High-Throughput Screening: Using a More Intelligent Approach for Hit Discovery
High-Throughput Screening: Using a More Intelligent Approach for Hit Discovery
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High-throughput screening (HTS) is a well-established part of drug discovery which involves the use of automated equipment to rapidly screen large libraries of small molecules to identify compounds (called hits) with activity against a biological target.
“High throughput screening is not feasible without some kind of robust and low volume assay,” says Catherine Kettleborough, head of biology at LifeArc, a medical research charity that supports translational research. “We do everything in 384-well microtiter plates, but it’s possible to take that down further to 1536-well formats.”
HTS is commonly the first step in the search for active compounds with the potential for further development into a candidate drug – or chemical probes to help advance biological research.
“If you’re working on a very novel drug target, there may be very little precedent on how to develop a screening assay,” explains Kettleborough. “And so the intermediate step might be to try and find something that binds to it to use as a tool to get a handle on it.”
In recent decades, the focus has been on boosting HTS capacity through increased automation, miniaturization and large-scale data analysis.
“In large-scale industrial facilities it’s now possible to screen many hundreds of thousands – or even up to a million compounds – per day,” says Matthew Lloyd, senior lecturer in pharmacy and pharmacology at the University of Bath.
But academic researchers, who may have budget constraints or limited access to full HTS facilities, are turning to more intelligent screening strategies.
Rapid MS/MS Analysis With Acoustic Ejection Mass Spectrometry
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Screening for chemical starting points
The search for compounds with activity against a promising new drug target – such as an enzyme involved in a disease-critical pathway – will often begin by screening libraries containing several thousands of compounds, with the help of HTS technologies. The first step is to design a suitable in vitro assay that can reliably measure the desired change in function.
“For example, you might be looking for a compound that can block the activity of a target enzyme,” explains Lloyd. “In these cases, the most common approach is to set up a fluorescence-based assay measuring product formation and looking for a detectable drop in the signal that indicates enzymatic inhibition.”
Although the type of assay used in HTS will vary depending on the target, it needs to be simple enough to be miniaturized and automated. Other readout methods include detecting a change in color or luminescence or may involve more complex approaches such as mass spectrometry or cell-based assays.
An analysis of recent HTS campaigns for the discovery of enzyme inhibitors showed that the hit frequency was largely independent of library size but was linked with the Z’ value for the assay, a statistical measure for how easy it is to find a hit.
“You might expect a hit rate of between 0.5 and 1 percent with a typical HTS assay,” says Lloyd. “But some targets are more difficult – and you might end up with less than 0.1 percent.”
MTT Cell Proliferation, Viability and Cytotoxicity Assay
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Refining the hit list
While false-negative results are lost opportunities, false positives can lead to wasted time and resources – with the numbers becoming particularly problematic when screening large compound libraries.
“Many compounds in libraries are small, organic and not very water-soluble,” says Lloyd. “These compounds tend to form aggregates that can interfere with the ability of the enzyme to break down the substrate, leading to apparent inhibition.”
This inhibition is heavily dependent on the assay conditions and is typically reduced by the presence of a detergent, such as 0.01% Triton X-100. But increasing the level of detergent to 0.1% may be needed for full suppression of aggregate formation, which can help to eliminate many of the false positives in follow-up assays.
“If you’re then only left with a few tens of hits, which might be typical in a small screen, then it’s probably feasible to do a dose-response curve on all of them,” says Lloyd. “But if you’ve still got many thousands you might need to carry out more assays to whittle them down even further.”
The overall goal of HTS is to narrow a shortlist of active hits to move into hit-to-lead optimization, which involves making small adaptations to the chemical structure to generate series of closely related compounds for further testing.
“At this stage, medicinal chemists will need to examine the structures of any remaining hits to assess if it’s worth progressing any further,” says Lloyd. “A compound will need to be synthetically tractable so that it’s possible to generate a series of analogs for further testing.”
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Quality over quantity
While industrial laboratories can screen libraries containing vast quantities of compounds to identify hits, academic researchers may need an alternative strategy more well-suited for laboratories with limited resources.
“This requires screening smaller, more refined compound libraries,” says Kettleborough.
An example is the representative LifeArc index set, a clustered collection of around 10,000 drug-like compounds that have been compiled from the charity’s larger diversity collection of around 150,000 compounds. The library is available for sharing with academic groups around the world.
“It’s almost a one-stop-shop for academic groups – saving them the cost of buying a bigger compound collection,” says Kettleborough. “After identifying an initial hit in this small set, they can then get hold of analogs from associated clusters within our larger diversity collection for rapid follow-up.”
The index set has been carefully designed to increase the chances of identifying chemically tractable hits while maximizing chemical diversity. A big challenge is around selecting high-quality compounds – both to avoid false positives in HTS and investing time and resources on hits that are likely to be eliminated at a later stage.
“We initially use computational approaches to select compounds based on the chemical space that needs to be filled, we then share those structures with medicinal chemists for a sanity check,” says Kettleborough. “We then only add in those molecules that are independently approved by two chemists as having at least a reasonable chance of progressing to the next stage of drug discovery.”
Screening the LifeArc index set in conjunction with hit analog follow-up provides a good chance of identifying a compound that has the potential for further development.
One example of applying this more cost-effective screening strategy is searching for new small molecule inhibitors of alpha-methylacyl-CoA racemase (AMACR), an enzyme that is important for the breakdown of branched-chain fatty acids in the body. It is a novel drug target for prostate and other cancers, but previous drug discovery efforts have been hampered due to challenges around developing a suitable screening assay.
“We set up a colorimetric assay that is based on using a colorless substrate that AMACR breaks down into a bright yellow product, resulting in a detectable change in absorbance,” says Lloyd.
The researchers used this assay to screen more than 20,000 drug-like compounds, around half of which were from the LifeArc index set, leading to the successful identification of active clusters of analog compounds as potential starting points for chemistry optimization.
High-Throughput Plate Sorting
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A smarter approach to HTS
The past few decades have seen a revolution in HTS – with increased capacity making it possible for pharmaceutical companies to screen unprecedented quantities of compounds to identify hits.
“I suspect that we’re now reaching the limits of what’s possible through miniaturization and automation,” says Lloyd. “A major challenge with these large-scale screens is you end up with a big jump in the number of artifacts.”
The future may see a move towards more intelligent screening strategies.
“There may be a shift away from screening larger and larger numbers of compounds to a greater focus on quality – and using artificial intelligence and iterative screening to inform the selection of molecules for further investigation,” predicts Kettleborough.