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A Protocol for Computer-Based Protein Structure and Function Prediction
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3DFI: a pipeline to infer protein function using structural homology.

Alexander Thomas Julian1, Anne Caroline Mascarenhas Dos Santos1, Jean-François Pombert1

  • 1Department of Biology, Illinois Institute of Technology, Chicago, IL, USA.

Bioinformatics Advances
|June 6, 2022
PubMed
Summary

We developed 3DFI, a structural homology pipeline for inferring protein function. This tool aids genome annotation by overcoming limitations of sequence-based methods for divergent proteins.

Keywords:
Computational genomicsGenome annotationProtein function predictionProtein structure predictionStructural bioinformatics

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Area of Science:

  • Genomics
  • Structural Bioinformatics
  • Computational Biology

Background:

  • Protein function inference is crucial for genome annotation.
  • Sequence homology methods have limitations with divergent protein sequences.
  • Protein structure is intrinsically linked to biological function.

Purpose of the Study:

  • To develop a pipeline for genome-wide protein function inference using structural homology.
  • To address the limitations of disconnected, web-server based tools for high-throughput analysis.

Main Methods:

  • Developed a pipeline named 3DFI (tridimensional functional inference).
  • Leveraged existing high-quality structural homology search tools.
  • Integrated tools into a cohesive, user-friendly pipeline.

Main Results:

  • 3DFI enables efficient, genome-wide structural homology inferences.
  • The pipeline overcomes limitations of traditional sequence-based approaches.
  • Provides a solution for high-throughput functional annotation.

Conclusions:

  • 3DFI facilitates accurate protein function prediction through structural analysis.
  • The pipeline enhances genome annotation by integrating diverse structural tools.
  • 3DFI offers a robust and accessible solution for computational biologists.