LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

PLIDflow: an open-source workflow for the online analysis of protein-ligand docking using galaxy

Photo from wikipedia

MOTIVATION Molecular docking is aimed at predicting the conformation of small-molecule (ligands) within an identified binding site in a target protein (receptor). Protein-ligand docking plays an important role in modern… Click to show full abstract

MOTIVATION Molecular docking is aimed at predicting the conformation of small-molecule (ligands) within an identified binding site in a target protein (receptor). Protein-ligand docking plays an important role in modern drug discovery and biochemistry for protein engineering. However, efficient docking analysis of proteins requires prior knowledge of the binding site which is not always known. The process which covers binding site identification and protein-ligand docking usually requires the combination of different programs which require several input parameters. This is furtherly aggravated when factoring in computational demands such as CPU-time. Therefore, these types of simulation experiments can become a complex process for researchers without a background in computer sciences. RESULTS To overcome these problems, we have designed an automatic computational workflow to process protein-ligand complexes, which runs from the identification of the possible binding sites positions to the prediction of the experimental binding modes and affinities of the ligand. This open-access workflow runs under the Galaxy platform that integrates public domain software. The results of the proposed method are in close agreement with state-of-the-art docking software. AVAILABILITY Software is available at: https://pistacho.ac.uma.es/galaxy-bitlab. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Keywords: protein; analysis; binding site; protein ligand; ligand docking

Journal Title: Bioinformatics
Year Published: 2020

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.