Stress: Plant Protein Database
        PSPDB: Plant Stress Protein Database
BioTools embedded with PSPDB Content 

When user clicks or opts for Biotools from the main menu by clicking ‘Tools’ the PSPDB system reach the following page. Tools (BLAST, ClustalW, and Hmmer are integrated to the PSPDB database system.



BLAST (Basic Local Alignment Search Tool) is a sequence similarity tool designed to scan a database for similarities to a target sequence. Blast accommodates both protein and DNA sequences. Copy your sequence/sequences into the space provided [below the “Enter your sequence(s) in FASTA format” heading]
Alternatively upload your sequence sequence file using the ‘Browse’ button. Now click the ‘Run Blast’ with QueryProfile button to generate sequence matches/hits. Under the Blast heading select whether you wish to Blast your sequence/s against the whole PSPDB database or only against Uniprot-Swissprot or Uniprot-TReMBL. Under the ‘View Options’ heading select how you wish to have the results displayed. After making your choices click the ‘Run Blast’ with ‘QueryFile’ button. To start a new Blast search click the ‘Reset’ button Blast focuses on local alignment, that is, it focuses on matching fragments or portions of a sequence as opposed to taking the entire sequence into consideration. Hence those sequences [in the database] with significant areas matching the users sequences are aligned and displayed to the user.
These results or hits are based on a similarity score which exceeds some “threshold value”. Hence Blast is able to detect “relationships among sequences that share only isolated regions of similarity” (Altschul et al.1990).




CLUSTALW is a multiple sequence alignment program which can align large amounts of protein or dna sequences.
Copy your sequence/sequences into the space provided [below the “Enter your sequence(s) in FASTA format” heading] Alternatively upload your sequence sequence file Now click the ‘run ClustalW button’ to generate sequence matches/hits A phylogram is automatically generated and by right-clicking on the phylogram, it can be saved in the pdf format. To start a new ClustalW search click the ‘reset’ button
It takes a sequences/sequence file containing the target sequences and then computes the best alignment for them. The sequences are then lined up so that their “identities, similarities and differences can be seen”. In turn the sequence alignment is then used to generate a Phylogram where evolutionary relationships among the sequence families can be seen.



Hmmer is an alignment tool which uses the Hidden Markov Model (HMM) algorithm to analyse sequences and generate a protein domain profile. HMMer has two parts: 1) Build a profile 2) Query a profile

1) Build a profile To build a profile you have to enter more than one sequence Copy your sequences into the space provided [below the “Enter your sequence(s) in FASTA format” heading] Now click the ‘build a profile’ button to generate a profile At the bottom right-hand corner [of the page] a dropdown list appears. There are two options, namely, ‘use profile’ & ‘view profile’ Select ‘view the profile’ to view an analysis of the profile generated. Select ‘use profile’ to use it as a basis for identifying whether a sequence belongs to the profile.

2) Query a profile Continuing from the above section, after having built a profile, select ‘use profile’ and click the ‘submit’ button. The user is automatically taken to the ‘Query a profile’ page. Now, enter your sequence and click ‘Query profile’ Alternatively, the user can use one of the Stress’s profiles to analyse a sequence. In the latter case, the user goes straight to the ‘query a profile’ page and enters a sequence. Next select a profile from the dropdown list and click ‘Query profile’ The profiles are mapped against a database/s to search for the presence of those domains in [the database]. HMMs are particularly useful when dealing with large amounts of data, that is, hundreds/thousands of sequences. Large amounts of data improve alignment accuracy and impact positively on database search sensitivity as the algorithm has a larger data pool to generate its predictions.