Updated resources for exploring experimentally-determined PDB structures and Computed Structure Models at the RCSB Protein Data Bank.

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB, RCSB.org), the US Worldwide Protein Data Bank (wwPDB, wwPDB.org) data center for the global PDB archive, provides access to the PDB data via its RCSB.

DNAproDB: an updated database for the automated and interactive analysis of protein-DNA complexes.

DNAproDB (https://dnaprodb.usc.edu/) is a database, visualization tool, and processing pipeline for analyzing structural features of protein-DNA interactions.

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.

PNAbind: Structure-based prediction of protein-nucleic acid binding using graph neural networks.

The recognition and binding of nucleic acids (NAs) by proteins depends upon complementary chemical, electrostatic and geometric properties of the protein-NA binding interface. Structural models of protein-NA complexes provide insights into these properties but are scarce relative to models of unbound proteins. We present a deep learning approach for predicting protein-NA binding given the apo structure of a protein (PNAbind).

IHMCIF: An Extension of the PDBx/mmCIF Data Standard for Integrative Structure Determination Methods.

IHMCIF (github.com/ihmwg/IHMCIF) is a data information framework that supports archiving and disseminating macromolecular structures determined by integrative or hybrid modeling (IHM), and making them Findable, Accessible, Interoperable, and Reusable (FAIR). IHMCIF is an extension of the Protein Data Bank Exchange/macromolecular Crystallographic Information Framework (PDBx/mmCIF) that serves as the framework for the Protein Data Bank (PDB) to archive experimentally determined atomic structures of biological macromolecules and their complexes with one another and small molecule ligands (e.

DeepPBS: Geometric deep learning for interpretable prediction of protein-DNA binding specificity.

Predicting specificity in protein-DNA interactions is a challenging yet essential task for understanding gene regulation. Here, we present Deep Predictor of Binding Specificity (DeepPBS), a geometric deep-learning model designed to predict binding specificity across protein families based on protein-DNA structures. The DeepPBS architecture allows investigation of different family-specific recognition patterns.

Crystal Structures of Ternary Complexes of MEF2 and NKX2-5 Bound to DNA Reveal a Disease Related Protein-Protein Interaction Interface.

MEF2 and NKX2-5 transcription factors interact with each other in cardiogenesis and are necessary for normal heart formation. Despite evidence suggesting that these two transcription factors function synergistically and possibly through direct physical interactions, molecular mechanisms by which they interact are not clear. Here we determined the crystal structures of ternary complexes of MEF2 and NKX2-5 bound to myocardin enhancer DNA in two crystal forms.

DNAproDB: an expanded database and web-based tool for structural analysis of DNA-protein complexes.

DNAproDB (https://dnaprodb.usc.edu) is a web-based database and structural analysis tool that offers a combination of data visualization, data processing and search functionality that improves the speed and ease with which researchers can analyze, access and visualize structural data of DNA-protein complexes.

Experimental maps of DNA structure at nucleotide resolution distinguish intrinsic from protein-induced DNA deformations.

Recognition of DNA by proteins depends on DNA sequence and structure. Often unanswered is whether the structure of naked DNA persists in a protein-DNA complex, or whether protein binding changes DNA shape. While X-ray structures of protein-DNA complexes are numerous, the structure of naked cognate DNA is seldom available experimentally.

Expanding the repertoire of DNA shape features for genome-scale studies of transcription factor binding.

Uncovering the mechanisms that affect the binding specificity of transcription factors (TFs) is critical for understanding the principles of gene regulation. Although sequence-based models have been used successfully to predict TF binding specificities, we found that including DNA shape information in these models improved their accuracy and interpretability. Previously, we developed a method for modeling DNA binding specificities based on DNA shape features extracted from Monte Carlo (MC) simulations.

Structure of the Forkhead Domain of FOXA2 Bound to a Complete DNA Consensus Site.

FOXA2, a member of the forkhead family of transcription factors, plays essential roles in liver development and bile acid homeostasis. In this study, we report a 2.8 Å co-crystal structure of the FOXA2 DNA-binding domain (FOXA2-DBD) bound to a DNA duplex containing a forkhead consensus binding site (GTAAACA).

DNAproDB: an interactive tool for structural analysis of DNA-protein complexes.

Many biological processes are mediated by complex interactions between DNA and proteins. Transcription factors, various polymerases, nucleases and histones recognize and bind DNA with different levels of binding specificity. To understand the physical mechanisms that allow proteins to recognize DNA and achieve their biological functions, it is important to analyze structures of DNA-protein complexes in detail.

Direct atom-by-atom chemical identification of nanostructures and defects of topological insulators.

We present a direct atom-by-atom chemical identification of the nanostructures and defects of topological insulators (TIs) with a state-of-the-art atomic mapping technology. Combining this technique and density function theory calculations, we identify and explain the layer chemistry evolution of Bi(2)Te(3–x)Se(x) ternary TIs. We also reveal a long neglected but crucially important extended defect found to be universally present in Bi(2)Te(3) films, the seven-layer Bi(3)Te(4) nanolamella acceptors.