relative to ground truth and the predicted uncertainty estimates. Significantly, the model provides an upper bound on the expected error. Specifically, an important quality of this uncertainty-aware model is that it can indicate when the model is predicting on out-of-sample data. This allows for its integration with large scale sampling of structures together with active learning or other techniques for structure refinement. Additionally, our models can be generalized to larger molecules than those used for training, and also successfully track uncertainty due to random distortions in test molecules. While we demonstrate this workflow on a specific example, ensemble learning is completely general. We believe it could have significant impact on ML-enabled forward modeling of a broad array of molecular and materials properties.Comment: 24 pages, 16 figure

Quantitative interocular suppression in children with intermittent exotropia

PurposeWe have demonstrated that the depth of unbalanced interocular suppression can be quantified by balancing the interocular luminance differences required when both eyes are viewing simultaneously. In this study, we aimed to investigate the applicability of this method in children with intermittent exotropia (IXT), offering a quantitative assessment of interocular suppression in individuals with binocular imbalance. Additionally, we evaluated its association with the clinical characteristics of IXT.MethodsInterocular suppression in IXT was quantitatively measured using a polarizer and neutral-density (ND) filters. The density of the ND filter was adjusted incrementally from 0.3ND to 3ND, with a step size of 0.3ND (a total of 10 levels). Our prospective study involved 46 patients with IXT (mean age: 10.12 ± 4.89 years; mean ± SD) and 24 normal observers (mean age: 7.88 ± 1.83 years).ResultsThe suppression test exhibited good test–retest reliability, supported by statistical analysis. We observed more pronounced interocular suppression in individuals with IXT compared to controls. Notably, the magnitude of suppression during distant and near viewing significantly differed in IXT (1.55 ± 0.93 vs. 0.57 ± 0.64; Z = 4.764, p < 0.001). Furthermore, we identified a positive correlation between interocular suppression and data obtained from the Worth-4-Dot test. Additionally, interocular suppression showed a significant association with distance control scores.ConclusionOur novel test offers a convenient and reliable means to quantify interocular suppression in patients with IXT. The quantitative assessment of interocular suppression provides a sensitive tool to evaluate the clinical characteristics of IXT