Automated Protein Crystallization

Q: What is automated protein crystallization, and how does it enhance efficiency compared to manual methods?

Automated protein crystallization uses instruments to set up experiments across the workflow without manual effort. By reducing pipetting errors, conserving samples, and enabling high-throughput, reproducible setups under controlled conditions, automation accelerates screening and optimization while saving time and resources.

Q: How does automation reduce human error in protein crystallization experiments?

Automation removes inconsistencies in liquid handling and drop setup that occur with manual pipetting, ensuring reproducible results across crystallization experiments.

Q: Which protein crystallization steps, such as screen building, drop setting, imaging, and scoring, can be automated for better results?

All workflow steps—from screen building and drop setting to imaging and scoring—can be automated to improve outcomes.

Q: What products are included in the Formulatrix automated protein crystallization suite (Rock Maker, NT8, Formulator, Rock Imager)?

The suite includes Rock Maker (LIMS–protein crystallization software), Formulator (screen builder), NT8 (drop setter), Rock Imager (protein crystallization imager), SONICC (nanocrystal detector), and FRAP (LCP condition prescreener).

Q: Can automated protein crystallization systems reduce the protein sample volume needed for successful experiments?

Yes. Automated systems can handle nanoliter volumes without human error. Humidity control in the drop setter helps prevent evaporation. The NT8 also uses liquid-level sensing to aspirate without submerging the tip, preventing sample loss and dripping.

Q: How does the Formulatrix NT8 Drop Setter improve hit rates, reduce failed crystallization experiments, and lower overall trial costs?

The NT8 is a precise nanoliter liquid handler with an active humidity chamber and an eight-tip head with flexible fingers. Precise drop setup and proportionally controlled humidification prevent evaporation and reduce handling errors, improving reproducibility and hit rates, reducing failures, and lowering overall trial costs.

Q: What is the role of AI-based autoscoring models (MARCO, Sherlock) in streamlining protein crystallization analysis?

AI-based autoscoring models analyze images of protein drops to identify crystals quickly and without bias, streamlining analysis.

Q: Can automated crystallization platforms be customized for different experimental designs and research needs?

Yes. Formulator is available with 10, 16, or 34 reagent inputs to match screen complexity. NT8 configurations support different experiment types. Rock Imager (RI360/RI1000) plate capacity and imaging modalities can be configured to fit lab setups and requirements.

Q: What are the cost benefits of implementing automated protein crystallization systems?

Automation reduces reagent use, minimizes sample waste, and improves reproducibility, lowering repeat trials. It also saves researcher time by removing manual pipetting and imaging, enabling higher throughput with fewer personnel and leading to faster structure determination and reduced project costs.

Q: Are there published case studies, success stories, or scientific results showing the benefits of automated protein crystallization?

Yes. There is substantial literature demonstrating the benefits of automated protein crystallization. See our publications section for details.

Protein crystallization is the process of forming a regular array of individual protein molecules stabilized by crystal contacts. Understanding the protein structure is of great importance for predicting its function, studying protein-protein or ligand-protein interaction for drug discovery, and uncovering stages in enzyme catalysis.

The process of protein crystallization involves gradually reducing the solubility of the protein using precipitants in a controlled environment (Figure 1). Predicting the optimal conditions under which a protein will form individual and well-diffracting crystals remains a challenge due to a complex interplay of the interactions between protein molecules.

Therefore, a comprehensive screening of various conditions, such as pH, temperature, salt concentration, precipitant type, and other additives, is necessary to optimize crystal development.

Figure 1: Protein Crystallization Phase Diagram

Protein Crystallization Workflow

Protein crystallization is a multistep process, beginning with the experimental design (Figure 2). Next, crystallization plates are prepared by combining purified protein droplets with the screening reagents. This is followed by incubation at specific temperatures and imaging to check for crystal formation.

Figure 2: Protein Crystallization Workflow

Protein Crystallization Techniques

There exist various protein crystallization techniques, and the choice depends on multiple factors, including the type of protein, its concentration and available volume, required experimental throughput, type of reagents to be used, and desired outcomes. Some of the most widely used protein crystallization methods are given below:

Feature	Hanging Drop	Sitting Drop	Micro-Batch	Micro-Dialysis	Free-Interface Diffusion	Lipid Cubic Phase
Amount of Protein	Small to Large	Small	Small	Large	Very Small	Small to Large
Automation	Possible	Possible	Not Possible	Not Possible	Difficult	Possible
Seeding	Possible	Possible	Not Possible	Not Possible	Possible	Possible
Harvesting	Easy	Easy	Difficult	Easy	Difficult	Difficult
Suitability	Crystallization Optimization Using High Surface Tension Reagents	Initial Screening	For Proteins and Reagents Having Minimal Interactions with Oil	For Developing Large Crystals	For Diffraction-Quality Crystals	For High-Quality Crystals of Membrane Proteins

