Identification of Mannose Interacting Residues Using Local Composition
2011

Identifying Mannose Interacting Residues in Proteins

Sample size: 120 publication Evidence: high

Author Information

Author(s): Agarwal Sandhya, Mishra Nitish Kumar, Singh Harinder, Gajendra P. S.

Primary Institution: Institute of Microbial Technology, Chandigarh, India

Hypothesis

The study aims to develop a method for predicting mannose-interacting residues in proteins.

Conclusion

The study successfully developed a method to predict mannose interacting residues with high accuracy using compositional analysis.

Supporting Evidence

  • The study achieved a maximum MCC of 0.74 with an accuracy of 86.64% on the main dataset.
  • Compositional analysis showed that certain residues are preferred in mannose interaction.
  • A standalone program and web server were developed for predicting mannose interacting residues.

Takeaway

This study helps scientists understand how certain proteins interact with sugars, which is important for our immune system.

Methodology

The study used support vector machine (SVM) models based on binary, PSSM, and compositional profiles to predict mannose interacting residues.

Limitations

The models developed on the main dataset may not represent real-life scenarios where non-MIRs are more abundant than MIRs.

Statistical Information

Statistical Significance

p<0.05

Digital Object Identifier (DOI)

10.1371/journal.pone.0024039

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