scholarly journals PatternQuery: web application for fast detection of biomacromolecular structural patterns in the entire Protein Data Bank

2015 ◽  
Vol 43 (W1) ◽  
pp. W383-W388 ◽  
Author(s):  
David Sehnal ◽  
Lukáš Pravda ◽  
Radka Svobodová Vařeková ◽  
Crina-Maria Ionescu ◽  
Jaroslav Koča
Keyword(s):  
Protein Data Bank ◽  
Web Application ◽  
Data Bank ◽  
Structural Patterns ◽  
Fast Detection

scholarly journals PDBrt: A free database of complexes with measured drug-target residence time

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 1236
Author(s):  
Magdalena Ługowska ◽  
Marcin Pacholczyk
Keyword(s):  
Protein Data Bank ◽  
Residence Time ◽  
Web Application ◽  
Data Bank ◽  
Molecular Target ◽  
Binding Kinetics ◽  
New Drugs ◽  
Complex Data ◽  
Ligand Complex

Background: Difficulties in translating the in vitro potency determined by cellular assays into in vivo efficacy in living organisms complicates the design and development of drugs. However,  the residence time of a drug in its molecular target is becoming a key parameter in the design and optimization of new drugs, as recent studies show that residence time can reliably predict drug efficacy in vivo. Experimental approaches to binding kinetics and target ligand complex solutions are currently available, but known bioinformatics databases do not usually report information about the ligand residence time in its molecular target. Methods: To extend existing databases we developed the Protein Data Bank (PDB) residence time database (PDBrt) which reports drug residence time. The database is implemented as an open access web-based tool. The front end uses Bootstrap with Hypertext Markup Language (HTML), jQuery for the interface and 3Dmol.js to visualize the complexes. The server-side code uses Python web application framework, Django Rest Framework and backend database PostgreSQL. Results: The PDBrt database is a free, non-commercial repository for 3D protein-ligand complex data, including the measured ligand residence time inside the binding pocket of the specific biological macromolecules as deposited in The Protein Data Bank. The PDBrt database contains information about both the protein and the ligand separately, as well as the protein-ligand complex, binding kinetics, and time of the ligand residence inside the protein binding site. Availability: https://pdbrt.polsl.pl

GeoMine: interactive pattern mining of protein–ligand interfaces in the Protein Data Bank

2020 ◽  
Author(s):  
Konrad Diedrich ◽  
Joel Graef ◽  
Katrin Schöning-Stierand ◽  
Matthias Rarey
Keyword(s):  
Protein Data Bank ◽  
Web Application ◽  
Pattern Mining ◽  
Structural Data ◽  
Data Bank ◽  
Supplementary Information ◽  
User Friendliness ◽  
Iterative Search ◽  
Potential Applications ◽  
Query Generation

Abstract Summary The searching of user-defined 3D queries in molecular interfaces is a computationally challenging problem that is not satisfactorily solved so far. Most of the few existing tools focused on that purpose are desktop based and not openly available. Besides that, they show a lack of query versatility, search efficiency and user-friendliness. We address this issue with GeoMine, a publicly available web application that provides textual, numerical and geometrical search functionality for protein–ligand binding sites derived from structural data contained in the Protein Data Bank (PDB). The query generation is supported by a 3D representation of a start structure that provides interactively selectable elements like atoms, bonds and interactions. GeoMine gives full control over geometric variability in the query while performing a deterministic, precise search. Reasonably selective queries are processed on the entire set of protein–ligand complexes in the PDB within a few minutes. GeoMine offers an interactive and iterative search process of successive result analyses and query adaptations. From the numerous potential applications, we picked two from the field of side-effect analyze showcasing the usefulness of GeoMine. Availability and implementation GeoMine is part of the ProteinsPlus web application suite and freely available at https://proteins.plus. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals The Protein Data Bank: data distribution and query functionality

2002 ◽  
Vol 58 (s1) ◽  
pp. c214-c214
Author(s):  
W. F. Bluhm ◽  
T. Battistuz ◽  
E. Clingman ◽  
N. Deshpande ◽  
W. Fleri ◽  
...  
Keyword(s):  
Protein Data Bank ◽  
Data Distribution ◽  
Data Bank

FLIPPER: predicting and characterizing linear interacting peptides in the Protein Data Bank

2021 ◽  
pp. 166900
Author(s):  
Alexander Miguel Monzon ◽  
Paolo Bonato ◽  
Marco Necci ◽  
Silvio C.E. Tosatto ◽  
Damiano Piovesan
Keyword(s):  
Protein Data Bank ◽  
Data Bank

scholarly journals Validation and correction of Zn–Cys x His y complexes

2016 ◽  
Vol 72 (10) ◽  
pp. 1110-1118 ◽  
Author(s):  
Wouter G. Touw ◽  
Bart van Beusekom ◽  
Jochem M. G. Evers ◽  
Gert Vriend ◽  
Robbie P. Joosten
Keyword(s):  
Crystal Structures ◽  
Protein Data Bank ◽  
Model Validation ◽  
Data Bank ◽  
Zinc Complexes ◽  
Zinc Ions ◽  
Tetrahedral Complex ◽  
Context Sensitive

Many crystal structures in the Protein Data Bank contain zinc ions in a geometrically distorted tetrahedral complex with four Cys and/or His ligands. A method is presented to automatically validate and correct these zinc complexes. Analysis of the corrected zinc complexes shows that the average Zn–Cys distances and Cys–Zn–Cys angles are a function of the number of cysteines and histidines involved. The observed trends can be used to develop more context-sensitive targets for model validation and refinement.

scholarly journals Protein Data Bank: the single global archive for 3D macromolecular structure data

2018 ◽  
Vol 47 (D1) ◽  
pp. D520-D528 ◽  
Author(s):  
◽  
Stephen K Burley ◽  
Helen M Berman ◽  
Charmi Bhikadiya ◽  
Chunxiao Bi ◽  
...  
Keyword(s):  
Protein Data Bank ◽  
Structure Data ◽  
Data Bank ◽  
Macromolecular Structure
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