Table: Comparison of Protein Crystallization Techniques

Imaging Modalities

Different imaging modalities, including visible light, ultraviolet, multi-fluorescent imaging, and SONICC^®, are available to image the protein drops and identify positive hits. Each technology has its own advantages; the choice varies based on the crystal properties and the purpose of imaging. A brief description of each modality is given below:

Visible Light Imaging

Visible light imaging captures images using the visible light spectrum (400 to 700 nm wavelength). Techniques such as bright-field, dark-field, and phase-contrast microscopy utilize visible light for imaging. This modality is suitable for analyzing large-sized protein crystals, but cannot distinguish between protein and salt crystals.

Learn More About Visible Light Imaging

Ultraviolet (UV) Imaging

UV imaging is a label-free imaging modality where protein drops are illuminated with UV light. The fluorescence from aromatic amino acids like tryptophan helps distinguish protein crystals from salt ones. However, it may give false-positive results with phase separation and protein aggregation.

Learn More About Ultraviolet Imaging

Multifluorescence Imaging (MFI)

This is a powerful technique for imaging crystals of fluorescently labeled proteins using trace fluorescent labeling approach (TFL). MFI efficiently distinguishes protein crystals from salts, as well as the crystals of a single protein from a complex. However, choosing the type of fluorescent dye and its concentration is important as it impacts the protein stability and, ultimately, its crystallizability.

Learn More About Multifluorescence Imaging

Second Order Non-linear Imaging of Chiral Crystals (SONICC)

The SONICC combines Second Harmonic Generation (SHG) with Ultraviolet Two-Photon Excited Fluorescence (UV-TPEF) to image the protein crystals. It easily detects microcrystals (<1 μm), and the crystals obscured in birefringent LCP or buried under aggregates.

Learn More About SONICC

Need for Automation in Protein Crystallization

The conventional protein crystallization process has been slow, resource-intensive, and error-prone due to manual workflows for screen building, plate setup, and imaging. It often involves working with sub-microliter volumes, and even slight inaccuracy in dispensing or mixing the reagents leads to significant errors or suboptimal results. Automation and integration of all crystallization steps eliminate human error, ensure reproducibility, and dramatically increase the throughput.

Automation Solutions for Protein Crystallization by Formulatrix^®

Formulatrix protein crystallization repository includes Laboratory Information Management Software (Rock Maker^®), screen builder (Formulator^®), drop setter (NT8^®), and imagers (Rock Imagers^®). Our systems are designed to streamline protein crystallization workflows with high precision, throughput, and time efficiency.

Rock Maker - Crystallization Software

Rock Maker is a powerful and easy-to-use protein crystallization software that seamlessly integrates all our protein crystallization products to manage the entire workflow, including data analysis.

Learn More About Rock Maker

Formulator - Screen Builder

The Formulator is a microfluidic liquid dispenser designed to set up crystallization screens and capable of dispensing up to 34 different ingredients of any volume and viscosity with a 96-nozzle chip. It supports low volumes (down to 200 nL) with no upper limit and can dispense a 100 μL, 3-ingredient grid across 96 wells in 2.7 minutes, accommodating all microplate types. Features include an integrated barcode scanner, automatic ingredient detection, and seamless Rock Maker crystallization software integration.

Learn More About the Formulator

Formulator - Screen Builder

NT8 - Drop Setter / Crystallization Robot

The NT8 Drop Setter is a fast liquid handler capable of dispensing drops from 10 nL to 1.5 μL. It supports various experimental setups like hanging and sitting drops, LCP, additives, and seeding. It features proportionally controlled active humidification to prevent evaporation. Additionally, reusable tips and compatibility with temperature-controlled rooms ensure cost efficiency, flexibility, and reproducibility. Moreover, it is the only crystallization robot that integrates with Rock Maker.

Learn More About the NT8

NT8 - Drop Setter / Crystallization Robot

Fluorescence Recovery After Photobleaching (FRAP) for Membrane Proteins

Membrane proteins are challenging to crystallize in LCP, and the optimization process is time, effort, and resource-intensive. FRAP saves all the hassle and resources by quickly screening LCP conditions and ruling out sub-optimal conditions before setting up crystallization experiments.

Learn More About FRAP

Rock Imager - Protein Crystallization Imagers

Rock Imagers are a series of automated imaging systems designed for protein crystallization screening. They capture superior-quality images of protein drops and are available with various plate capacities and imaging features (Table).

