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FPDock: Protein-protein docking using flower pollination algorithm.

Sharon Sunny1, P B Jayaraj1

  • 1Department of Computer Science and Engineering, National Institute of Technology Calicut, India.

Computational Biology and Chemistry
|May 28, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a novel Flower Pollination Algorithm (FPA) for protein-protein docking, enhancing computational structure prediction. The FPA method achieved a 58% success rate in top-ranked predictions, outperforming existing algorithms.

Keywords:
Flower pollination algorithmNature inspired algorithmsProtein–protein dockingProtein–protein interactions

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Area of Science:

  • Computational Biology
  • Structural Bioinformatics
  • Bioinformatics Algorithms

Background:

  • Protein structure and interactions are crucial for biological functions.
  • Abnormal protein interactions can lead to detrimental health effects.
  • Accurate protein structure prediction is vital for understanding protein function.

Purpose of the Study:

  • To develop an accurate computational method for protein-protein docking.
  • To apply a variant of the Flower Pollination Algorithm (FPA) for predicting protein-protein complex structures.
  • To evaluate the performance of the proposed FPA-based method against established docking tools.

Main Methods:

  • Implementation of a variant of the Flower Pollination Algorithm (FPA) for protein-protein docking.
  • Utilizing random initial populations and island-based optimization.
  • Incorporating abiotic and biotic pollination for solution diversity and intensity.
  • Employing an energy-based scoring function to guide solution acceptance.

Main Results:

  • The proposed FPA-based method achieved a 58% success rate within the top 10 ranks according to CAPRI quality criteria.
  • Performance comparison indicated that the FPA method surpasses SwarmDock, pyDock, and ZDOCK.
  • The algorithm effectively explores the solution space to find optimal protein complex structures.

Conclusions:

  • The developed Flower Pollination Algorithm variant offers a promising and effective approach for protein-protein docking.
  • This method demonstrates superior performance compared to existing computational docking tools.
  • The study contributes to advancing the field of protein structure prediction through metaheuristic algorithms.