An approach to rapid protein crystallization using nanodroplets

A fully integrated protein crystallization platform for small-molecule drug discovery

Structure-based drug discovery in the pharmaceutical industry benefits from cost-efficient methodologies that quickly assess the feasibility of specific, often refractory, protein targets to form well-diffracting crystals. By tightly coupling construct and purification diversity with nanovolume crystallization, the Structural Biology Group at Syrrx has developed such a platform to support its small-molecule drug-discovery program. During the past 18 months of operation at Syrrx, the Structural Biology Group has executed several million crystallization and imaging trials on over 400 unique drug-discovery targets. Here, key components of the platform, as well as an analysis of some experimental results that allowed for platform optimization, will be described.

Efficient protein crystallization

High-throughput molecular biology and crystallography advances have placed an increasing demand on crystallization, the one remaining bottleneck in macromolecular crystallography. This paper describes three experimental approaches, an incomplete factorial crystallization screen, a high-throughput nanoliter crystallization system, and the use of a neural net to predict crystallization conditions via a small sample (approximately 0.1%) of screening results. The use of these technologies has the potential to reduce time and sample requirements. Initial experimental results indicate that the incomplete factorial design detects initial crystallization conditions not previously discovered using commercial screens. This may be due to the ability of the incomplete factorial screen to sample a broader portion of "crystallization space," using a multidimensional set of components, concentrations, and physical conditions. The incomplete factorial screen is complemented by a neural network program used to model crystallization. This capability is used to help predict new crystallization conditions. An automated, nanoliter crystallization system, with a throughput of up to 400 conditions/h in 40-nl droplets (total volume), accommodates microbatch or traditional "sitting-drop" vapor diffusion experiments. The goal of this research is to develop a fully-automated high-throughput crystallization system that integrates incomplete factorial screen and neural net capabilities.

The genesis of high-throughput structure-based drug discovery using protein crystallography

Over the past 12 years, drugs have been developed using structure-based drug design relying upon traditional crystallographic methods. Established successes, such as the drugs designed against HIV-1 protease and neuraminidase, demonstrate the utility of a structure-based approach in the drug-discovery process. However, the approach has historically lacked throughput and reliability capabilities; these bottlenecks are being overcome by breakthroughs in high-throughput structural biology. Recent technological innovations such as submicroliter high-throughput crystallization, high-performance synchrotron beamlines and rapid binding-site analysis of de novo targets using virtual ligand screening and small molecule co-crystallization have resulted in a significant advance in structure-based drug discovery.

Structural genomics of the Thermotoga maritima proteome implemented in a high-throughput structure determination pipeline

Structural genomics is emerging as a principal approach to define protein structure-function relationships. To apply this approach on a genomic scale, novel methods and technologies must be developed to determine large numbers of structures. We describe the design and implementation of a high-throughput structural genomics pipeline and its application to the proteome of the thermophilic bacterium Thermotoga maritima. By using this pipeline, we successfully cloned and attempted expression of 1,376 of the predicted 1,877 genes (73%) and have identified crystallization conditions for 432 proteins, comprising 23% of the T. maritima proteome. Representative structures from TM0423 glycerol dehydrogenase and TM0449 thymidylate synthase-complementing protein are presented as examples of final outputs from the pipeline.