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DisoLipPred is a state-of-the-art predictor of intrinsically disordered lipid-binding residues in protein sequences. This method relies on a modern deep neural network model, produces accurate results, and is available as a convenient web server. We provide a practical and detailed introduction to the DisoLipPred’s web server. We describe the underlying predictive process, which is fully automated and performed on the server side, and offer instructions for interactions with DisoLipPred’s web interface. We also discuss how to obtain, read, and interpret results produced by this server using a case study that analyzes results generated for the vacuolar-sorting protein SNF8. The web server is freely available at http://biomine.cs.vcu.edu/servers/DisoLipPred/ .

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Prediction of Intrinsically Disordered Lipid Binding Residues with DisoLipPred

  • 实验方案

  • 发表日期：

    2025年

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  • Bi Zhao,
  • Lukasz Kurgan

摘要

DisoLipPred is a state-of-the-art predictor of intrinsically disordered lipid-binding residues in protein sequences. This method relies on a modern deep neural network model, produces accurate results, and is available as a convenient web server. We provide a practical and detailed introduction to the DisoLipPred’s web server. We describe the underlying predictive process, which is fully automated and performed on the server side, and offer instructions for interactions with DisoLipPred’s web interface. We also discuss how to obtain, read, and interpret results produced by this server using a case study that analyzes results generated for the vacuolar-sorting protein SNF8. The web server is freely available at http://biomine.cs.vcu.edu/servers/DisoLipPred/ .