Geometric deep learning of protein-DNA binding specificity.

Predicting protein-DNA binding specificity is a challenging yet essential task for understanding gene regulation. Protein-DNA complexes usually exhibit binding to a selected DNA target site, whereas a protein binds, with varying degrees of binding specificity, to a wide range of DNA sequences. This information is not directly accessible in a single structure. Here, to access this information, we present Deep Predictor of Binding Specificity (DeepPBS), a geometric deep-learning model designed to predict binding specificity from protein-DNA structure. DeepPBS can be applied to experimental or predicted structures. Interpretable protein heavy atom importance scores for interface residues can be extracted. When aggregated at the protein residue level, these scores are validated through mutagenesis experiments. Applied to designed proteins targeting specific DNA sequences, DeepPBS was demonstrated to predict experimentally measured binding specificity. DeepPBS offers a foundation for machine-aided studies that advance our understanding of molecular interactions and guide experimental designs and synthetic biology.

RNAscape: geometric mapping and customizable visualization of RNA structure.

Analyzing and visualizing the tertiary structure and complex interactions of RNA is essential for being able to mechanistically decipher their molecular functions in vivo. Secondary structure visualization software can portray many aspects of RNA; however, these layouts are often unable to preserve topological correspondence since they do not consider tertiary interactions between different regions of an RNA molecule. Likewise, quaternary interactions between two or more interacting RNA molecules are not considered in secondary structure visualization tools. The RNAscape webserver produces visualizations that can preserve topological correspondence while remaining both visually intuitive and structurally insightful. RNAscape achieves this by designing a mathematical structural mapping algorithm which prioritizes the helical segments, reflecting their tertiary organization. Non-helical segments are mapped in a way that minimizes structural clutter. RNAscape runs a plotting script that is designed to generate publication-quality images. RNAscape natively supports non-standard nucleotides, multiple base-pairing annotation styles and requires no programming experience. RNAscape can also be used to analyze RNA/DNA hybrid structures and DNA topologies, including G-quadruplexes. Users can upload their own three-dimensional structures or enter a Protein Data Bank (PDB) ID of an existing structure. The RNAscape webserver allows users to customize visualizations through various settings as desired. URL: https://rnascape.usc.edu/.

Effectiveness and safety of image-directed biopsies: coaxial technique versus conventional fine-needle aspiration.

BACKGROUND: We compared the effectiveness and safety of image-guided biopsies done with coaxial guides versus fine-needle aspiration done without coaxial guides. METHODS: With the use of hospital computer records and chart reviews, all image-guided biopsies done during a 4-year period at our institution were assessed for adequacy and complications. For each biopsy, the use of a coaxial guide, the site, and the imaging modality were recorded. Adequacy of the biopsy and complications were compiled. Success rates were calculated for conventional and coaxial biopsies and by modality and site. RESULTS: Coaxial technique reduced the number of unsatisfactory biopsies compared with conventional technique in extrathoracic sites. The decrease was statistically significant. No major complications occurred from extrathoracic biopsies with either technique. No difference was found in success rates or complication rates between ultrasound-guided and CT-guided biopsies using coaxial technique. CONCLUSION: Coaxial technique reduces the number of inadequate biopsies in extrathoracic sites, without a detectable increase in complications.