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NNDock2: A neural network-based scoring function for ranking protein-protein docking models.

Myong-Ho Chae1, Gwang So2, Ung-Jin Kim1

  • 1Department of Life Science, University of Sciences, Unjong-District, Pyongyang, DPR, Korea.

Journal of Bioinformatics and Computational Biology
|April 21, 2026
PubMed
Summary
This summary is machine-generated.

We developed NNDock2, a neural network-based scoring function for protein-protein docking models. NNDock2 improves accuracy by using more distant decoys and a better target function, performing comparably to existing methods.

Keywords:
Protein dockingdocking model evaluationneural networksprotein complex structure prediction

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Area of Science:

  • Computational biology
  • Structural biology
  • Bioinformatics

Background:

  • Protein-protein interactions (PPIs) are vital for cellular functions.
  • Structural information of protein complexes aids in understanding functions and drug design.
  • Computational modeling, particularly molecular docking, is essential due to experimental limitations.

Purpose of the Study:

  • To introduce NNDock2, an improved neural network-based scoring function for protein-protein docking models.
  • To enhance the accuracy and reliability of protein complex modeling.
  • To provide a computationally efficient scoring function for assessing protein docking models.

Main Methods:

  • Developed NNDock2, an updated version of the NNDock1 scoring function.
  • Augmented training data with additional distant decoys.
  • Utilized the fraction of native contact ([Formula: see text]) as the target function instead of interface root mean square deviation (iRMSD).
  • Applied regularization techniques to prevent overfitting during neural network training.

Main Results:

  • NNDock2 demonstrated performance comparable to state-of-the-art scoring functions on benchmark datasets (BM5, DOCKGROUND, CAPRI).
  • The updated training strategy and target function improved model quality assessment.
  • The method is computationally efficient and relatively simple.

Conclusions:

  • NNDock2 is a viable scoring function for protein-protein docking models.
  • It can be used independently or integrated into more complex scoring systems.
  • The findings contribute to advancing computational approaches for protein complex modeling and drug discovery.