top of page

Novel Therapeutic Peptide Design and Development 

Therapeutic peptides are a novel and promising approach for developing anti-cancer agents, anti-viral, anti-bacteria, anti-fungi, and other infections or diseases. They are small in size, easy to synthesize, and can penetrate cell membranes or act by binding to specific cell surface receptors, where they trigger intracellular pathways. Therapeutic peptides are known to show great potential in treating many diseases.

 

We will use a series of modern computational techniques including machine learning to discover novel therapeutic peptides from any biological sources against your desired target of infectious disease and take a step further to do wet lab experiments in other to validate the in-silico discovery. 

Research Workflow/Analysis

Stage 1

  • Aim and Objective of your therapeutic research project with your therapeutical focus (Anti-CP e.g. Breast cancer, Anti-viral e.g. HIV, Antimicrobial e.g. Skins diseases by Staphylococcus sp.)

  • The category and classification of therapeutic peptide (one or more) to use

  • ·Peptide sources (Microbial, WGS, or Metagenomics), plant, Insect, or Animal)

Stage 3: SDD Analysis

  • Identification of drug targets from known microbiome causing infection or disease such as breast cancer, diabetes, etc. 

  • Retrieval of protein/enzyme structure. 

  • Identification/retrieval/construction of chemical compound libraries. 

  • Molecular docking simulations of peptides, drug targets,s and known drug compounds

  • Protein-peptide interactions analysis ( 2D and 3D plots) 

  • Binding free energies calculations

Stage 5: 

  • Computing data and visualization of the results: (Statistical visualization which includes heatmaps, tabular, Venn diagram, bar charts, clusters, etc.)

  • Report (Materials and Method, Results and References)   

Stage 2

  • ·Extraction of the peptide/protein from databanks or sequence samples 

  • ·The design and construction of two categories of novel therapeutic peptides as an Anti-CP

  • Phytochemical properties of Anti-CP

In silico prediction of structure & function of the peptide:

  • Experimental Verification of peptide using BLAST

  • Half-life prediction

  • Predicted peptide toxicity

  • Peptide structure (Secondary Structure, 3D, and Molecular formula)

  • Function prediction

Stage 4: In vitro Experiments

  • 1. Peptide Synthesis

  • 2. Cytotoxicity assay (MTT assay) against 4 cancer cell lines and one normal cell line

  • 3. Apoptosis and necrosis detection assay (Annexin/PI assay)

  • 4. RNA expression analysis of a known apoptosis marker and Analysis

The workflow as we have shown you entails the steps of bioinformatics analysis to be carried out for your data and each is unique to the workflow designed for the final outcome. 

The analysis will be conducted providing your desired visualization for each major steps

 

The following will be provided after the complete job is done.

  • A detailed draft of a report containing the materials and methods, results, and references

  • Visualizations (figures)

  • Technical support: A live zoom session will be held to explain and discuss the results with you. 

Get In Touch

You can book a free session with us to discuss what you want to do, your research project, and show you a demo report. We promise to deliver accurate and trusted work done.

bottom of page