Our aims

Our goal is to achieve the highest quality of service and support possible for all users. We also aim to keep our services:
  • At the cutting-edge of in silico protein analysis.
  • Relevant to scientists' needs by constructively responding to feedback.
  • Accessible and easy to engage.

The bigger picture

From genome to proteome TO IMMUNOME

Genes encode proteins. The exponential increase in genetic information from global genome sequencing efforts, is producing a vast wealth of protein sequence information, which emphasises the importance of proteomics, the study of an organism's proteome, and especially in the areas of diagnostics, therapeutics (more than 95% of drug targets are proteins), and cell and molecular biology. The exponential increase in the number of protein sequences and solved 3-D structures recently has received a colossal boost through the addition to public protein structure databases of a vast number of protein structures generated ab initio from protein sequences using vastly improved AI approaches. This generates the need for a greatly increased number of new antibodies for use as key analytical tools in areas including:
  • Protein structure, function and activity.
  • Protein expression and location.
  • Protein interaction with other macromolecules and small molecules.

Further increases in the number of different proteins for investigation occur as a result of:

  • Post-translational modification of proteins in cells.
  • Proteins with multiple functions (in the same and different cells) that may be regulated by post-translational modification.
  • Cell, tissue and individual variations in a protein's structure, function and activity that occur as a result of innate and acquired differences in genome coding and non-coding sequences.
Global genome sequencing efforts have also generated large amounts of immunologically relevant data deposited in immunological databases.


Immunoinformatics utilises structural biology, immunology, and bioinformatics prediction and analysis tools and database resources for the enhanced design and development of:

  • Epitope-targeted biotherapeutics.
  • Diagnostic monoclonal antibodies.
  • Prophylactic or therapeutic vaccines targeting pathogens, and to transform vaccine development through use of increasingly rational vaccine design.
Immunoinformatics tools and resources are also used to advance knowledge in the areas of immunology and vaccinology, for example, to improve understanding of the induction of an immune response by vaccines.


Recent advances in immunoinformatics and the availability of databases and a diverse array of tools for identifying therapeutically relevant epitopes have profoundly enhanced research into the development of novel epitope-based vaccines, increasingly a cornerstone of modern vaccine development.

Vaccinology approaches utilising immunoinformatics tools and resources include:

  • Structural vaccinology - characterising the 3-D structure of an antigen and using this knowledge to design a vaccine that structurally mimics the antigen in its original setting in order to induce a protective antibody response.
  • Reverse vaccinology - uses a genomic sequence of interest as the starting point for antigen identification and epitope targeting.
  • Systems vaccinology - vaccine candidate prediction using bioinformatics tools, with genomics, transcriptomics, proteomics, metabolomics, and immunomics at its core.
  • Proteome-wide identification of epitope-based vaccine candidates.
  • In silico vaccination.
  • Immune system modeling.


Antibodies play an essential role to protect against infectious disease. The development of effective vaccines and therapeutic antibodies targeting pathogens remains challenging. Nearly all vaccines in routine use are thought to confer host protection through the induction of pathogen-directed antibodies. Monoclonal antibodies are used for the prophylaxis of infectious pathogens, and vaccines and immunotherapeutics will continue to be needed for the prophylaxis and treatment of diseases caused by infectious agents (emerging and re-emerging), potential bioterrorism agents, including naturally evolving or intentionally engineered therapy-resistant variants.

Enhanced antibody and vaccine design will flow from the now very real possibility of accurately predicting pathogen protein structures using the vastly improved AI approaches AlphaFold and RoseTTAFold. These new tools provide very quick analysis compared to experimental protein structure determination and will be invaluable for countering emerging pathogens in future pandemics. However, there remains deficiencies in knowledge regarding how antigen sites elicit immunity, for example, which epitope structures are most immunogenic.

Increasingly important is being able to identify protective B cell epitopes, regions on pathogens that bind to the variable regions (CDR regions or paratopes) of protective antibodies. Knowledge of protective epitopes, such as those of a pathogen targeted by patients' broadly neutralising (protective) antibodies, can lead to:

  • Development of antibody therapeutics.
  • Development of diagnostic assays for monitoring the strength and quality of protective antibody responses in vaccinated, infected or prophylactically treated individuals.
  • Identification of pathogen function that could be targeted by novel therapeutic molecules (antimicrobials).

Additionally, knowledge of protective epitopes can guide design of a vaccine that aims to:

  • Induce a broad immune response that includes broadly neutralising antibodies targeting conserved regions of a pathogen.
  • Excluding epitopes that might induce host autoimmunity, and/or enhance infection by the same or another organism (ADE: antibody-dependent enhancement).

The role of Epitope Informatics

Our goal is to promote and enhance antibody-centred investigation through offering services for the identification, analysis and targeting of antibody epitopes present at the surface of proteins. Although this may change, currently our view is that epitope discovery remains best performed treating target proteins on a case-by-case basis, using a consensus in silico approach for targeting epitopes. Value is added to target protein sequences and structures through their annotation with findings from consensus epitope prediction and epitope contextual analysis.

Future goals

Longer term aims for Epitope Informatics include:
  • Develop enhanced protein analysis platforms using datasets enriched with AI-derived protein structures.
  • Develop novel platforms and immunoinformatics tools for computational vaccinology.
  • Being an educational facility for undergraduate and postgraduate students seeking to pursue a period of time in industry as part of an intercalated degree course. In this situation, Epitope Informatics would aim to provide a supportive and stimulating, high quality teaching and learning environment for the pursuit of research project work in the areas of computational biology and pure and applied bioinformatics.