Mining the Protein Data Bank to improve prediction of changes in protein-protein binding
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ABSTRACT:
SUBMITTER: Flores S
PROVIDER: S-EPMC8562805 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Mutual positioning and non-covalent interactions in anion-aromatic motifs are crucial for functional performance of biological systems. In this context, regular, comprehensive Protein Data Bank (PDB) screening that involves various scientific points of view and individual critical analysis is of utmost importance. Analysis of anions in spheres with radii of 5 Å around all 5- and 6-membered aromatic rings allowed us to distinguish 555 259 unique anion-aromatic motifs, including 92 660 structures out of the 171 588 structural files in the PDB. The use of a scarcely exploited (x, h) coordinate system led to (i) identification of three separate areas of motif accumulation: A - over the ring, B - over the ring-substituent bonds, and C - roughly in the plane of the aromatic ring, and (ii) unprecedented simultaneous comparative description of various anion-aromatic motifs located in these areas. Of the various residues considered, i.e. aminoacids, nucleotides, and ligands, the latter two exhibited a considerable tendency to locate in region Avia archetypal anion-π contacts. The applied model not only enabled statistical quantitative analysis of space around the ring, but also enabled discussion of local intermolecular arrangements, as well as detailed sequence and secondary structure analysis, e.g. anion-π interactions in the GNRA tetraloop in RNA and protein helical structures. As a purely practical issue of this work, the new code source for the PDB research was produced, tested and made freely available at https://github.com/chemiczny/PDB_supramolecular_search.
| S-EPMC8985504 | biostudies-literature
Project description:MotivationThe Protein Data Bank (PDB) currently holds over 140 000 biomolecular structures and continues to release new structures on a weekly basis. The PDB is an essential resource to the structural bioinformatics community to develop software that mine, use, categorize and analyze such data. New computational biology methods are evaluated using custom benchmarking sets derived as subsets of 3D experimentally determined structures and structural features from the PDB. Currently, such benchmarking features are manually curated with custom scripts in a non-standardized manner that results in slow distribution and updates with new experimental structures. Finally, there is a scarcity of standardized tools to rapidly query 3D descriptors of the entire PDB.ResultsOur solution is the Lemon framework, a C++11 library with Python bindings, which provides a consistent workflow methodology for selecting biomolecular interactions based on user criterion and computing desired 3D structural features. This framework can parse and characterize the entire PDB in <10 min on modern, multithreaded hardware. The speed in parsing is obtained by using the recently developed MacroMolecule Transmission Format to reduce the computational cost of reading text-based PDB files. The use of C++ lambda functions and Python bindings provide extensive flexibility for analysis and categorization of the PDB by allowing the user to write custom functions to suite their objective. We think Lemon will become a one-stop-shop to quickly mine the entire PDB to generate desired structural biology features.Availability and implementationThe Lemon software is available as a C++ header library along with a PyPI package and example functions at https://github.com/chopralab/lemon.Supplementary informationSupplementary data are available at Bioinformatics online.
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Project description:The International Agency for Research on Cancer has unequivocally classified inorganic arsenic as a Group 1 carcinogen, definitively establishing its potential to induce cancer in humans. Paradoxically, despite its well-documented toxicity, arsenic finds utility as a chemotherapeutic agent. Notable examples include melarsoprol and arsenic trioxide, both employed in the treatment of acute promyelocytic leukemia. In both therapeutic and hazardous contexts, arsenic can accumulate within cellular environments, where it engages in intricate interactions with protein molecules. Gaining a comprehensive understanding of how arsenic compounds interact with proteins holds immense promise for the development of innovative inhibitors and pharmaceutical agents. These advancements could prove invaluable in addressing a spectrum of arsenic-related diseases. In pursuit of this knowledge, we undertook a systematic exploration of the Protein Data Bank, with a focus on 902 proteins intricately associated with 26 arsenic compounds. Our comprehensive investigation reveals insights into the interactions between these arsenical compounds and amino acids located within a 4.0 Å molecular distance from arsenic-binding sites. Our findings identify that cysteine, glutamic acid, aspartic acid, serine, and arginine frequently engage with arsenic. In complement to our computational analyses, we conducted rigorous Raman spectroscopy studies on the top five amino acids displaying robust interactions with arsenic. The results derived from experimental Raman spectroscopy were meticulously compared with our computational assessments, thereby enhancing the reliability and depth of our investigations. The current study presents a multidimensional exploration into the elaborate interplay between arsenic compounds and proteins. By elucidating the specific amino acids that preferentially interact with arsenic, this study not only contributes to the fundamental understanding of these molecular associations but also lays the foundation for future endeavors in drug design and therapeutic interventions targeting arsenic-related illnesses. Our work at the convergence of toxicology, medicine, and molecular biology carries profound implications for advancing our knowledge of arsenic's dual nature as both a poison and a potential cure.
