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Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
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For successful DNA replication, the unwinding of double-stranded DNA must be accompanied by stabilization and protection of the separated single strands of the DNA. This crucial task is performed by single-strand DNA-binding (SSB) proteins. They bind to the DNA in a sequence-independent manner, which means that the nitrogenous bases of the DNA need not be present in a specific order for binding of SSB proteins to it. The binding of SSB proteins straightens single-stranded DNA (ssDNA) and makes...
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Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
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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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PredPSD: A Gradient Tree Boosting Approach for Single-Stranded and Double-Stranded DNA Binding Protein Prediction.

Changgeng Tan1, Tong Wang1, Wenyi Yang1

  • 1School of Computer Science and Engineering, Central South University, Changsha 410075, China.

Molecules (Basel, Switzerland)
|January 1, 2020
PubMed
Summary

We developed PredPSD, a computational method to accurately distinguish single-stranded DNA-binding proteins (SSBs) from double-stranded DNA-binding proteins (DSBs) using sequence information, improving functional annotations.

Keywords:
DSB (double-stranded DNA-binding proteins)SSBs (single-stranded DNA-binding proteins)binding specificitygradient tree boostingprotein sequence

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Area of Science:

  • Bioinformatics
  • Molecular Biology
  • Computational Biology

Background:

  • Protein-DNA interactions are crucial for biological processes.
  • DNA-binding proteins are classified as single-stranded (SSBs) or double-stranded (DSBs).
  • Accurate classification aids in protein functional annotation.

Purpose of the Study:

  • To develop an effective computational method for classifying DNA-binding proteins.
  • To accurately predict single-stranded DNA-binding proteins (SSBs) and double-stranded DNA-binding proteins (DSBs) using sequence data.

Main Methods:

  • Proposed PredPSD, a sequence-based computational method.
  • Introduced novel feature extraction algorithms, including autocross-covariance (ACC) transformation.
  • Utilized minimal-redundancy-maximal-relevance (mRMR) for feature selection and gradient tree boosting (GTB) for classification.

Main Results:

  • Achieved high performance in 10-fold cross-validation (AUC: 0.956, Accuracy: 0.912).
  • Outperformed existing methods on a benchmark dataset.
  • Demonstrated improved prediction accuracy in independent testing, effectively differentiating DSBs and SSBs.

Conclusions:

  • PredPSD accurately predicts and differentiates DNA-binding proteins based on sequence.
  • The method offers a valuable tool for functional annotation of proteins.
  • PredPSD shows significant potential for recognizing binding specificities.