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Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

Published on: July 16, 2017

Use of designed sequences in protein structure recognition.

Gayatri Kumar¹, Richa Mudgal^1,2, Narayanaswamy Srinivasan³

¹Lab 103, Molecular Biophysics Unit, Indian Institute of Science, Bangalore, Karnataka, 560012, India.

|May 20, 2018

Summary

Computationally designed protein sequences bridge gaps in structural knowledge, aiding in the recognition of protein structures for families lacking 3-D information. This approach successfully identifies structures for previously uncharacterized protein families.

Keywords:

Fold-assignment Function annotation Homology detection Sequence-structure gap Structural domain assignment Structure recognition

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Area of Science:

Structural Biology
Bioinformatics
Computational Biology

Background:

Understanding protein structure is crucial for elucidating molecular function.
A significant gap exists in the protein sequence-structure space, particularly in the post-genomic era.
The Pfam database currently lacks 3-D structure information for 52% of protein families.

Purpose of the Study:

To address the lack of 3-D structure information for numerous protein families.
To develop a method for structure recognition of protein families with unknown structures.
To facilitate functional annotation by assigning structures to domains of unknown function (DUFs).

Main Methods:

Utilizing computationally designed sequences that link known protein domain families with shared folds.
Employing these designed sequences to detect distant relationships between protein sequences.
Applying the method to identify structures for protein families lacking known 3-D structural data.

Main Results:

Achieved an 88% success rate in structure recognition for protein families with known folds.
Successfully assigned partial or full-length structures for 1392 protein families with previously unknown structures.
Provided fold associations for 423 domains of unknown function (DUFs) to aid functional annotation.

Conclusions:

Knowledge-based filling of sequence-structure gaps is an effective strategy for protein structure recognition.
Computationally designed sequences act as crucial 'linkers' to traverse protein sequence space.
This approach enhances the understanding of protein families with limited or no available structural data.