Feature	Rock Imager 1	Rock Imager 2	Rock Imager 360	Rock Imager 1000
Plate Capacity	1	2	360	1000
Refrigeration	No	No	Yes	Yes
Plate Storage and Retrieval	No	No	Yes	Yes
Imaging Options	Visible, UV	Visible, UV, MFI	Visible, UV, MFI	Visible, UV, MFI, SONICC
Footprint	Benchtop	Benchtop	Benchtop	Floor Standing
Software	Windows-based	Windows-based	Browser-based	Windows-based

Learn More About the Rock Imager

AI-Based Autoscoring Models Integrated with Rock Maker

Integration of MARCO and Sherlock, AI-based autoscoring models, with Rock Maker has streamlined the analysis of the extensive image datasets generated during crystallization experiments. Sherlock, our proprietary autoscoring model, is continually being enhanced based on feedback from Rock Maker users to further improve its performance and accuracy.

Learn More About Sherlock

Related Links

Webinars

From Design to Data: End-to-End Automation with Formulatrix Protein Crystallization Solutions

Discover how Formulatrix’s comprehensive suite of tools enables a seamless, fully integrated automated protein crystallization workflow.

Watch the Webinar

Bridging the Gap: From Microfluidic Crystals to High-Throughput Imaging

Learn how combining the advantages of the microfluidic format with high-throughput imaging opens exciting perspectives in protein crystallization studies.

Watch the Webinar

ROCK IMAGER 360 (2023) - Automated Imaging for Protein Crystallization (2)

Advancements in AI-Powered Scoring: Save Time, Increase Efficiency, Gain Confidence in Your Results

Learn how to enhance and automate the scoring of crystallization experiments using Sherlock, an advanced AI auto-scoring model that can help you save time and increase your confidence in the results.

Watch the Webinar

Rock Imager 360 - A Next Generation Benchtop Crystal Imager

Explore the latest advancements in benchtop imaging technology offering unmatched plate storage, integrated refrigeration, and advanced automation for effortless crystal imaging.

Watch the Webinar

View All Webinars

Application Notes

AI-Powered Crystallization Experiment Scoring by Sherlock: Enhancing Efficiency, Accuracy, and Confidence in Outcomes

Learn how our protein crystallization software- Rock Maker can help you perform effortless AI-based autoscoring of your crystallization experiments.

Read the Application Note

Influence of Humidity on Drop Evaporation

Learn how our protein crystallization software- Rock Maker can help you perform effortless AI-based autoscoring of your crystallization experiments.

Read the Application Note

Influence of Humidity on Drop Evaporation

Volumetric and Hygrometric Performance of the NT8^®: An Advanced Liquid Handler for High-Throughput Crystallization Screening

Learn more about our advanced liquid handler-NT8 to set up crystallization experiments with reliable low volume performance due to its built-in active humidity control system.

Read the Application Note

Iterative Screen Optimization (ISO) of Macromolecular Crystals

Learn more about our advanced liquid handler-NT8 to set up crystallization experiments with reliable low volume performance due to its built-in active humidity control system.

Read the Application Note

iterative-screen-optimization-iterations

View All Application Notes

Publications

Citations: 817 Application: Protein Crystallization

Structural and Functional Characterization of Encapsulin-Targeted Double Ferritin Fold Ferroxidases

Anuchina et al., 2025 |Preprint |Link

Ferritins are a widespread family of proteins involved in iron homeostasis While classic ferritins consist of four -helices and form -meric nanocages related ferritin-like proteins display other types of assemblies and sometimes lack any iron storage capacity Here by analyzing the available genomic data we identify a family of double ...More |

A third type of PETase from the marine Halopseudomonas lineage

Turak et al., 2025 |Protein Science |Link

The enzymatic degradation of polyethylene terephthalate PET offers a sustainable solution for PET recycling Over the past two decades more than PETases have been characterized primarily exhibiting similar sequences and structures Here we report new PET-degrading hydrolases including HaloPETase from the marine Halopseudomonas lineage thereby extending the narrow sequence space ...More |

Combining crystallographic fragment screening, algorithmic merging and digitized chemical synthesis efficiently yields scaffolds that target diverse NCS-1 protein-protein interactions implicated in neurological disorders

Muñoz-Reyes et al., 2025 |Preprint |Link

Efficient drug discovery relies on workflows that integrate structural insights with rapid and cost-effective exploration of chemical space Here we present a data-driven fragment-based lead discovery approach to target Neuronal Calcium Sensor NCS- protein-protein interactions PPIs This study represents a complete implementation of a single high-value design-make-test-analyze cycle that directly ...More |

Impact of 2′-deoxyribo-purine substrates on nonenzymatic RNA template-directed primer extension

Fang et al., 2025 |Preprint |Link

The composition of the primordial genetic material remains uncertain Studies of duplex structure and stability and of nonenzymatic template copying chemistry provide insight into the viability of potentially primordial genetic polymers Recent work suggests that - deoxyribo-purine nucleotides may have been generated together with ribonucleotides on the early Earth Since ...More |

