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.
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.
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.
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.
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.
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.
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.
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.
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 |
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.
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Related Links
Webinars
Discover how Formulatrix’s comprehensive suite of tools enables a seamless, fully integrated automated protein crystallization workflow.
Learn how combining the advantages of the microfluidic format with high-throughput imaging opens exciting perspectives in protein crystallization studies.
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.
Explore the latest advancements in benchtop imaging technology offering unmatched plate storage, integrated refrigeration, and advanced automation for effortless crystal imaging.
Application Notes
Learn how our protein crystallization software- Rock Maker can help you perform effortless AI-based autoscoring of your crystallization experiments.
Learn how our protein crystallization software- Rock Maker can help you perform effortless AI-based autoscoring of your crystallization experiments.
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.
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.
Publications
Dynamic and Structural Insights into Allosteric Regulation on MKP5 a Dual-Specificity Phosphatase
Skeens et al. 2025 | Nature Communication | Link: https://doi.org/10.1038/s41467-025-62150-w
Dual-specificity mitogen-activated protein kinase MAPK phosphatases MKPs directly dephosphorylate and inactivate the MAPKs Although the catalytic mechanism of dephosphorylation of the MAPKs by the MKPs is established a complete molecular picture of the regulatory interplay between the MAPKs and MKPs still remains to be fully explored Here we sought to define the molecular mechanism of MKP regulation through an allosteric site within its catalytic domain We demonstrate using crystallographic and NMR spectroscopy More.... | Related Solution: NT8
Heterologous Production, Purification and Crystallization of 24C-Sterol Methyltransferase From Candida Albicans
Mpontshane et al. 2025 | Preprint | Link: https://doi.org/10.1101/2025.02.05.636639
Candida albicans is a critical priority fungal pathogen causing invasive fungal infections with high mortality rates in immunocompromised patients The increasing fungal infection rate and resistance of fungal pathogens to existing antifungal treatments have emphasized the need for the development of novel antifungal medicine The ergosterol biosynthesis pathway has been a successful target for antifungal compounds but many enzymatic steps remain unexplored C-sterol methyltransferase C-SMT catalyzes a critical fungal-specific step in ergosterol biosynthesis More.... | Related Solution: Formulator
Binding Differences of the Peptide-Substrate–Binding Domain of Collagen Prolyl 4-Hydroxylases I and II for Proline- and Hydroxyproline-Rich Peptides
Rahman et al. 2025 | Proteins: Structure, Function and Bioinformatics | Link: https://doi.org/10.1002/prot.26839
Collagen prolyl -hydroxylase C-P H catalyzes the -hydroxylation of Y-prolines of the XYG-repeat of procollagen C-P Hs are tetrameric enzymes The -subunit provides the N-terminal dimerization domain the middle peptide-substrate binding PSB domain and the C-terminal catalytic CAT domain There are three isoforms of the -subunit complexed with a -subunit that is protein disulfide isomerase forming C-P H I-III The PSB domain of the -subunit binds proline-rich peptides but its function with respect to the prolyl hydroxylation mechanism More.... | Related Solution: Rock Imager
Preparing for Successful Protein Crystallization Experiments
Budziszewski et al. 2025 | Structural Biology Communications | Link: https://doi.org/10.1107/S2053230X25004650
Crystal-based structural methods including X-ray crystallography are frequently utilized for the determination of high-resolution structures of biomolecules All crystal-based diffraction methods first require the preparation of biomolecular crystals and careful sample preparation for crystallization experiments can increase the frequency of success In this article strategies to optimize factors that can impact crystallization are presented from which buffers and reducing agents are most favorable to which crystallization techniques could be used More.... | Related Solution: SONICC
Managing Macromolecular Crystallographic Data with a Laboratory Information Management System
Daniel et al. 2024 | Structural Bilogy | Link: https://doi.org/10.1107/S2059798324005680
Protein crystallography is an established method to study the atomic structures of macromolecules and their complexes. A prerequisite for successful structure determination is diffraction-quality crystals, which may require extensive optimization of both the protein and the conditions, and hence projects can stretch over an extended period, with multiple users being involved. The workflow from crystallization and crystal treatment to deposition and publication is well defined, and therefore an electronic laboratory information management system (LIMS) is well suited to management of the data More.... | Related Solution: Rock Maker