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Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
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FTDMP: A Framework for Protein-Protein, Protein-DNA, and Protein-RNA Docking and Scoring.

Kliment Olechnovič1,2, Rita Banciul1, Justas Dapkūnas1

  • 1Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, Lithuania.

Proteins
|January 3, 2025
PubMed
Summary

FTDMP is a versatile software framework for biomolecular docking and scoring. It aids in modeling protein, DNA, and RNA interactions, proving effective in blind tests and benchmarks.

Keywords:
dockingmodel quality assessmentprotein complexesprotein–protein interactionsscoring

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Area of Science:

  • Computational Biology
  • Structural Bioinformatics
  • Molecular Modeling

Background:

  • Accurate modeling of biomolecular interactions is crucial for understanding biological processes.
  • Existing tools may have limitations in docking flexibility and scoring accuracy for diverse biomolecular complexes.
  • Development of robust computational frameworks is needed for assessing and ranking molecular models.

Purpose of the Study:

  • To introduce FTDMP, a novel software framework for comprehensive biomolecular docking and scoring.
  • To enable docking and scoring of complexes involving proteins, DNA, and RNA.
  • To provide a platform for ranking user-generated models and evaluating new scoring functions.

Main Methods:

  • FTDMP performs docking of subunits (protein, DNA, RNA) and subsequent scoring of generated models.
  • It utilizes the VoroIF-jury consensus scoring method, integrating scores from Voronoi tessellation.
  • The framework supports the ranking of user-submitted models from any structure prediction method.

Main Results:

  • FTDMP demonstrated utility in blind testing during recent CAPRI experiments.
  • Performance was validated across protein-protein, protein-DNA, and protein-RNA docking benchmarks.
  • The software proved effective for various research tasks in modeling biomolecular interactions.

Conclusions:

  • FTDMP is a valuable and versatile tool for computational modeling of biomolecular interactions.
  • Its flexibility allows for the assessment of new scoring functions and the analysis of diverse complexes.
  • The framework supports critical research in structural bioinformatics and computational biology.