Abstract
Desire for High Throughput Protein Crystallography Ignites Demand for
Automated Crystallization
The need to understand exactly how small molecules bind to their protein
target is driving the demand for protein crystallography in drug discovery. A
higher throughput protein crystallography process requires protein
crystallization to also become high throughput and this is best achieved through
automated crystallization. A number of large proteomic initiatives are being
launched, increasing market opportunities for automated crystallization.
This Frost & Sullivan research analyzes the global market for structural
proteomics. It provides an analysis of market drivers, restraints, and
forecasts, identifying areas of growth. The study covers liquid handlers used
for protein purification; automated protein crystallization instruments; nuclear
magnetic resonance (NMR) spectrometers, and X-ray systems used for protein
studies.
Drug Discovery Initiatives Drive Technological Advancements in Structural
Proteomics
"Pharmaceutical companies agree that structure discovery helps lead
optimization," says the author of the study. With rapid technology
advances, structure-based design is set to become a preferred method for
discovering new drugs.
As an increasing number of companies discover the importance and significance
of protein structure studies for drug discovery, more efforts are being made
toward improving structural determination technologies. Market consolidation and
industrialization along with the introduction of powerful integrated systems is
changing research approaches. Besides automation, miniaturization of protein
crystals and processes including purification is another big trend.
Lack of Experienced Researchers Increases Need for Automated
Crystallization
Protein crystallization is a process that requires training, skill, and time.
The number of trained researchers and people willing to commit to such a process
is decreasing. "The surge in automation has addressed the worrisome dearth
of protein-structure researchers," says the analyst.
However, automation allows researchers with less experience and training to
be involved in crystallization. A novice, with an expert's guidance, can now
perform projects that once required the full-time attention of an expert.
Automation eliminates much of the repetitive work involved in setting up the
massive number of crystallization trials. This frees researchers, allowing them
to focus on increasing productivity, reproducibility, and throughput.
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