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Billions of screens have produced … what?
January 2011
by Lloyd Dunlap  |  Email the author


Nanoliter acoustic compound dispensing technology; custom-made benchtop enclosures with automated liquid handling vortexers and mixers; chemical libraries that have grown to include more than 1 million small molecules and grow by 20 percent every year; ministores that have the capacity to store million of compound in 384 well microplates at -20º C that can be cherry-picked from the same or different collections—and that's just a brief look at the advanced equipment side.
Elsewhere, there's induced fit docking; rational drug design; structure-based lead optimization; integration of experimental and in- silico data by cross-functional expert teams and dozens of other approaches.
It's all subsumed under the single rubric of high-throughput screening (HTS), which is used in one form or another in hundreds, if not thousands, of labs around the globe.
HTS is defined as a method for scientific experimentation especially used in drug discovery and relevant to the fields of biology and chemistry.
Using robotics, data processing and control software, liquid handling devices and sensitive detectors, HTS allows a researcher to quickly conduct millions of biochemical, genetic or pharmacological tests.
Through this process, one can rapidly identify active compounds, antibodies or genes which modulate a particular bimolecular pathway.
The results of these experiments provide starting points for drug design and for understanding the interaction or role of a particular biochemical process in biology.
Yet after 25 years of HTS, we have little by way of NMEs that have contributed to the cure of disease or alleviation of debilitating symptoms.
Several years ago, a respected U.K. researcher, Dr. David Horrobin, vented his frustration by decrying the process altogether. He noted that estimates of the ratios of compounds synthesized to marketed drugs at the time of peak success of Nobel Laureates Black, Bovet, Elion and Hitchings was about 100:1; most of the industry from about 1960 to about 1990 saw about 10,000:1 to 30,000:1; Big Pharma since the introduction of combinatorial chemistry and HTS, well over 1,000,000:1.
Horrobin asked the question, "Is the approach of building a bigger haystack really the best way to find more needles?
Dr. Stephan Heyse, head of Genedata's Screener business unit, doesn't care for the haystack analogy because he says HTS has changed. He thinks the "more needles" approach has been supplanted by a "sharper needles" goal. "It's more like a well-tended field where you already know a lot about what's in each row," he says. "We're evolving toward biology-rich information that goes beyond simple endpoint assays and uses better detection technologies, such as optical assays and ion channel readers, to make results more trustworthy. The problem has always been that what you saw at the first filter will always be out there and can affect basic business decisions. You can't always afford to reproduce scans to get to the next level. High-content screening, for example, provides a much broader basis for decision-making. You can generate active plus toxicology information, for example. Maybe weak actives that have a good tox profile are more important than just strong hits."

Summarizing the current state-of-the-art technology, Heyse notes that classical primary screens continue to be performed in high throughput—i.e., millions of wells. As new technologies such as high-content screening and time-resolved fluorescence, label-free and electrophysiology methods deliver more information per well and screened compound, data management and analysis become more complex.
Mastering these challenges yields more precise information at the HTS stage on compound mode-of-action and potential therapeutic window. Complete bioactivity profiles of compounds are compiled from sets of high-throughput primary and secondary screens, enabling optimized decisions on compound progression into the hit-to-lead phase.
At Schrödinger Inc. screening can vary from ligand- based similarity searches where thousands or tens of thousands of molecules are screened per second to much more refined and specific studies such as induced fit docking, explains Dr. Woody Sherman, vice president of applications science.
In May 2010, his group reported the results of a large-scale, ligand-based virtual screening study, with the goal of improving database enrichments.
The study involved 11 pharmaceutically relevant targets to investigate the interrelation between 8 two-dimensional fingerprinting methods, 13 atom-typing schemes, 13 bit scaling rules and 12 similarity metrics using the new cheminformatics package Canvas.
In total, 157,872 virtual screens were performed to assess the ability of each combination of parameters to identify actives in a database screen. In general, fingerprint methods such as MOLPRINT2D, Radial and Dendritic that encode information about the local environment beyond simple linear paths outperformed other fingerprint methods. Atom-typing schemes with more specific information, such as Daylight, Mol2 and Carhart were generally superior to more generic atom-typing schemes.
Enrichment factors across all targets were improved considerably with the best settings, although no single set of parameters performed optimally on all targets.
Kinases remain an important drug target class within the pharmaceutical industry, Sherman notes, but he adds that the rational design of kinase inhibitors is plagued by the complexity of gaining selectivity for a small number of proteins within a family of more than 500 related enzymes. He and his team have developed a computational screening method for identifying the location and thermodynamic properties of water molecules within a protein binding site that can yield insight into previously inexplicable selectivity and structure-activity relationships. Four kinase systems (Src family, Abl/c-Kit, Syk/ZAP-70, and CDK2/4) were investigated, and differences in predicted water molecule locations and energetics were able to explain the experimentally observed binding selectivity profiles. The successful predictions across the range of kinases suggest that this screening methodology could be generally applicable for predicting selectivity profiles in related targets.
"Understanding kinase selectivity is key to developing effective therapies that don 't have side effects," he concludes.
As Sherman's work reveals, screening that predicts or confirms experimental observations can answer, in silico, fundamental questions about molecular interactions and be used as an important part of the drug development process.
Code: E011130



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