Comparing chemistry to outcome: the development of a chemical distance metric, coupled with clustering and hierarchal visualization applied to macromolecular crystallography

20 years of crystal hits: progress and promise in ultrahigh-throughput crystallization screening

Diffraction-based structural methods contribute a large fraction of the biomolecular structural models available, providing a critical understanding of macromolecular architecture. These methods require crystallization of the target molecule, which remains a primary bottleneck in crystal-based structure determination. The National High-Throughput Crystallization Center at Hauptman-Woodward Medical Research Institute has focused on overcoming obstacles to crystallization through a combination of robotics-enabled high-throughput screening and advanced imaging to increase the success of finding crystallization conditions. This paper will describe the lessons learned from over 20 years of operation of our high-throughput crystallization services. The current experimental pipelines, instrumentation, imaging capabilities and software for image viewing and crystal scoring are detailed. New developments in the field and opportunities for further improvements in biomolecular crystallization are reflected on.

High-throughput macromolecular polymorph screening via an NMR and X-ray powder diffraction synergistic approach: the case of human insulin co-crystallized with resorcinol derivatives

Regular injections of insulin provide life-saving benefits to millions of diabetics. Apart from native insulin and insulin analogue formulations, microcrystalline insulin suspensions are also commercially available. The onset of action of the currently available basal insulins relies on the slow dissociation of insulin hexamers in the subcutaneous space due to the strong binding of small organic ligands. With the aim of identifying insulin–ligand complexes with enhanced pharmacokinetic and pharmacodynamic profiles, the binding affinity of two resorcinol-based molecules (4-chlororesorcinol and 4-bromoresorcinol) and the structural characteristics of insulin upon co-crystallization with them were investigated in the present study. `In solution' measurements were performed via saturation transfer difference (STD) NMR. Co-crystallization upon pH variation resulted in the production of polycrystalline precipitates, whose structural characteristics (i.e. unit-cell symmetry and dimension) were assessed. In both cases, different polymorphs (four and three, respectively) of monoclinic symmetry (P21 and C2 space groups) were identified via X-ray powder diffraction. The results demonstrate the efficiency of a new approach that combines spectroscopy and diffraction techniques and provides an innovative alternative for high-throughput examination of insulin and other therapeutic proteins.

Tools to Ease the Choice and Design of Protein Crystallisation Experiments

The process of macromolecular crystallisation almost always begins by setting up crystallisation trials using commercial or other premade screens, followed by cycles of optimisation where the crystallisation cocktails are focused towards a particular small region of chemical space. The screening process is relatively straightforward, but still requires an understanding of the plethora of commercially available screens. Optimisation is complicated by requiring both the design and preparation of the appropriate secondary screens. Software has been developed in the C3 lab to aid the process of choosing initial screens, to analyse the results of the initial trials, and to design and describe how to prepare optimisation screens.

What macromolecular crystallogenesis tells us - what is needed in the future

Crystallogenesis is a longstanding topic that has transformed into a discipline that is mainly focused on the preparation of crystals for practising crystallo-graphers. Although the idiosyncratic features of proteins have to be taken into account, the crystallization of proteins is governed by the same physics as the crystallization of inorganic materials. At present, a diversified panel of crystallization methods adapted to proteins has been validated, and although only a few methods are in current practice, the success rate of crystallization has increased constantly, leading to the determination of ∼105 X-ray structures. These structures reveal a huge repertoire of protein folds, but they only cover a restricted part of macromolecular diversity across the tree of life. In the future, crystals representative of missing structures or that will better document the structural dynamics and functional steps underlying biological processes need to be grown. For the pertinent choice of biologically relevant targets, computer-guided analysis of structural databases is needed. From another perspective, crystallization is a self-assembly process that can occur in the bulk of crowded fluids, with crystals being supramolecular assemblies. Life also uses self-assembly and supramolecular processes leading to transient, or less often stable, complexes. An integrated view of supramolecularity implies that proteins crystallizing either in vitro or in vivo or participating in cellular processes share common attributes, notably determinants and antideterminants that favour or disfavour their correct or incorrect associations. As a result, under in vivo conditions proteins show a balance between features that favour or disfavour association. If this balance is broken, disorders/diseases occur. Understanding crystallization under in vivo conditions is a challenge for the future. In this quest, the analysis of packing contacts and contacts within oligomers will be crucial in order to decipher the rules governing protein self-assembly and will guide the engineering of novel biomaterials. In a wider perspective, understanding such contacts will open the route towards supramolecular biology and generalized crystallogenesis.

Optimizing Associative Experimental Design for Protein Crystallization Screening

The goal of protein crystallization screening is the determination of the main factors of importance to crystallizing the protein under investigation. One of the major issues about determining these factors is that screening is often expanded to many hundreds or thousands of conditions to maximize combinatorial chemical space coverage for maximizing the chances of a successful (crystalline) outcome. In this paper, we propose an experimental design method called "Associative Experimental Design (AED)" and an optimization method includes eliminating prohibited combinations and prioritizing reagents based on AED analysis of results from protein crystallization experiments. AED generates candidate cocktails based on these initial screening results. These results are analyzed to determine those screening factors in chemical space that are most likely to lead to higher scoring outcomes, crystals. We have tested AED on three proteins derived from the hyperthermophile Thermococcus thioreducens, and we applied an optimization method to these proteins. Our AED method generated novel cocktails (count provided in parentheses) leading to crystals for three proteins as follows: Nucleoside diphosphate kinase (4), HAD superfamily hydrolase (2), Nucleoside kinase (1). After getting promising results, we have tested our optimization method on four different proteins. The AED method with optimization yielded 4, 3, and 20 crystalline conditions for holo Human Transferrin, archaeal exosome protein, and Nucleoside diphosphate kinase, respectively.

Lessons from ten years of crystallization experiments at the SGC

Although protein crystallization is generally considered more art than science and remains significantly trial-and-error, large-scale data sets hold the promise of providing general learning. Observations are presented here from retrospective analyses of the strategies actively deployed for the extensive crystallization experiments at the Oxford site of the Structural Genomics Consortium (SGC), where comprehensive annotations by SGC scientists were recorded on a customized database infrastructure. The results point to the importance of using redundancy in crystallizing conditions, specifically by varying the mixing ratios of protein sample and precipitant, as well as incubation temperatures. No meaningful difference in performance could be identified between the four most widely used sparse-matrix screens, judged by the yield of crystals leading to deposited structures; this suggests that in general any comparison of screens will be meaningless without extensive cross-testing. Where protein sample is limiting, exploring more conditions has a higher likelihood of being informative by yielding hits than does redundancy of either mixing ratio or temperature. Finally, on the logistical question of how long experiments should be stored, 98% of all crystals that led to deposited structures appeared within 30 days. Overall, these analyses serve as practical guidelines for the design of initial screening experiments for new crystallization targets.

Computational crystallization

Crystallization is a key step in macromolecular structure determination by crystallography. While a robust theoretical treatment of the process is available, due to the complexity of the system, the experimental process is still largely one of trial and error. In this article, efforts in the field are discussed together with a theoretical underpinning using a solubility phase diagram. Prior knowledge has been used to develop tools that computationally predict the crystallization outcome and define mutational approaches that enhance the likelihood of crystallization. For the most part these tools are based on binary outcomes (crystal or no crystal), and the full information contained in an assembly of crystallization screening experiments is lost. The potential of this additional information is illustrated by examples where new biological knowledge can be obtained and where a target can be sub-categorized to predict which class of reagents provides the crystallization driving force. Computational analysis of crystallization requires complete and correctly formatted data. While massive crystallization screening efforts are under way, the data available from many of these studies are sparse. The potential for this data and the steps needed to realize this potential are discussed.

Single Molecule Cluster Analysis dissects splicing pathway conformational dynamics

We report Single Molecule Cluster Analysis (SiMCAn), which utilizes hierarchical clustering of hidden Markov modeling-fitted single-molecule fluorescence resonance energy transfer (smFRET) trajectories to dissect the complex conformational dynamics of biomolecular machines. We used this method to study the conformational dynamics of a precursor mRNA during the splicing cycle as carried out by the spliceosome. By clustering common dynamic behaviors derived from selectively blocked splicing reactions, SiMCAn was able to identify the signature conformations and dynamic behaviors of multiple ATP-dependent intermediates. In addition, it identified an open conformation adopted late in splicing by a 3' splice-site mutant, invoking a mechanism for substrate proofreading. SiMCAn enables rapid interpretation of complex single-molecule behaviors and should prove useful for the comprehensive analysis of a plethora of dynamic cellular machines.

Human insulin polymorphism upon ligand binding and pH variation: the case of 4-ethylresorcinol

This study focuses on the effects of the organic ligand 4-ethylresorcinol on the crystal structure of human insulin using powder X-ray crystallography. For this purpose, systematic crystallization experiments have been conducted in the presence of the organic ligand and zinc ions within the pH range 4.50-8.20, while observing crystallization behaviour around the isoelectric point of insulin. High-throughput crystal screening was performed using a laboratory X-ray diffraction system. The most representative samples were selected for synchrotron X-ray diffraction measurements, which took place at the European Synchrotron Radiation Facility (ESRF) and the Swiss Light Source (SLS). Four different crystalline polymorphs have been identified. Among these, two new phases with monoclinic symmetry have been found, which are targets for the future development of microcrystalline insulin drugs.

Novel crystalline phase and first-order phase transitions of human insulin complexed with two distinct phenol derivatives

The primary focus of the present work is the study of the effects that two ligands and the crystallization pH have on the crystalline forms of human insulin. For this purpose, human insulin (HI) was co-crystallized with two distinct phenolic derivatives: the organic ligandsmeta-cresol (m-cresol) and 4-nitrophenol. The formation of polycrystalline precipitates was then followed by means of structural characterization of the individual specimens in terms of unit-cell symmetry and parameters. In both cases, two different polymorphs were identifiedviaX-ray powder diffraction measurements, the first of hexagonal symmetry (R3 space group) at higher pH values and the second of monoclinic symmetry (space groupP21) with unit-cell parametersa= 87.4282 (5),b = 70.5020 (3),c= 48.3180 (4) Å, β = 106.8958 (4)°, the latter of which to our knowledge has never been observed before.

A drunken search in crystallization space

The REMARK280 field of the Protein Data Bank is the richest open source of successful crystallization information. The REMARK280 field is optional and currently uncurated, so significant effort needs to be applied to extract reliable data. There are well over 15 000 crystallization conditions available commercially from 12 different vendors. After putting the PDB crystallization information and the commercial cocktail data into a consistent format, these data are used to extract information about the overlap between the two sets of crystallization conditions. An estimation is made as to which commercially available conditions are most appropriate for producing well diffracting crystals by looking at which commercial conditions are found unchanged (or almost unchanged) in the PDB. Further analyses include which commercial kits are the most appropriate for shotgun or more traditional approaches to crystallization screening. This analysis suggests that almost 40% of the crystallization conditions found currently in the PDB are identical or very similar to a commercial condition.