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SoftwareStructural BioinformaticsStructure PredictionTools

Protein structure & folding information exploited from remote homologs.

Dr. Muniba Faiza
Last updated: March 31, 2023 12:16 pm
Dr. Muniba Faiza
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protein structure & folding prediction using remote homologs
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Remote homologs are similar protein structures that share similar functions, but there is no easily detectable sequence similarity in them. A new study has revealed that the protein folding information can be exploited from remote homologous structures. A new tool is developed to recognize such proteins and predict their structure and folding pathway.

Contents
How PAthreader works?References

This tool is known as PAthreader [1]. It recognizes remote templates and explores their folding pathways. A summary of the PAthreader workflow is explained below.

How PAthreader works?

  • PAthreader extracts predicted distance profiles and structure profiles from PDB and AlphaFold DB.
  • Creates a three-track alignment between them to improve recognition accuracy.
  • Improves AlphaFold2 performance by using the templates identified by PAthreader.
  • Later, it explores the protein folding pathways based on the hypothesis that dynamic folding information of protein is implicitly contained in its remote homologs.

The results show higher accuracy than the HHsearch and PAthreader outperforms AlphaFold2 in accuracy [1].

The online server of PAthreader is freely available at http://zhanglab-bioinf.com/PAthreader/. The code is freely available on GitHub.

For further details, read here.


References

  1. Zhao, K., Xia, Y., Zhang, F. et al. (2023). Protein structure and folding pathway prediction based on remote homologs recognition using PAthreader. Commun Biol 6, 243.
TAGGED:folding pathwayprotein structure predictionremote homologs
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ByDr. Muniba Faiza
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Dr. Muniba is a Bioinformatician based in New Delhi, India. She has completed her PhD in Bioinformatics from South China University of Technology, Guangzhou, China. She has cutting edge knowledge of bioinformatics tools, algorithms, and drug designing. When she is not reading she is found enjoying with the family. Know more about Muniba
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