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European Biopharmaceutical Review

Target Practice

Developing a safe, efficacious drug that is the first of its kind to reach the market is the major goal of pharmaceutical R&D. In the decade to 2008, almost two thirds of the first-in-class new molecular entities approved by the Food and Drug Administration were discovered using phenotypic screening approaches, despite widespread industry focus on target-based discovery (1). In contrast to screening against isolated targets, phenotypic drug discovery allows multiple, often unknown, but biologically-relevant targets and pathways to be investigated simultaneously. Molecules are then selected based on their functional effects on disease-relevant cells, tissues, or even whole organisms.

Mechanism of Action

This hypothesis-free approach arguably provides a better indicator of efficacy as the initial selection is based on activity observed in the context of human disease. Discovery – or deconvolution – of the actual target or receptor for a particular molecule occurs later, although it has already been assumed that the target is likely to be linked to biological response and that it is inherently druggable. As a target has not been pre-selected there is an increased chance of it being novel, or of the drug lead displaying a new mechanism of action. Both of these scenarios could provide a real competitive advantage in pharmaceutical research, especially considering that the first party to discover a disease-relevant target may be entitled to protect their intellectual property (IP).

However, at this early stage, researchers still have little or no understanding of the molecular mechanisms underlying the observed phenotypic activity. Although it is technically possible to gain regulatory approval for a drug that is safe and effective without knowing the target, receptor deconvolution is critical, for optimising the best leads, securing any IP on a novel target, as well as providing valuable information which could support regulatory submission.

As phenotypic screening has the potential to uncover a new, disease-relevant target, as well as a promising drug lead, it is increasingly
being used to complement the traditional target-led approaches, both in biologics research – for the discovery of phenotypic antibodies – and for small molecules.

Target Deconvolution

Target deconvolution is a well-recognised bottleneck in the progress of phenotypic drug development due to the inefficiencies in the technologies that have been available to researchers. Until recently, traditional biochemical and proteomics approaches, such as ‘pull-down’ assays coupled with mass spectrometry, typically yielded only a 10 per cent success rate in identifying binding partners for molecules of interest. Furthermore, confidence in the results can be limited as, even if primary targets are identified, secondary targets which could point to potential undesirable or toxicity effects could easily be missed or underestimated.

Traditional approaches have such low hit rates because they often do not provide a natural environment for interactions to occur with fully-formed proteins. Moreover, they are not optimised for pulling out the plasma membrane receptors that are the most relevant target class when studying either small molecules or phenotypic antibodies. However, recent advances in cell microarray technology have increased the success rates for identifying human plasma membrane protein targets to over 60 per cent, while also allowing for the scale-up required to keep up with ever-more sophisticated and higherthroughput phenotypic screening initiatives.

New Systems

Cell microarray systems provide a physiologically-relevant environment for phenotypic molecules to interact with full-length human membrane proteins which are expressed in their native form in the context of human cells (see Figure 1, page 72). This allows for normal trafficking to the cell surface, correct folding in the plasma membrane and natural post-translational modification. As such, the system is extremely wellsuited to cell surface proteins and receptors, which are the main targets for phenotypic antibodies and small molecules.

Currently, more than 3,500 proteins can be individually expressed at the same time in the cell microarray system. This represents more than 65 per cent of known human plasma membrane proteome, accounting for the high probability of rapidly identifying specific, disease-relevant targets. The broad coverage extends across the full spectrum of known plasma membrane protein sub-classes, including G protein coupled receptors (GPCRs), ion channels, drug transporters, cytokines and growth factor receptors, among many others (see Figure 2).

The cell microarrays are produced from a library of expression vectors containing open reading frames (ORFs) encoding full-length human plasma membrane proteins and green fluorescent protein (GFP). Around 75 per cent of the ORFs included in the cell microarrays are unique genes – the remaining 25 per cent are alternative variants of the same genes and have been selected to represent variants in extracellular domains.

Each expression vector is combined with a lipid, and the complexes are spotted in distinct locations on glass slides ready for reverse-transfection of human cells. The result is over-expression of the respective membrane proteins – plus GFP – in cells which directly overlay each expression vector. The GFP acts as a transfection control, as well as marking out spot coordinates for the microarray slides. The phenotypic antibody – or other ligand of interest, such as a small molecule, virus or other protein – is applied to the cell microarrays and allowed to bind. Its putative receptor targets are identified by analysing ‘gainof-binding’. Further tests then determine which receptor hits are specific and reproducible.

Cancer Therapeutics

A variety of assays and methodologies to select for phenotypic antibodies are being used to great success, particularly in the development of novel cancer therapeutics. These range from using antibody phage display libraries to selecting against disease cells or patient tissue, through to whole systems approaches of isolating antibodies from human cancer patients or animals that have been inoculated with a tumour to evoke a full antibody response. Exploiting the disease system, rather than focusing on a single isolated target, increases the likelihood that a drug lead will be relevant to a complex and multi-factorial disease such as cancer.

Regardless of which route is taken for phenotypic discovery, they all converge on target deconvolution. Therefore, it is essential that the technology is versatile to accommodate a range of ligands and detection systems, in addition to being scalable. The cell microarray technology can process up to around 100 molecules simultaneously. This is achieved by pooling all the test proteins together for an initial round of screening to quickly identify all proteins targeted. Subsequent screening rounds then isolate the targets which are specific to each ligand, allowing for high throughput with no detriment to the quality or the specificity of the final results.

Antibody Molecules

In the case highlighted in Figure 3, 20 antibody molecules were selected following phenotypic screening. These were pooled and applied to the cell microarrays pulling out multiple initial hits. The specificity of these hits to each ligand was then confirmed, leading to the identification of specific cell surface targets for the majority of the phenotypic antibodies in the study. This provided crucial information for the researchers who commissioned the work, allowing them to prioritise the best candidates, as well as providing new data on disease-relevant targets. Interestingly, a proportion of the targets that were ‘discovered’ using this approach were previously known.

Shedding new light on existing targets increased the value of those targets, but also validated the whole phenotypicbased approach by confirming its ability to pull out relevant drug leads. More significant, however, was the identification of several promising drug leads, along with matched, novel, disease-relevant targets, which can now be optimised in order to develop new drug classes and exploit the IP generated.

Crucial Insights

Advances in target deconvolution using human cell microarrays allow researchers to maximise the increasing opportunities that are arising from the successes of phenotypic screening programmes. Efficient target deconvolution aims to not only discover the primary target pathways for molecules of interest, but also uncover secondary/off-targets, providing crucial insights into potential additional functionality or possible toxicity issues at a very early stage.

Although not all phenotypic molecules will progress through drug development – and fewer still will make it to market – the exercise of target deconvolution furthers our understanding of the molecular mechanisms of disease and provides valuable information to complement target-based approaches, opening up other avenues for researchers to explore. As the discovery of novel, druggable targets presents a major competitive advantage, many pharmaceutical companies are now taking a multi-track approach in the search for innovative drugs to boost the development pipeline.

References
1. Swinney DC and Anthony J, How were new medicines discovered? Nature Reviews Drug Discovery 10(7): pp507-519, 2011

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About the author

Jim Freeth is Managing Director of Retrogenix, having co-founded the company in 2008. This followed over 10 years of experience in management within the biotechnology and pharmaceutical industries. He is a biologist by training and obtained his PhD at Manchester University, UK, in 1997. Jim has had a long-standing involvement and interest in phenotypic drug discovery and target deconvolution.
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