Enhancing the outcome of crystallographic screening for efficient drug discovery by choosing the right crystal form

Barthel et al., 2025 |Preprint |Link

In more and more drug discovery projects crystallographic fragment screening CFS is employed as an early screening method Here we demonstrate that choosing the right crystal form has a profound influence on the hit rates and hence success and speed of downstream lead generation Two CFS campaigns with the same ...More |

FAQs

What is automated protein crystallization, and how does it enhance efficiency compared to manual methods?
Automated protein crystallization is the process of setting up protein crystallization experiments with the help of instruments that support every step of the workflow efficiently, without the need for manual effort. By reducing manual pipetting errors, conserving protein samples, and enabling high-throughput, reproducible setups under controlled conditions, automation accelerates screening and optimization while saving time and resources.

How does automation reduce human error in protein crystallization experiments?
Automation eliminates inconsistencies in liquid handling and drop setup that users experience with manual pipetting. This ensures reproducible results across crystallization experiments.

Which protein crystallization steps—such as screen building, drop setting, imaging, and scoring—can be automated for better results?
All the steps in the protein crystallization workflow—from screen building and drop setting to imaging and scoring—can be automated to achieve better outcomes.

What products are included in the Formulatrix automated protein crystallization suite (Rock Maker, NT8, Formulator, Rock Imager)?
The Formulatrix automated protein crystallization suite includes Rock Maker (laboratory information management system–protein crystallization software), Formulator (screen builder), NT8 (drop setter), Rock Imager (protein crystallization imager), SONICC (nanocrystal detector), and FRAP (LCP condition prescreener).

Can automated protein crystallization systems reduce the protein sample volume needed for successful experiments?
Yes. Automated protein crystallization systems reduce the protein sample volumes needed to set up crystallization experiments, as they can handle nanoliter volumes without human error. Moreover, humidity control within the drop setter helps maintain nanoliter drops without the risk of evaporation. The NT8 also features liquid-level sensing while aspirating a protein sample, allowing aspiration without dipping the entire tip into the well. This prevents sample loss and dripping by avoiding tip coating with protein formulation.

How does the Formulatrix NT8 Drop Setter improve hit rates, reduce failed crystallization experiments, and lower overall trial costs?
The NT8 Drop Setter by Formulatrix is a precise nanoliter liquid handler equipped with an active humidity chamber and an eight-tip head with flexible fingers. The flexible fingers allow precise drop setup, while proportionally controlled active humidification prevents protein drop evaporation during experiment setup. These features reduce errors in handling small sample volumes, maintain reproducibility, and ultimately lead to improved hit rates and fewer failed experiments. Fewer failed experiments, in turn, result in lower overall trial costs.

What is the role of AI-based autoscoring models (MARCO, Sherlock) in streamlining protein crystallization analysis?
AI-based autoscoring models help analyze captured images of protein drops to identify crystals in an unbiased and efficient manner.

Can automated crystallization platforms be customized for different experimental designs and research needs?
Automated crystallization platforms provided by Formulatrix can be customized for different experimental designs and research needs. The Formulator (screen builder) is available in various configurations based on reagent input options (10, 16, and 34), depending on the complexity of the crystallization screens users wish to build. Different configurations of the NT8 can support different types of experiments. Additionally, the Rock Imager (RI360 and RI1000) plate storage capacity can be configured based on lab setup. Users can also customize imaging modalities in their Rock Imager systems according to experimental requirements.

What are the cost benefits of implementing automated protein crystallization systems?
Implementing automated protein crystallization systems offers significant long-term cost benefits by reducing reagent consumption, minimizing sample waste, and increasing experiment reproducibility, thereby lowering the need for repeat trials. Automation also saves researchers’ time by eliminating manual pipetting and imaging, enabling higher throughput with fewer personnel. Over time, these efficiencies lead to faster structure determination and reduced overall project costs.

Are there published case studies, success stories, or scientific results showing the benefits of automated protein crystallization?
Yes. There is ample scientific literature highlighting the benefits of automated protein crystallization. You can visit our publications section for more information.

What are the latest innovations and trends in automated protein crystallization technology?
In protein crystallization technology, researchers are moving toward integrated systems in which all instruments are controlled by Laboratory Information Management Systems (LIMS) for improved workflow control. Additionally, the introduction of Artificial Intelligence (AI) in crystallization workflows—not just in image scoring but also in instrument control and experiment outcome prediction—is gaining popularity.

How can a laboratory get started with adopting automated protein crystallization solutions from Formulatrix?
Labs can get started with Formulatrix automated protein crystallization solutions by contacting the company to discuss research goals and workflow needs. The Formulatrix team helps select suitable systems, such as the NT8 Drop Setter for automated experiment setup and the Rock Imager for imaging, then provides installation and training. Users can also integrate Rock Maker software to ensure a smooth transition to automation.