Companies are beginning to develop imaging technologies to study GPCRS.
Drug Discovery & Development magazine conducted a roundtable discussion with industry scientists to answer questions about GPCR. Below are the answers to a question related to the development of imaging systems to study GPCRs.
James Netterwald: Dr. Eglen mentioned that PerkinElmer is starting to work on some imaging technologies to study these proteins. So with imaging, are you looking at live- cell assays or are those cells preserved in some way?
Richard Eglen: The technologies we’ve developed will work for both of those sorts of experiments. One experiment is a fixed cell preparation when one looks at changes in the location of GPCR and associated proteins by various immunostaining procedures. Others are live-cell assays where one is quantifying the amount of protein translocation that would occur as a result of the GPCR activation. The obvious one being the translocation of beta-arrestin, either to the GPCR or association of that GPCR-arrestin complex into the cell cytoplasm once the receptor has been activated. I think the whole point about the imaging side of things is, firstly, that the responses can be quantified and used in a high throughput screening system. But the other point may be that some of the groups that we’ve collaborated with are starting to detect interactions with other proteins and not necessarily the obvious ones such as beta-arrestin. So these may involve kinases, or various ramps, or other sorts of receptor-modifying proteins that interact with a receptor once it’s activated.
The flip side to this approach is not looking at the way in which the receptor associates with protein using imaging, but simply looking at changes in the cell phenotype that occur once the receptor’s been activated. A clear case for this, for example, is activation of a chemokine or cytokine receptor in response to the HIV virus and quantifying phenotypic changes in the cell once the virus has been activated. This approach appears to be an emerging field, and is certainly opening up other ways to look at cell surface proteins such as GPCRs.
Charles Lunn: I think one of the big problems is the massive amount of subtle information that you accumulate as organic compounds interact with cells. This is a problem in HTS laboratories seeking “yes/no” answers for compounds in our library. Also, most current imaging assays are relatively low throughput, able to handle relatively few compounds per day. As computational systems improve, and our design of imaging experiments get better, I do believe high throughput imaging will find their way into screening labs. Again, if the cells being analyzed mimic target biology, there is much information that we can generate for each individual compound.
Eglen: Yes, I think that’s a fair point. I think one of the things we’ve seen starting to emerge … is the way in which there are now discrete cell phenotypes being associated with discrete effects of the GPCRs. So there’s a correlation coming [out] now. Many of the computer algorithms can speed up that kind of analysis. Of course, if you’ve got a single protein interacting with your GPCR of interest, then the analysis becomes much more straightforward, because one is now simply analyzing one response as opposed to the whole cellular response. It is amazing how many proteins actually interact with GPCRs once they’re activated. Clearly, what we’ve seen in simple biochemical assays in particular is the tip of the iceberg, in terms of the whole pathway activated by the receptor.
Netterwald: So is there an interest to improve the throughput of these live-cell imaging assays?
Eglen: Some of them can be very fast. A high throughput confocal imaging system can perform at very high speeds. That does generate a very large amount of data. And that data needs to be carefully managed and archived, and analyzed using very discrete algorithms. So I think for some labs that are doing HTS using confocal imaging, the speed is already there. I think the issue’s going to be the analysis—interrogation as Charles said—of the data that is generated. Fortunately, there are going to be imaging and archival systems now coming online that should make that task easier.
Lunn: Again, success will be based on the host cell background that you are testing. If the host cell background adequately reflects the biology of the GPCR in the human organism, then these approaches will be extremely valuable. The task of validating your assay to guarantee that your assay adequately mimics the human organism is daunting. Most programs progress on a hope and a prayer, and then biologically validate the compounds from the screening assay. We would be more successful if we had a better understanding of the relevance of host cells we use for screens.
Netterwald: But doesn’t the live cell aspect make it more physiologically relevant, as opposed to a biochemical assay?
Eglen: I think that’s the presumption. I mean, to Charles’ point, it does in a cellular environment. But then the question is … which cell? For example, if you’re looking at behavior of a cannabinoid receptor on a neuron, how does that behave on a human neuron, relative to a cannabinoid receptor on a CHO [Chinese Hamster Ovary] cell. That’s a very relevant point in terms of once you’re in the cellular world, making sure that cell phenotype corresponds to a human condition is key. With some cell types, such as lymphocytes, it’s very straightforward. With the more difficult-to-study cell types, such as neurons, then perhaps it’s a lot more complex. This has been one of the advantages being hailed about label-free technologies—that one looks at the response of the cell via a signal that doesn’t involve any labeling, and there’s a holistic effect of looking at the total cellular response. I don’t know if the other two gentlemen have comments about label-free approaches to GPCRs, but that’s been hailed as one of the advantages.
Suresh Poda: This is one area I think many people are looking into. The reason being we have been using these heterologous systems for quite some time. [Until] now, we haven’t had any technologies to substitute. Now at least there are a lot of label-free technologies available for GPCRs. We evaluated some of these technologies. We are very pleased with our initial data coming from label-free technologies. The pharmacology we generated using these label-free technologies are quite similar to the ones we got from FLIPR-based cell based assays. In these assays, the proteins are expressed at normal physiological levels, and they are coupled to their primary signaling, you get more biologically-relevant data than heterologous systems. This is one area that is emerging.
Lunn: I think that’s true. And, as the throughput becomes higher for these no-label platforms, they will become of greater interest. No-label assays tend to be easier to establish because less time is spent optimizing ligands. These systems can also identify unexpected phenomena caused by the test compound. Therefore, no-label assays may detect biology that you may not see using standard pathway assays to interrogate your receptor. These platforms will become more valuable as screening tools.
Netterwald: So is it true—and is it correct to assume—that for the GPCR field, drug companies are going after sort of a more natural or physiologically-accurate approach to study these proteins because of what you’ve mentioned with regard to looking at live-cell imaging and label-free platforms. Would you say there is a greater trend to looking at the natural state of the protein?
Poda: Yes, I agree with you. This is actually a trend across the industry. I think people are looking more into the native state of cells. Also, we don’t want to manipulate cells that much, so ideally, we would like to screen our targets in a normal physiological condition.
Eglen: To some extent, it is a bit of an evolution—in terms of looking at GPCRs—that’s almost gone full-circle. When they were first looked at, particularly as significant drug discovery targets, even as late as the 1960s or 1970s, whole tissues were in fact used to analyze the pharmacology of the ligand-GPCR interaction. And they led to some very successful therapies being developed that were based upon the GPCRs. So I think it’s always been understood that this kind of thing gives you a more physiologic response to the drug in question. I think the goal of the technology has always been how to develop this in practice in terms of enabling very large compound libraries to use with these kinds of screening systems, with a completely unambiguous response that gives very good structure-activity relationships. An area that we think is developing quite rapidly—and I don’t know whether it has hit screening in drug discovery yet, but it has hit basic academic research—is the use of stem cells, and bringing stem cells, particularly ones that can be induced from pluripotent stem cells, to providing enough of a reliable and reproducible amount of cells that can be used in drug discovery, in general, and [for] GPCRs, in particular.
Filed Under: Drug Discovery