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Updated: Mar 11, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Inferring Function from Homology.

Tom C Giles^1,2, Richard D Emes^3,4

¹School of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington Campus, Leicestershire, LE12 5RD, UK.

Methods in Molecular Biology (Clifton, N.J.)

|November 30, 2016

Summary

This summary is machine-generated.

Bioinformatics tools can predict gene and protein functions from large DNA sequence datasets. This pipeline aids in generating testable hypotheses for uncharacterized sequences.

Keywords:

BLAST Comparative genomics Ensembl Homology Orthology Paralogy Pfam Protein domain SMART UCSC genome browser

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Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

High-throughput sequencing generates vast amounts of biological sequence data.
Experimental validation of gene and protein function is ideal but challenging for large datasets.
Bioinformatics approaches are crucial for predicting function when hypotheses are unknown or data is extensive.

Purpose of the Study:

To propose a pipeline of freely available web-based tools for analyzing DNA and peptide sequences of unknown function.
To guide the generation of testable functional hypotheses from sequence data.
To provide a systematic approach for functional annotation in the absence of prior hypotheses.

Main Methods:

Protein domain detection using SMART and Pfam.
Sequence similarity searches with BLAST and DELTA-BLAST for homolog detection.
Comparative analysis against whole genome data.

Main Results:

The pipeline integrates multiple bioinformatics tools to analyze unknown sequences.
Each step accumulates information to build a functional hypothesis.
The described methods facilitate the prediction of gene and protein functions.

Conclusions:

A web-based bioinformatics pipeline can effectively analyze large-scale sequence data.
This approach aids in formulating testable hypotheses for uncharacterized genes and proteins.
The pipeline offers a valuable resource for functional genomics research.