We present a structure-based method for finding and evaluating structural similarities in protein regions relevant to ligand binding. PDBspheres comprises an exhaustive library of protein structure regions ('spheres') adjacent to complexed ligands derived from the Protein Data Bank (PDB), along with methods to find and evaluate structural matches between a protein of interest and spheres in the library. PDBspheres uses the LGA (Local-Global Alignment) structure alignment algorithm as the main engine for detecting structural similarities between the protein of interest and template spheres from the library, which currently contains >2 million spheres. To assess confidence in structural matches, an all-atom-based similarity metric takes side chain placement into account. Here, we describe the PDBspheres method, demonstrate its ability to detect and characterize binding sites in protein structures, show how PDBspheres-a strictly structure-based method-performs on a curated dataset of 2528 ligand-bound and ligand-free crystal structures, and use PDBspheres to cluster pockets and assess structural similarities among protein binding sites of 4876 structures in the 'refined set' of the PDBbind 2019 dataset.
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http://dx.doi.org/10.1093/nargab/lqac078 | DOI Listing |
Natl Sci Rev
January 2025
Hefei National Laboratory for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei 230026, China.
Lattice thermal conductivity ( ) is of great importance in basic sciences and in energy conversion applications. However, low- crystalline materials have only been obtained from heavy elements, which typically exhibit poor stability and possible toxicity. Thus, low- materials composed of light elements should be explored.
View Article and Find Full Text PDFNatl Sci Rev
January 2025
CAS Key Laboratory of Organic Solids, Beijing National Laboratory for Molecular Sciences (BNLMS), CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China.
In the face of advancements in microrobotics, intelligent control and precision medicine, artificial muscle actuation systems must meet demands for precise control, high stability, environmental adaptability and high integration miniaturization. Carbon materials, being lightweight, strong and highly conductive and flexible, show great potential for artificial muscles. Inspired by the butterfly's proboscis, we have developed a carbon-based artificial muscle, hydrogen-substituted graphdiyne muscle (HsGDY-M), fabricated efficiently using an emerging hydrogen-substituted graphdiyne (HsGDY) film with an asymmetrical surface structure.
View Article and Find Full Text PDFBiosci Microbiota Food Health
August 2024
Central Research Institute, Itoen Ltd., 21 Mekami, Sagara-cho, Haibara-gun, Shizuoka, Japan.
Probiotics exert their beneficial effects by improving the intestinal environment. Heat-inactivated probiotics may show similar effects. However, whether multi-strain mixtures (MSM) are better than single strains, irrespective of whether the bacteria are alive or dead, is unknown.
View Article and Find Full Text PDFAm J Med Open
December 2024
Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR.
Background: Studies examining racial and ethnic disparities in-hospital mortality for patients hospitalized with COVID-19 had mixed results. Findings from patients within academic medical centers (AMCs) are lacking, but important given the role of AMCs in improving health equity.
Objective: The purpose of this study is to assess whether minority patients hospitalized with COVID-19 in National COVID Cohort Collaborative (N3C) institutions, which consist predominantly of AMCs, have higher mortality rates relative to White patients.
Background: Limited-angle (LA) dual-energy (DE) cone-beam CT (CBCT) is considered as a potential solution to achieve fast and low-dose DE imaging on current CBCT scanners without hardware modification. However, its clinical implementations are hindered by the challenging image reconstruction from LA projections. While optimization-based and deep learning-based methods have been proposed for image reconstruction, their utilization is limited by the requirement for X-ray spectra measurement or paired datasets for model training.
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