HHpred is a web-based tool for remote protein homology detection and structure prediction. It allows users to search various databases and analyze the homology and predicted structures of proteins. HHpred requires a protein sequence in FASTA format as input. It then generates alignments and evaluates E-values to identify related template proteins and make structure predictions, which are more sensitive than BLAST. The tool is accessible through a web browser and its accuracy makes it competitive with other leading structure prediction servers.

1. HHPred

2. Content
● Introduction
● Objectives
● Input & Output
● Parameters
● Methodology
● Conclusion

3. HHpred is a fast server for
remote protein homology
detection and structure
prediction.
Introduction

4. “ HHPred allows to search a wide
choice of databases, such as the
PDB, SCOP, Pfam, SMART, COGs
and CDD.”

5. Objectives
Available on
HHPred is a web based
tool that can accessed
through any web
browser.
Research
Outcome
HHpred sensitivity is
competitive with the most
powerful servers for
structure prediction
currently available.
Analyzes
HHPred analyzes
the protein
homology and
predicted
structures of
proteins.

6. Input
The tool requires to
prepare or used
already existing
template protein
sequence in FASTA
format.
It provides the
isoforms of the
target protein and
their accession IDs,
in a graphical
representation.
Output
Input & Output

7. Outline of
the
HHpred
algorithm

8. 1st Input
Requires to enter query protein
in A3M/Clustal/FASTA/Stockholm
format.
2nd Parameters
Requires to provide MSA
generation method, MSA
generation iterations, E-value
cutoff for MSA generation etc.
Parameters

9. Conserved
motifs
Check for possible
conserved motifs.
Predictions
Verify the predictions
experimentally.
Check E-value
Measures the
probability & E-value
for query protein.
Alignments
Check query and
template
alignments.
Top hits
Check relationship
among top hits.
Methodology
Secondary
structure
Check secondary
structure similarity.

10. HHpred is a method for
sequence database
searching and structure
prediction that is as easy to
use as BLAST or PSI-BLAST
and that is at the same time
much more sensitive in
finding remote homologs. In
fact, HHpred sensitivity is
competitive with the most
powerful servers for
structure prediction
currently available.
Conclusion