Target deconvolution for phenotypic antibodies and small molecules

Remove the target deconvolution bottleneck

 

The Retrogenix Cell Microarray Technology is ideally suited to target deconvolution. Specifically, it is used to identify the primary targets of large or small molecules that display a desired biological or clinical effect. This ranges from uncovering the primary target of antibodies or small molecule compounds identified by phenotypic screening, right through to marketed drugs where the mechanism of action has not been fully elucidated.

Given that antibody targets are predominantly plasma membrane proteins, and that antibodies require no direct labelling, our microarray technology is used extensively for the antibody target deconvolution.

Discover:

  • novel, druggable targets
  • receptors targeted by phenotypic molecules (antibodies, ScFvs, Fc-fusion proteins etc)
  • disease-specific antigens by direct screening of patient plasma samples

Phenotypic Drug Discovery Process

The phenotypic drug discovery process

Unrivalled success rates in target deconvolution

To date, Retrogenix has identified specific, reproducible primary target receptors for 60-70% of the phenotypic molecules that have been screened. This includes projects on ‘difficult’ molecules where extensive in-house target deconvolution efforts have failed to find any specific hits or have identified many false postives. This success rate is unrivalled by other techniques and is due to our extensive collection of membrane proteins that are expressed in the context of the human cell.

Phenotypic screening is a powerful approach that can identify potential therapies by selecting for disease-relevant binding and/or functional properties of molecules. The nature of phenotypic screening means that any novel targets discovered are likely to be disease-relevant, inherently linked to a desired biological effect and druggable. Although, in theory, knowledge of the target receptor is not necessary to the development of a successful therapy, it is still fundamental for informing lead optimisation and is essential in protecting the valuable intellectual property (IP) around that target.

High specificity

Retrogenix produces a low rate of false positives ensuring that months or even years of research are not wasted chasing dead ends when validating potential target hits. Target deconvolution using Retrogenix typically results in one or two reproducible hits that are specific to the test molecule and generally represent the primary receptor target and its different isoforms.

 

Scripps study uncovers novel CLL drug target

A previously unreported cell surface antigen provides a promising new immunotherapy target to treat patients with chronic lymphocytic leukemia (CLL). The target, Siglec-6, was identified using Retrogenix cell microarray screening after attempts to uncover the antigen by immunoprecipitation and mass spectrometry proved unsuccessful.

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Case Study: Target deconvolution

Find out more about how Retrogenix is advancing phenotypic drug discovery with our MedImmune case study.

Scientists used 3-D phenotypic screening to select novel antibodies that were functional against primary tumour cells. The Retrogenix technology then identified the specific cell surface antigen targets of the most promising phenotypic molecules…

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Pfizer
The University of Sheffield
Aveo Oncology - The Human Response
Theraclone Sciences
BioInvent
AstraZeneca
Bluebird Bio
The Center for Infectious Disease Research
Compugen Logo
The University of Copenhagen
Lund University
MedImmune
NIH - National Institutes of Health
The University of Pennsylvania
Scripps Florida - The Scripps Research Institute
Peptinnovate Ltd - Unlocking Nature's Potential
…working with you was exactly like working with an experienced and knowledgeable scientific collaborator. We had the same types of discussions and strategic planning sessions and I felt confident throughout that we were addressing the issues in the best way possible. It was fun and if I see the opportunity we would do this again.
Professor Mark Kahn, University of Pennsylvania