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

Eugenia Ulzurrun, Yorley Duarte, Esteban Perez-Wohlfeil, Fernando Gonzalez-Nilo, Oswaldo Trelles

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

2 Citas (Scopus)


MOTIVATION: Molecular docking is aimed at predicting the conformation of small-molecule (ligands) within an identified binding site (BS) 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 BS, which is not always known. The process which covers BS 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 (WF) to process protein-ligand complexes, which runs from the identification of the possible BSs positions to the prediction of the experimental binding modes and affinities of the ligand. This open-access WF 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 AND IMPLEMENTATION: Software is available at: CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Idioma originalInglés
Páginas (desde-hasta)4203-4205
Número de páginas3
PublicaciónBioinformatics (Oxford, England)
EstadoPublicada - 15 ago. 2020

Áreas temáticas de ASJC Scopus

  • Estadística y probabilidad
  • Bioquímica
  • Biología molecular
  • Informática aplicada
  • Teoría computacional y matemáticas
  • Matemática computacional


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