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Detalle de: pyDockDNA: A new web server for energy-based protein-DNA docking and scoring

Title pyDockDNA: A new web server for energy-based protein-DNA docking and scoring
Abstract

Proteins and nucleic acids are essential biological macromolecules for cell life. Indeed, interactions between proteins and DNA regulate many biological processes such as protein synthesis, signal transduction, DNA storage, or DNA replication and repair. Despite their importance, less than 4% of total structures deposited in the Protein Data Bank (PDB) correspond to protein-DNA complexes, and very few computational methods are available to model their structure. We present here the pyDockDNA web server, which can successfully model a protein-DNA complex with a reasonable predictive success rate (as benchmarked on a standard dataset of protein-DNA complex structures, where DNA is in B-DNA conformation). The server implements the pyDockDNA program, as a module of pyDock suite, thus including third-party programs, modules, and previously developed tools, as well as new modules and parameters to handle the DNA properly. The user is asked to enter Protein Data Bank files for protein and DNA input structures (or suitable models) and select the chains to be docked. The server calculations are mainly divided into three steps: sampling by FTDOCK, scoring with new energy-based parameters and the possibility of applying external restraints. The user can select different options for these steps. The final output screen shows a 3D representation of the top 10 models and a table sorting the model according to the scoring function selected previously. All these output files can be downloaded, including the top 100 models predicted by pyDockDNA. The server can be freely accessed for academic use ( https://model3dbio.csic.es/pydockdna ).

Apa Reference Rodríguez-Lumbreras, L. A., Jiménez-García, B., Giménez-Santamarina, S., & Fernández-Recio, J. (2022). pyDockDNA: A new web server for energy-based protein-DNA docking and scoring. Frontiers in Molecular Biosciences, 9. 10.3389/fmolb.2022.988996
Doi 10.3389/fmolb.2022.988996
Publication Date 6 Oct 2022
Publication Type Software
Researcher Juan Fernández Recio
Ontology Computational Methods
Research Groups Structural Bioinformatics, Modeling and Biological Mechanisms
Tools pyDockDNA

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