Digital Signal Processing Techniques:Calculating Biological Functionalities
Norbert Nwankwo* and Huseyin Seker
The Bio-Health Unit of the Centre for Computational Intelligence, De Montfort University, Leicester, United Kingdom
- *Corresponding Author:
- Norbert Nwankwo
The Bio-Health Unit of the Centre for Computational Intelligence
De Montfort University
Leicester, United Kingdom
E-mail: [email protected] or [email protected]
Received Date: September 20, 2011; Accepted Date: November 03, 2011; Published Date: December 01, 2011
Citation: Nwankwo N (2011) Digital Signal Processing Techniques: Calculating Biological Functionalities. J Proteomics Bioinform 4: 260-268. doi: 10.4172/jpb.1000199
Copyright: © 2011 Nwankwo N. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Calculating Biological functionalities of proteins and presenting them numerically is an approach that will benefit the designing of drugs and vaccines. For example, potency of vaccines is known to be measured in terms of specificity, which is determined by bio-recognition (affinity), and sensitivity. Calculating the bio-recognition of peptides employed in the design of vaccines by means of procedures like the Digital Signal Processing (DSP) techniques rather than clinical experimentations not only gives room for the manipulation of the amino acids sequences of the peptides but also helps determine the degree of specificity of the antibody generated, hence the potency of the vaccine produced. This also provides opportunity for optimatization of the peptides for the desired biological characteristics. Also comparing the potency of peptide-based drugs through calculation of their biological functions is a faster, easier and resource-saving approach to pharmacotherapeutic investigations. In this study, two DSP techniques are fully explained and demonstrated. They are Resonant Recognition Model and Informational Spectrum Method. They are employed in the calculation of some physiological characteristics of Plasmodial peptides (P18 and P32), which are still being study for possible use as materials for the designing of anti-Malaria vaccines. Furthermore, the approaches are utilised to assess the pharmacological activities of two Fusion inhibitors (Enfuvirtide and Sifuvirtide). Enfuvirtide is currently in use for the management of anti-HIV/AIDS while Sifuvirtide is still being studied. Our calculated results demonstrate strong correlation with the preliminary clinical findings. They also seem to suggest that presenting biological characteristics in numerical terms is an easier and more rational approach to designing drugs and vaccines as it save resources and time unlike clinical experimentations. The methods also appear to help simplify the manoeuvring of the protein residues, which are employed in the designing and development of drugs and vaccines in order to obtain maximal biological characteristics.