High Throughput Screening (HTS) is a Well-Established Part of Drug Discovery which implies 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 possible without some sort of robust, low volume test,” 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 there is scope to reduce that even further to 1536-well formats.”
HTS is usually the first step in the search for active compounds with the potential to become a drug candidate – or chemical probes to help advance biological research.
“If you are working on a very new drug target, there may be very little precedent for how to develop a screening test,” says Kettleborough. “And so the middle step might be to try to find something that ties into it to use as a tool to master it.”
Over the past decades, the focus has been on increasing HTS capacity through increased automation, miniaturization, and large-scale data analysis.
“In large-scale industrial facilities, it is now possible to screen several hundred thousand – or even up to a million compounds – per day,” says Matthew Lloyd, senior lecturer in pharmacy and pharmacology at the University of Bath.
But university researchers, who may have budget constraints or limited access to all HTS facilities, are turning to smarter screening strategies.
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Chemical starting point screening
The search for compounds active against a promising new drug target – such as an enzyme involved in a critical disease pathway – will often begin by screening libraries containing several thousand compounds, using HTS technologies. The first step is to design a in vitro test 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,” says 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 signal indicating enzyme inhibition.”
Although the type of test used in HTS varies depending on the target, it should be simple enough to be miniaturized and automated. Other reading methods include detecting a change in color or luminescence or may involve more complex approaches such as mass spectrometry or cell assays.
An analysis of recent HTS campaigns for the discovery of enzyme inhibitors showed that the the frequency of access was largely independent of the size of the library, but was related to the Z ‘ value for test, a statistical measure of how easy it is to find a hit.
“You can expect a success rate of between 0.5% and 1% with a typical HTS test,” Lloyd explains. “But some goals are more difficult – and you could end up with less than 0.1%.”
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Refine the list of results
While false negative results are wasted opportunities, false positives can lead to wasted time and resources – numbers becoming especially problematic when screening large libraries of compounds.
“Many compounds in libraries are small, organic, and poorly soluble in water,” Lloyd explains. “These compounds tend to form aggregates which can interfere with the ability of the enzyme to break down the substrate, leading to apparent inhibition.”
This inhibition is highly dependent on the test conditions and is typically reduced by the presence of a detergent, such as 0.01% Triton X-100. But increasing the detergent level to 0.1% may be necessary for complete suppression of aggregate formation, which can help eliminate many of the false positives in follow-up tests.
“If you only have a few dozen results left, which might be typical on a small screen, then it’s probably possible to do a dose-response curve on each one,” Lloyd explains. “But if you still have several thousand of them, you may need to perform further analysis to reduce them even further.”
The overall goal of HTS is to narrow down a shortlist of active hits to move to hit-to-lead optimization, which involves making small adaptations to the chemical structure to generate a series of closely related compounds for testing. additional.
“At this stage, medicinal chemists will have to look at the structures of any remaining hits to determine if it is worth progressing further, ”said Lloyd. “A compound will need to be synthetically treatable so that it is possible to generate a series of analogs for further testing.”
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Quality over quantity
While industrial laboratories may screen libraries containing large amounts of compounds to identify results, academic researchers may need an alternative strategy more suited to laboratories with limited resources.
“It requires screening smaller, more refined compound libraries,” Kettleborough says.
An example is the representative LifeArc Index Set, a pooled collection of about 10,000 drug-like compounds that has been compiled from the charity’s largest diversity collection of about 150,000 compounds. The library is available to be shared with academic groups around the world.
“It’s almost a one-stop-shop for college groups, so they don’t have to buy a larger collection of compounds,” Kettleborough says. “After identifying a first success in this small set, they can then source analogs from related clusters within our larger diversity collection for quick follow-up.”
The set of indices has been carefully designed to increase the chances of identifying chemically treatable impacts while maximizing chemical diversity. A big challenge is to select high-quality compounds – both to avoid false positives in HTS and to invest time and resources on results that can be ruled out at a later stage.
“We initially use computational approaches to select compounds based on the chemical space to be filled, then we share these structures with medicinal chemists for mental health monitoring,” Kettleborough explains. “We then only add molecules that are independently approved by two chemists as having at least a reasonable chance of moving to the next stage of drug discovery.”
Screening the LifeArc index set in conjunction with analog hit tracking offers a good chance of identifying a compound that has the potential for further development.
An example of the application of this more cost-effective screening strategy is search for new small molecule inhibitors of alpha-methylacyl-CoA racemase (AMACR), an enzyme important for the breakdown of branched-chain fatty acids in the body. It is a new drug target for prostate and other cancers, but previous drug discovery efforts have been hampered by challenges in developing an appropriate screening test.
“We set up a colorimetric test based on the use of a colorless substrate that AMACR breaks down into a bright yellow product, resulting in a detectable change in absorbance,” explains Lloyd.
Researchers used this assay to screen over 20,000 drug-like compounds, about half of which were from the LifeArc index set, successfully identifying active clusters of analog compounds as potential starting points. for chemical optimization.
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A smarter approach to HTS
The past few decades have seen a revolution in HTS – with increased capacity allowing pharmaceutical companies to screen unprecedented amounts of compounds to identify hits.
“I suspect that we are now reaching the limits of what is possible through miniaturization and automation,” Lloyd says. “A major challenge with these large-scale displays is that you end up with a big jump in the number of artifacts.”
The future may see a shift towards smarter screening strategies.
“There may be a shift from screening more and more compounds to a greater focus on quality – and the use of artificial intelligence and iterative screening to inform the selection of molecules for further investigation,” predicts Kettleborough.