PROST python package v0.2.15

PRotein Ortholog Search Tool is a new homolog detection tool that utilizes ESM-1b language model and iDCT quantization method. PROST is fast and accurate compared to traditional tools.

Installation

The package can be installed with:

pip install pyprost

On the initial run, PROST will download required files to ~/.config/prost or an user defined directory via PROSTDIR environment variable.

How to use

Following commands can be used to create databases and perform homology search.

prost.py makedb db/sp.fa db/sp.prdb
prost.py makedb db/covid.fa db/covid.prdb
prost.py search --thr 0.05 --jobs 8 db/covid.prdb db/sp.prdb results
prost.py searchsp --thr 0.05 --jobs 8 db/covid.prdb results
prost.py tosjonwp -a -i 'info' results.tsv website

• makedb: creates a PROST database from given fasta file. The fasta file usually contains more than one entry.
• search: searches a query database agains a target database. Query database can contain one or more sequences embedded using makedb command. --thr can be used to specify an e-value threshold. The default threshold is 0.05. You can paralelize the search by using --jobs option.
• searchsp: searches a query database agains a SwissProt February 2023 database. Performs GO enrichment analysis on found homologs. Query database can contain one or more sequences embedded using makedb command. Again --thr can be used to specify an e-value threshold. --gothr can be used to specifiy different e-value threshold for GO enrichment analysis. searchsp produces a tab seprataed file .tsv This file can be converted into a .json file that can be used with the tool JSONWP using the command prost.py tojsonwp -i 'Here is an info string to shown on website' results.tsv website Here is an example result: Sequence alignment done automatically using the PROTSUB matrix which is better for aligning remote proteins then BLOSUM62 matrix. Protein structures are fetched from the Alphafold 2 database. No alignment produced this time.

Scripting

import pyprost

hpo30 = '''MPLIMYKFLLVTSIFLIVSGLILTAFSLFSPLWEVVDFPRSHLSHHHGLWWDCIVHHET
LIPLHEDQAELRGDRCDSKMDSSVQASLRVALEKGDEEARELLLHRFLPHHKGVIFFAVF
TFVFGLISILIGSCSPCFPPNALLYVVGVFMTGACSLLADIIYIFAFNQKPIFTKEQSEP
HQEVLSRRERGSIGPIYKRLGIATYMHMFGSMLLIAAFIFSIFCAYFLITSKHAHDVCCT
SRKEYREQTKWKNNGLILKTGRVNHQSHRPFVVIDDDSSM'''

clc2 = '''MSQAVSYAILVLTIIAFLLTAAALCTPAWQVVYAREIRQWVQSGLWLSCQTRPNGMYSCT
YTFSHDDFNTYFSDEVSGFRTPSFYPWQRTLFHIYLISQAFAMLSLISFCVSVSHKESKM
PNILRSVFLVLAAVIAFGCLIAFAVYSYMVEYRFFHVSVSGIYEKHRGYSWYIALTGAFV
YLVAIILSVVHVLLQARNSNTTMSRQNINSSLQSDFFEYQYHPNRSMESFEDRFAMRTLP
PVPRQEKKTTVF'''

hpo30embedding = pyprost.quantSeq(hpo30)
clc2embedding = pyprost.quantSeq(clc2)

dist = pyprost.prostDistance(hpo30embedding,clc2embedding)
print('HPO30-CLC2 prost distance:',dist)
#Should print: HPO30-CLC2 prost distance: 3479.0
#Distance smaller than 6875 may indicate homology

Resources

• Yeast analysis: https://mesihk.github.io/prostyeast
• Unannotated Human Proteins Analysis: https://mesihk.github.io/prosthuman
• Webserver: https://mesihk.github.io/prost
• PROST Python package: https://github.com/MesihK/prost
• PROST Research Data: https://github.com/MesihK/prost-data
• JSONWP: https://jsonwp.onrender.com/