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In silico Identification and Characterization of Protein-Ligand Binding Sites.

Daniel Barry Roche1,2, Liam James McGuffin3

  • 1Institut de Biologie Computationnelle, LIRMM, CNRS, Université de Montpellier, 860 rue de St Priest, 34095, Montpellier, France. daniel.roche@lirmm.fr.

Methods in Molecular Biology (Clifton, N.J.)
|April 21, 2016
PubMed
Summary

Predicting protein-ligand interactions is crucial for understanding protein function. This study introduces FunFOLD, a web server for structure-informed prediction, aiding functional elucidation in areas like drug discovery.

Keywords:
Binding site residue predictionBiochemical functional elucidationContinuous Automated EvaluatiOn (CAMEO)Critical Assessment of Techniques for Protein Structure Prediction (CASP)Protein function predictionProtein structure predictionProtein–ligand interactionsQuality assessment of protein–ligand binding site predictionsStructure-based function prediction

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Area of Science:

  • Computational Biology
  • Structural Bioinformatics
  • Drug Discovery

Background:

  • In silico characterization of protein-ligand interactions is vital for determining protein functionality.
  • Traditional in vivo and in vitro methods for functional elucidation are slow, costly, and not scalable for large datasets.
  • Accelerated growth of sequence databases necessitates efficient computational approaches for functional analysis.

Purpose of the Study:

  • To highlight the importance of in silico methods for protein function prediction and protein-ligand interaction analysis.
  • To introduce and detail the FunFOLD web server and FunFOLD3 application for predicting protein-ligand interactions.
  • To provide practical guidance and examples of using FunFOLD for aiding protein functional elucidation.

Main Methods:

  • Reviewing protein function prediction strategies and the role of Critical Assessment of Techniques for Protein Structure Prediction (CASP) and Continuous Automated EvaluatiOn (CAMEO) competitions.
  • Describing the FunFOLD web server, a cutting-edge method for structure-informed prediction of protein-ligand interactions.
  • Providing a step-by-step tutorial for utilizing the FunFOLD web server and FunFOLD3 downloadable application.

Main Results:

  • The FunFOLD method enables structurally informed prediction of protein-ligand interactions.
  • The study offers practical examples demonstrating the utility of FunFOLD in aiding functional elucidation.
  • The FunFOLD web server and application facilitate large-scale analysis relevant to drug discovery.

Conclusions:

  • In silico prediction of protein-ligand interactions, particularly using methods like FunFOLD, is essential for efficient protein functional elucidation.
  • FunFOLD provides a valuable tool for researchers, streamlining the process of identifying protein-ligand binding sites and interactions.
  • The accessibility and application of FunFOLD support advancements in functional genomics and drug discovery efforts.