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Project description:The Membrane Protein Data Bank (MPDB) is an online, searchable, relational database of structural and functional information on integral, anchored and peripheral membrane proteins and peptides. Data originates from the Protein Data Bank and other databases, and from the literature. Structures are based on X-ray and electron diffraction, nuclear magnetic resonance and cryoelectron microscopy. The MPDB is searchable online by protein characteristic, structure determination method, crystallization technique, detergent, temperature, pH, author, etc. Record entries are hyperlinked to the PDB and Pfam for viewing sequence, three-dimensional structure and domain architecture, and for downloading coordinates. Links to PubMed are also provided. The MPDB is updated weekly in parallel with the Protein Data Bank. Statistical analysis of MPDB records can be performed and viewed online. A summary of the statistics as applied to entries in the MPDB is presented. The data suggest conditions appropriate for crystallization trials with novel membrane proteins.
| S-EPMC2792347 | biostudies-literature
Project description:XLinkDB is a fast-expanding public database now storing more than 100 000 distinct identified cross-linked protein residue pairs acquired by chemical cross-linking with mass spectrometry from samples of 12 species (J. Proteome Res. 2019, 18 (2), 753-758). Mapping identified cross-links to protein structures, when available, provides valuable guidance on protein conformations detected in the cross-linked samples. As more and more structures become available in the Protein Data Bank (Nucleic Acids Res. 2000, 28 (1), 235-242), we sought to leverage their utility for cross-link studies by automatically mapping identified cross-links to structures based on sequence homology of the cross-linked proteins with those within structures. This enables use of structures derived from organisms different from those of samples, including large multiprotein complexes and complexes in alternative states. We demonstrate utility of mapping to orthologous structures, highlighting a cross-link between two subunits of mouse mitochondrial Complex I that was mapped to 15 structures derived from five mammals, its distances there of 16.2 ± 0.4 Å indicating strong conservation of the protein interaction. We also show how multimeric structures enable reassessment of cross-links presumed to be intraprotein as potentially homodimeric interprotein in origin.
| S-EPMC7980787 | biostudies-literature
Project description:The Protein Data Bank (PDB) was established in 1971 as a repository for the three dimensional structures of biological macromolecules. Since then, more than 85000 biological macromolecule structures have been determined and made available in the PDB archive. Through analysis of the corpus of data, it is possible to identify trends that can be used to inform us abou the future of structural biology and to plan the best ways to improve the management of the ever-growing amount of PDB data.
| S-EPMC4068610 | biostudies-literature
Project description:The Protein Data Bank in Europe (pdbe.org) is a founding member of the Worldwide PDB consortium (wwPDB; wwpdb.org) and as such is actively engaged in the deposition, annotation, remediation and dissemination of macromolecular structure data through the single global archive for such data, the PDB. Similarly, PDBe is a member of the EMDataBank organisation (emdatabank.org), which manages the EMDB archive for electron microscopy data. PDBe also develops tools that help the biomedical science community to make effective use of the data in the PDB and EMDB for their research. Here we describe new or improved services, including updated SIFTS mappings to other bioinformatics resources, a new browser for the PDB archive based on Gene Ontology (GO) annotation, updates to the analysis of Nuclear Magnetic Resonance-derived structures, redesigned search and browse interfaces, and new or updated visualisation and validation tools for EMDB entries.
| S-EPMC3965016 | biostudies-literature
Project description:The Protein Data Bank in Europe (PDBe) (http://www.ebi.ac.uk/pdbe/) is actively working with its Worldwide Protein Data Bank partners to enhance the quality and consistency of the international archive of bio-macromolecular structure data, the Protein Data Bank (PDB). PDBe also works closely with its collaborators at the European Bioinformatics Institute and the scientific community around the world to enhance its databases and services by adding curated and actively maintained derived data to the existing structural data in the PDB. We have developed a new database infrastructure based on the remediated PDB archive data and a specially designed database for storing information on interactions between proteins and bound molecules. The group has developed new services that allow users to carry out simple textual queries or more complex 3D structure-based queries. The newly designed 'PDBeView Atlas pages' provide an overview of an individual PDB entry in a user-friendly layout and serve as a starting point to further explore the information available in the PDBe database. PDBe's active involvement with the X-ray crystallography, Nuclear Magnetic Resonance spectroscopy and cryo-Electron Microscopy communities have resulted in improved tools for structure deposition and analysis.
| S-EPMC2808887 | biostudies-literature
Project description:The Protein Data Bank in Europe (PDBe; pdbe.org) is actively involved in managing the international archive of biomacromolecular structure data as one of the partners in the Worldwide Protein Data Bank (wwPDB; wwpdb.org). PDBe also develops new tools to make structural data more widely and more easily available to the biomedical community. PDBe has developed a browser to access and analyze the structural archive using classification systems that are familiar to chemists and biologists. The PDBe web pages that describe individual PDB entries have been enhanced through the introduction of plain-English summary pages and iconic representations of the contents of an entry (PDBprints). In addition, the information available for structures determined by means of NMR spectroscopy has been expanded. Finally, the entire web site has been redesigned to make it substantially easier to use for expert and novice users alike. PDBe works closely with other teams at the European Bioinformatics Institute (EBI) and in the international scientific community to develop new resources with value-added information. The SIFTS initiative is an example of such a collaboration--it provides extensive mapping data between proteins whose structures are available from the PDB and a host of other biomedical databases. SIFTS is widely used by major bioinformatics resources.
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Project description:The Protein Data Bank in Europe (PDBe; pdbe.org) is a partner in the Worldwide PDB organization (wwPDB; wwpdb.org) and as such actively involved in managing the single global archive of biomacromolecular structure data, the PDB. In addition, PDBe develops tools, services and resources to make structure-related data more accessible to the biomedical community. Here we describe recently developed, extended or improved services, including an animated structure-presentation widget (PDBportfolio), a widget to graphically display the coverage of any UniProt sequence in the PDB (UniPDB), chemistry- and taxonomy-based PDB-archive browsers (PDBeXplore), and a tool for interactive visualization of NMR structures, corresponding experimental data as well as validation and analysis results (Vivaldi).
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