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6

You could use Blast2go to find the predicted relevant gene ontologies of your sequences. If you look for the cellular compartment sub ontology you should find the location of such protein. I have never used this tool, but here is the paper describing how it works. I wouldn't restrict to the first predicted match of blastp see if some more genes with a good ...


5

You can use these options: blastp -query my.faa -db VFDB.fas \ -perc_identity 50 -outfmt 6 \ -evalue 10e-5 -out results.txt Then select the 5th column, qlen, and the 13th columns, slen, and get the percentage higher than 50. awk -F'\t' '{ if ($NF >= 50) printf "%s\t%.2f\n", $0 , ($2/$5)*100 }' result.txt Check the documentation for the ...


4

The answer is it depends. 40% pident with ~100% qcovs (assuming length of protein is not very small) tells you that the virulence factor (VF) and your prokka predicted protein are likely homologs, they belong to the same (or closely related) protein family. For some research studies, you might annotate your prokka proteins as 'putative' VFs. On the other ...


4

It sounds like your easiest option is to just install blast on your local machine and set up the databases there. It really will only take a few minutes to blast 6,000 sentences against a yeast genome on a modern laptop. Any solution interfacing with web results or parsing the output will be painfully convoluted. There are executables for blast that will ...


3

The NCBI BLAST can be used with the PDB DB (which NCBI has). The PDB codes are stored as 4 letter codes underscore chain, e.g. 1GFL_B. The catch is segment identifiers —but generally they are the same peptide so shouldn't be an issue. You can search specifically the PDB DB in NCBI (not the RCSB PDB) by setting the database to PDB.


2

You can run the sequence through tools like SignalP to look for cell surface signals and so on, which will give you a clue about where I is bound for. None of these tools will give you an absolutely definitive answer though, often because we simply don’t have the experimental data.


1

You should increase the -evalue 10 default option to a higher value because this value it's adjusted to the sequence database size. Check this table, maybe this can help you to decide which parameters are the best option for you. OPTION TASK DEFAUL DESCRIPTION word_size blastp 3 Word size of initial match. ...


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