Bioinformatics Protocols

Antisense peptides are used as potential ligands for protein-protein interactions studies. The bioinformatics protocols detailed on this website have been developed to allow in silico identification of novel protein-protein interactions to be carried out using software freely available to academics. The technology described is based on the idea that proteins coded by the sense and antisense strands of DNA interact. The attached Summary Protocol has specifically been written by Dr Nat Milton of Leeds Beckett University and NeuroDelta Ltd, who has used antisense peptide techniques for both academic research and commercial activities. The methods detailed in the protocol are aimed at undergraduate and postgraduate students plus academic staff for use in non-commercial activities. The main method is based around antisense peptide screening [1] and has been adapted to protein sequence database screening [2]. A combined step by step fully detailed protocol is available using the Full Protocol link and support for these Bioinformatics protocols is available directly via Email.


The protocol details how to use an online method (using a
Python script or Word version which can be used in an online Python Compiler or a downloaded version of Python 3) to generate antisense peptide sequences from a target protein mRNA sequence and has been based on the methods outlined in [2],[3],[4]. Methods using the antisense peptides in BLAST searches to identify potential protein interactions with the target protein are included. Simple methods for 3D modelling and analysis to predict the structure of complexes between the proteins identified from the antisense peptide screening can also be used. A 3D modelling method using the ZDOCK server to predict protein-protein interactions from protein structure files for two interacting proteins identified using antisense peptide BLAST searches [5],[6] has been detailed in the attached protocol. The interacting sequences identified from the BLAST searches are used as potential contact residues to direct the predictions in this method.

An example of the use of these techniques was a study to identify Alzheimer's amyloid-ß (Aß) binding peptides that could block both neurotoxicity and fibril formation of Aß. The binding peptides were developed based on generating antisense peptides using the messenger RNA (mRNA) sequence for the Aß 1-43 peptide as a template
[3],[4] that would specifically bind the Aß 1-43 peptide. The Aß antisense peptide sequences and data from their generation plus characterisation were the subject of published patent applications [4]. Subsequent studies by other groups demonstrated that similar Aß antisense peptides were able to prevent the toxicity of Aß [7], confirming the original observations.

Bioinformatics Protocol Support: