Lignin is often overlooked in the valorization of lignocellulosic biomass, but lignin-based materials and chemicals represent potential value-added products for biorefineries that could significantly improve the economics of a biorefinery. Fluctuating crude oil prices and changing fuel specifications are some of the driving factors to develop new technologies that could be used to convert polymeric lignin into low molecular weight lignin and or monomeric aromatic feedstocks to assist in the displacement of the current products associated with the conversion of a whole barrel of oil. We present an approach to produce these chemicals based on the selective breakdown of lignin during ionic liquid pretreatment.
The lignin breakdown products generated are found to be dependent on the starting biomass, and significant levels were generated on dissolution at 160°C for 6 hrs. Guaiacol was produced on dissolution of biomass and technical lignins. Vanillin was produced on dissolution of kraft lignin and eucalytpus. Syringol and allyl guaiacol were the major products observed on dissolution of switchgrass and pine, respectively, whereas syringol and allyl syringol were obtained by dissolution of eucalyptus. Furthermore, it was observed that different lignin-derived products could be generated by tuning the process conditions.
We have developed an ionic liquid based process that depolymerizes lignin and converts the low molecular weight lignin fractions into a variety of renewable chemicals from biomass. The generated chemicals (phenols, guaiacols, syringols, eugenol, catechols), their oxidized products (vanillin, vanillic acid, syringaldehyde) and their easily derivatized hydrocarbons (benzene, toluene, xylene, styrene, biphenyls and cyclohexane) already have relatively high market value as commodity and specialty chemicals, green building materials, nylons, and resins.
Lignin valorization; Ionic liquid pretreatment; Renewable chemicals; Biofuels
The statistical effects of translational noncrystallographic symmetry can be characterized by maximizing parameters describing the noncrystallographic symmetry in a likelihood function, thereby unmasking the competing statistical effects of twinning.
In the case of translational noncrystallographic symmetry (tNCS), two or more copies of a component in the asymmetric unit of the crystal are present in a similar orientation. This causes systematic modulations of the reflection intensities in the diffraction pattern, leading to problems with structure determination and refinement methods that assume, either implicitly or explicitly, that the distribution of intensities is a function only of resolution. To characterize the statistical effects of tNCS accurately, it is necessary to determine the translation relating the copies, any small rotational differences in their orientations, and the size of random coordinate differences caused by conformational differences. An algorithm to estimate these parameters and refine their values against a likelihood function is presented, and it is shown that by accounting for the statistical effects of tNCS it is possible to unmask the competing statistical effects of twinning and tNCS and to more robustly assess the crystal for the presence of twinning.
translational noncrystallographic symmetry; intensity statistics; twinning; maximum likelihood
Single-structure models derived from X-ray data do not adequately account for the inherent, functionally important dynamics of protein molecules. We generated ensembles of structures by time-averaged refinement, where local molecular vibrations were sampled by molecular-dynamics (MD) simulation whilst global disorder was partitioned into an underlying overall translation–libration–screw (TLS) model. Modeling of 20 protein datasets at 1.1–3.1 Å resolution reduced cross-validated Rfree values by 0.3–4.9%, indicating that ensemble models fit the X-ray data better than single structures. The ensembles revealed that, while most proteins display a well-ordered core, some proteins exhibit a ‘molten core’ likely supporting functionally important dynamics in ligand binding, enzyme activity and protomer assembly. Order–disorder changes in HIV protease indicate a mechanism of entropy compensation for ordering the catalytic residues upon ligand binding by disordering specific core residues. Thus, ensemble refinement extracts dynamical details from the X-ray data that allow a more comprehensive understanding of structure–dynamics–function relationships.
It has been clear since the early days of structural biology in the late 1950s that proteins and other biomolecules are continually changing shape, and that these changes have an important influence on both the structure and function of the molecules. X-ray diffraction can provide detailed information about the structure of a protein, but only limited information about how its structure fluctuates over time. Detailed information about the dynamic behaviour of proteins is essential for a proper understanding of a variety of processes, including catalysis, ligand binding and protein–protein interactions, and could also prove useful in drug design.
Currently most of the X-ray crystal structures in the Protein Data Bank are ‘snap-shots’ with limited or no information about protein dynamics. However, X-ray diffraction patterns are affected by the dynamics of the protein, and also by distortions of the crystal lattice, so three-dimensional (3D) models of proteins ought to take these phenomena into account. Molecular-dynamics (MD) computer simulations transform 3D structures into 4D ‘molecular movies’ by predicting the movement of individual atoms.
Combining MD simulations with crystallographic data has the potential to produce more realistic ensemble models of proteins in which the atomic fluctuations are represented by multiple structures within the ensemble. Moreover, in addition to improved structural information, this process—which is called ensemble refinement—can provide dynamical information about the protein. Earlier attempts to do this ran into problems because the number of model parameters needed was greater than the number of observed data points. Burnley et al. now overcome this problem by modelling local molecular vibrations with MD simulations and, at the same time, using a course-grain model to describe global disorder of longer length scales.
Ensemble refinement of high-resolution X-ray diffraction datasets for 20 different proteins from the Protein Data Bank produced a better fit to the data than single structures for all 20 proteins. Ensemble refinement also revealed that 3 of the 20 proteins had a ‘molten core’, rather than the well-ordered residues core found in most proteins: this is likely to be important in various biological functions including ligand binding, filament formation and enzymatic function. Burnley et al. also showed that a HIV enzyme underwent an order–disorder transition that is likely to influence how this enzyme works, and that similar transitions might influence the interactions between the small-molecule drug Imatinib (also known as Gleevec) and the enzymes it targets. Ensemble refinement could be applied to the majority of crystallography data currently being collected, or collected in the past, so further insights into the properties and interactions of a variety of proteins and other biomolecules can be expected.
protein; crystallography; structure; function; dynamics; None
In X-ray crystallography, molecular replacement and subsequent refinement is challenging at low resolution. We compared refinement methods using synchrotron diffraction data of photosystem I at 7.4 Å resolution, starting from different initial models with increasing deviations from the known high-resolution structure. Standard refinement spoiled the initial models moving them further away from the true structure and leading to high Rfree-values. In contrast, DEN-refinement improved even the most distant starting model as judged by Rfree, atomic root-mean-square differences to the true structure, significance of features not included in the initial model, and connectivity of electron density. The best protocol was DEN-refinement with initial segmented rigid-body refinement. For the most distant initial model, the fraction of atoms within 2 Å of the true structure improved from 24% to 60%. We also found a significant correlation between Rfree-values and the accuracy of the model, suggesting that Rfree is useful even at low resolution.
DEN refinement; membrane protein; low-resolution refinement; simulated annealing; free R value
Escherichia coli has the potential to be a powerful biocatalyst for the conversion of lignocellulosic biomass into useful materials such as biofuels and polymers. One important challenge in using E. coli for the transformation of biomass sugars is diauxie, or sequential utilization of different types of sugars. We demonstrate that, by increasing the intracellular levels of the transcription factor XylR, the preferential consumption of arabinose before xylose can be eliminated. In addition, XylR augmentation must be finely tuned for robust coutilization of these two hemicellulosic sugars. Using a novel technique for scarless gene insertion, an additional copy of xylR was inserted into the araBAD operon. The resulting strain was superior at cometabolizing mixtures of arabinose and xylose and was able to produce at least 36% more ethanol than wild-type strains. This strain is a useful starting point for the development of an E. coli biocatalyst that can simultaneously convert all biomass sugars.
X-ray crystallography is a critical tool in the study of biological systems. It is able to provide information that has been a prerequisite to understanding the fundamentals of life. It is also a method that is central to the development of new therapeutics for human disease. Significant time and effort are required to determine and optimize many macromolecular structures because of the need for manual interpretation of complex numerical data, often using many different software packages, and the repeated use of interactive three-dimensional graphics. The Phenix software package has been developed to provide a comprehensive system for macromolecular crystallographic structure solution with an emphasis on automation. This has required the development of new algorithms that minimize or eliminate subjective input in favour of built-in expert-systems knowledge, the automation of procedures that are traditionally performed by hand, and the development of a computational framework that allows a tight integration between the algorithms. The application of automated methods is particularly appropriate in the field of structural proteomics, where high throughput is desired. Features in Phenix for the automation of experimental phasing with subsequent model building, molecular replacement, structure refinement and validation are described and examples given of running Phenix from both the command line and graphical user interface.
Macromolecular Crystallography; Automation; Phenix; X-ray; Diffraction; Python
Thermophilic fungi have attracted increased interest for their ability to secrete enzymes that deconstruct biomass at high temperatures. However, development of thermophilic fungi as enzyme producers for biomass deconstruction has not been thoroughly investigated. Comparing the enzymatic activities of thermophilic fungal strains that grow on targeted biomass feedstocks has the potential to identify promising candidates for strain development. Thielavia terrestris and Thermoascus aurantiacus were chosen for characterization based on literature precedents.
Thermoascus aurantiacus and Thielavia terrestris were cultivated on various biomass substrates and culture supernatants assayed for glycoside hydrolase activities. Supernatants from both cultures possessed comparable glycoside hydrolase activities when incubated with artificial biomass substrates. In contrast, saccharifications of ionic liquid pretreated switchgrass (Panicum virgatum) revealed that T. aurantiacus enzymes released more glucose than T. terrestris enzymes over a range of protein mass loadings and temperatures. Temperature-dependent saccharifications demonstrated that the T. aurantiacus proteins retained higher levels of activity compared to a commercial enzyme mixture sold by Novozymes, Cellic CTec2, at elevated temperatures. Enzymes secreted by T. aurantiacus released glucose at similar protein loadings to CTec2 on dilute acid, ammonia fiber expansion, or ionic liquid pretreated switchgrass. Proteomic analysis of the T. aurantiacus culture supernatant revealed dominant glycoside hydrolases from families 5, 7, 10, and 61, proteins that are key enzymes in commercial cocktails.
T. aurantiacus produces a complement of secreted proteins capable of higher levels of saccharification of pretreated switchgrass than T. terrestris enzymes. The T. aurantiacus enzymatic cocktail performs at the same level as commercially available enzymatic cocktail for biomass deconstruction, without strain development or genetic modifications. Therefore, T. aurantiacus provides an excellent platform to develop a thermophilic fungal system for enzyme production for the conversion of biomass to biofuels.
Thermoascus aurantiacus; Thielavia terrestris; GH 61; Polysaccharide monooxygenases; Fungal secretome; Ammonia fiber expansion; Ionic liquid; 1-ethyl-3-methylimidazolium acetate; Switchgrass (Panicum virgatum)
Cdc42 is a Ras-related small G-protein, and functions as a molecular switch in signal transduction pathways linked with cell growth and differentiation. It is controlled by cycling between GTP-bound (active) and GDP-bound (inactive) forms. Nucleotide binding and hydrolysis are modulated by interactions with effectors and/or regulatory proteins. These interactions are centralized in two relatively flexible “Switch” regions as characterized by internal dynamics on multiple timescales (Loh et al., (2001) Biochemistry 40, 4590–4600), and this flexibility may be essential for protein interactions. In the Switch I region, Thr35 seems critical for function, as it is completely invariant in Ras-related proteins. To investigate the importance of conformational flexibility in Switch I of Cdc42, we mutated threonine to alanine, determined the solution structure and characterized the backbone dynamics of the single-point mutant protein, Cdc42(T35A). Backbone dynamics data suggests that the mutation changes the timescale of the internal motions of several residues, with several resonances appearing not discernable in Cdc42 wild type (Adams and Oswald (2007) Biomolecular NMR Assignments 1, 225–227). The mutation does not appear to affect the thermal stability of Cdc42, and chymotrypsin digestion data further suggests that changes in conformational flexibility in Switch I slow proteolytic cleavage relative to wild type. In-vitro binding assays show reduced binding of Cdc42(T35A), relative to wild type, to a GTPase binding protein that inhibits GTP hydrolysis in Cdc42. These results suggest that the mutation of T35 leads to the loss of conformational freedom in Switch I that could affect effector/regulatory protein interactions.
Ras GTPase; Signal transduction; Cdc42; Threonine; Alanine; Switch 1 mutant; conformational flexibility; backbone dynamics
Metagenomics approaches provide access to environmental genetic diversity for biotechnology applications, enabling the discovery of new enzymes and pathways for numerous catalytic processes. Discovery of new glycoside hydrolases with improved biocatalytic properties for the efficient conversion of lignocellulosic material to biofuels is a critical challenge in the development of economically viable routes from biomass to fuels and chemicals.
Twenty-two putative ORFs (open reading frames) were identified from a switchgrass-adapted compost community based on sequence homology to related gene families. These ORFs were expressed in E. coli and assayed for predicted activities. Seven of the ORFs were demonstrated to encode active enzymes, encompassing five classes of hemicellulases. Four enzymes were over expressed in vivo, purified to homogeneity and subjected to detailed biochemical characterization. Their pH optima ranged between 5.5 - 7.5 and they exhibit moderate thermostability up to ~60-70°C.
Seven active enzymes were identified from this set of ORFs comprising five different hemicellulose activities. These enzymes have been shown to have useful properties, such as moderate thermal stability and broad pH optima, and may serve as the starting points for future protein engineering towards the goal of developing efficient enzyme cocktails for biomass degradation under diverse process conditions.
A density-based procedure is described for improving a homology model that is locally accurate but differs globally. The model is deformed to match the map and refined, yielding an improved starting point for density modification and further model-building.
An approach is presented for addressing the challenge of model rebuilding after molecular replacement in cases where the placed template is very different from the structure to be determined. The approach takes advantage of the observation that a template and target structure may have local structures that can be superimposed much more closely than can their complete structures. A density-guided procedure for deformation of a properly placed template is introduced. A shift in the coordinates of each residue in the structure is calculated based on optimizing the match of model density within a 6 Å radius of the center of that residue with a prime-and-switch electron-density map. The shifts are smoothed and applied to the atoms in each residue, leading to local deformation of the template that improves the match of map and model. The model is then refined to improve the geometry and the fit of model to the structure-factor data. A new map is then calculated and the process is repeated until convergence. The procedure can extend the routine applicability of automated molecular replacement, model building and refinement to search models with over 2 Å r.m.s.d. representing 65–100% of the structure.
molecular replacement; automation; macromolecular crystallography; structure similarity; modeling; Phenix; morphing
In scientific computing, Fortran was the dominant implementation language throughout most of the second part of the 20th century. The many tools accumulated during this time have been difficult to integrate with modern software, which is now dominated by object-oriented languages.
Driven by the requirements of a large-scale scientific software project, we have developed a Fortran to C++ source-to-source conversion tool named FABLE. This enables the continued development of new methods even while switching languages. We report the application of FABLE in three major projects and present detailed comparisons of Fortran and C++ runtime performances.
Our experience suggests that most Fortran 77 codes can be converted with an effort that is minor (measured in days) compared to the original development time (often measured in years). With FABLE it is possible to reuse and evolve legacy work in modern object-oriented environments, in a portable and maintainable way. FABLE is available under a nonrestrictive open source license. In FABLE the analysis of the Fortran sources is separated from the generation of the C++ sources. Therefore parts of FABLE could be reused for other target languages.
Fortran; C++; Source-to-source conversion; Python; Test-driven development
The foundations and current features of a widely used graphical user interface for macromolecular crystallography are described.
A new Python-based graphical user interface for the PHENIX suite of crystallography software is described. This interface unifies the command-line programs and their graphical displays, simplifying the development of new interfaces and avoiding duplication of function. With careful design, graphical interfaces can be displayed automatically, instead of being manually constructed. The resulting package is easily maintained and extended as new programs are added or modified.
macromolecular crystallography; graphical user interfaces; PHENIX
phenix.refine is a program within the PHENIX package that supports crystallographic structure refinement against experimental data with a wide range of upper resolution limits using a large repertoire of model parameterizations. This paper presents an overview of the major phenix.refine features, with extensive literature references for readers interested in more detailed discussions of the methods.
phenix.refine is a program within the PHENIX package that supports crystallographic structure refinement against experimental data with a wide range of upper resolution limits using a large repertoire of model parameterizations. It has several automation features and is also highly flexible. Several hundred parameters enable extensive customizations for complex use cases. Multiple user-defined refinement strategies can be applied to specific parts of the model in a single refinement run. An intuitive graphical user interface is available to guide novice users and to assist advanced users in managing refinement projects. X-ray or neutron diffraction data can be used separately or jointly in refinement. phenix.refine is tightly integrated into the PHENIX suite, where it serves as a critical component in automated model building, final structure refinement, structure validation and deposition to the wwPDB. This paper presents an overview of the major phenix.refine features, with extensive literature references for readers interested in more detailed discussions of the methods.
structure refinement; PHENIX; joint X-ray/neutron refinement; maximum likelihood; TLS; simulated annealing; subatomic resolution; real-space refinement; twinning; NCS
Recent developments in PHENIX are reported that allow the use of reference-model torsion restraints, secondary-structure hydrogen-bond restraints and Ramachandran restraints for improved macromolecular refinement in phenix.refine at low resolution.
Traditional methods for macromolecular refinement often have limited success at low resolution (3.0–3.5 Å or worse), producing models that score poorly on crystallographic and geometric validation criteria. To improve low-resolution refinement, knowledge from macromolecular chemistry and homology was used to add three new coordinate-restraint functions to the refinement program phenix.refine. Firstly, a ‘reference-model’ method uses an identical or homologous higher resolution model to add restraints on torsion angles to the geometric target function. Secondly, automatic restraints for common secondary-structure elements in proteins and nucleic acids were implemented that can help to preserve the secondary-structure geometry, which is often distorted at low resolution. Lastly, we have implemented Ramachandran-based restraints on the backbone torsion angles. In this method, a ϕ,ψ term is added to the geometric target function to minimize a modified Ramachandran landscape that smoothly combines favorable peaks identified from nonredundant high-quality data with unfavorable peaks calculated using a clash-based pseudo-energy function. All three methods show improved MolProbity validation statistics, typically complemented by a lowered R
free and a decreased gap between R
work and R
macromolecular crystallography; low resolution; refinement; automation
DEN refinement and automated model building with AutoBuild were used to determine the structure of a putative succinyl-diaminopimelate desuccinylase from C. glutamicum. This difficult case of molecular-replacement phasing shows that the synergism between DEN refinement and AutoBuild outperforms standard refinement protocols.
Phasing by molecular replacement remains difficult for targets that are far from the search model or in situations where the crystal diffracts only weakly or to low resolution. Here, the process of determining and refining the structure of Cgl1109, a putative succinyl-diaminopimelate desuccinylase from Corynebacterium glutamicum, at ∼3 Å resolution is described using a combination of homology modeling with MODELLER, molecular-replacement phasing with Phaser, deformable elastic network (DEN) refinement and automated model building using AutoBuild in a semi-automated fashion, followed by final refinement cycles with phenix.refine and Coot. This difficult molecular-replacement case illustrates the power of including DEN restraints derived from a starting model to guide the movements of the model during refinement. The resulting improved model phases provide better starting points for automated model building and produce more significant difference peaks in anomalous difference Fourier maps to locate anomalous scatterers than does standard refinement. This example also illustrates a current limitation of automated procedures that require manual adjustment of local sequence misalignments between the homology model and the target sequence.
reciprocal-space refinement; DEN refinement; real-space refinement; automated model building; succinyl-diaminopimelate desuccinylase
The combination of algorithms from the structure-modeling field with those of crystallographic structure determination can broaden the range of templates that are useful for structure determination by the method of molecular replacement. Automated tools in phenix.mr_rosetta simplify the application of these combined approaches by integrating Phenix crystallographic algorithms and Rosetta structure-modeling algorithms and by systematically generating and evaluating models with a combination of these methods. The phenix.mr_rosetta algorithms can be used to automatically determine challenging structures. The approaches used in phenix.mr_rosetta are described along with examples that show roles that structure-modeling can play in molecular replacement.
Molecular replacement; Automation; Macromolecular crystallography; Rosetta; Phenix
The implementation of crystallographic structure-refinement procedures that include both X-ray and neutron data (separate or jointly) in the PHENIX system is described.
Approximately 85% of the structures deposited in the Protein Data Bank have been solved using X-ray crystallography, making it the leading method for three-dimensional structure determination of macromolecules. One of the limitations of the method is that the typical data quality (resolution) does not allow the direct determination of H-atom positions. Most hydrogen positions can be inferred from the positions of other atoms and therefore can be readily included into the structure model as a priori knowledge. However, this may not be the case in biologically active sites of macromolecules, where the presence and position of hydrogen is crucial to the enzymatic mechanism. This makes the application of neutron crystallography in biology particularly important, as H atoms can be clearly located in experimental neutron scattering density maps. Without exception, when a neutron structure is determined the corresponding X-ray structure is also known, making it possible to derive the complete structure using both data sets. Here, the implementation of crystallographic structure-refinement procedures that include both X-ray and neutron data (separate or jointly) in the PHENIX system is described.
structure refinement; neutrons; joint X-ray and neutron refinement; PHENIX
iotbx.cif is a comprehensive toolbox for the development of applications that make use of the CIF format.
iotbx.cif is a new software module for the development of applications that make use of the CIF format. Comprehensive tools are provided for input, output and validation of CIFs, as well as for interconversion with high-level cctbx [Grosse-Kunstleve, Sauter, Moriarty & Adams (2002). J. Appl. Cryst.
35, 126–136] crystallographic objects. The interface to the library is written in Python, whilst parsing is carried out using a compiled parser, combining the performance of a compiled language (C++) with the benefits of using an interpreted language.
iotbx.cif; cctbx; CIF; computer programs
This report presents the conclusions of the X-ray Validation Task Force of the worldwide Protein Data Bank (PDB). The PDB has expanded massively since current criteria for validation of deposited structures were adopted, allowing a much more sophisticated understanding of all the components of macromolecular crystals. The size of the PDB creates new opportunities to validate structures by comparison with the existing database, and the now-mandatory deposition of structure factors creates new opportunities to validate the underlying diffraction data. These developments highlighted the need for a new assessment of validation criteria. The Task Force recommends that a small set of validation data be presented in an easily understood format, relative to both the full PDB and the applicable resolution class, with greater detail available to interested users. Most importantly, we recommend that referees and editors judging the quality of structural experiments have access to a concise summary of well-established quality indicators.
► Validation criteria used by the PDB for X-ray crystal structures have been reassessed ► Key scores should be presented prominently in an easily understood format ► A concise validation report should be available to referees of papers on crystal structures
Small molecules stabilize specific protein conformations from a larger ensemble, enabling molecular switches that control diverse cellular functions. We show here that the converse also holds true, where the conformational state of the estrogen receptor can direct distinct orientations of the bound ligand. “Gain of allostery” mutations that mimic the effects of ligand in driving protein conformation allowed crystallization of the partial agonist ligand WAY-169916 with both the canonical active and inactive conformations of the estrogen receptor. The intermediate transcriptional activity induced by WAY169916 is associated with the ligand binding differently to the active and inactive conformations of the receptor. Analyses of a series of chemical derivatives demonstrated that altering the ensemble of ligand binding orientations changes signaling output. The coupling of different ligand binding orientations to distinct active and inactive protein conformations defines a novel mechanism for titrating allosteric signaling activity.
The Protein Structure Initiative’s Structural Biology Knowledgebase (SBKB, URL: http://sbkb.org) is an open web resource designed to turn the products of the structural genomics and structural biology efforts into knowledge that can be used by the biological community to understand living systems and disease. Here we will present examples on how to use the SBKB to enable biological research. For example, a protein sequence or Protein Data Bank (PDB) structure ID search will provide a list of related protein structures in the PDB, associated biological descriptions (annotations), homology models, structural genomics protein target status, experimental protocols, and the ability to order available DNA clones from the PSI:Biology-Materials Repository. A text search will find publication and technology reports resulting from the PSI’s high-throughput research efforts. Web tools that aid in research, including a system that accepts protein structure requests from the community, will also be described. Created in collaboration with the Nature Publishing Group, the Structural Biology Knowledgebase monthly update also provides a research library, editorials about new research advances, news, and an events calendar to present a broader view of structural genomics and structural biology.
Protein; Protein production; Structural biology; Structural databases; Structural genomics; Theoretical models
A reference table of exact direct-space asymmetric units for the 230 crystallographic space groups is presented, based on a new geometric notation for asymmetric unit conditions.
It is well known that the direct-space asymmetric unit definitions found in the International Tables for Crystallography, Volume A, are inexact at the borders. Face- and edge-specific sub-conditions have to be added to remove parts redundant under symmetry. This paper introduces a concise geometric notation for asymmetric unit conditions. The notation is the foundation for a reference table of exact direct-space asymmetric unit definitions for the 230 crystallographic space-group types. The change-of-basis transformation law for the conditions is derived, which allows the information from the reference table to be used for any space-group setting. We also show how the vertices of an asymmetric unit can easily be computed from the information in the reference table.
asymmetric unit; direct space; space groups
A new software system for automated ligand coordinate and restraint generation is presented.
The electronic Ligand Builder and Optimization Workbench (eLBOW) is a program module of the PHENIX suite of computational crystallographic software. It is designed to be a flexible procedure that uses simple and fast quantum-chemical techniques to provide chemically accurate information for novel and known ligands alike. A variety of input formats and options allow the attainment of a number of diverse goals including geometry optimization and generation of restraints.
ligands; coordinates; restraints; Python; object-oriented programming
Central to crystallographic structure solution is obtaining accurate phases in order to build a molecular model, ultimately followed by refinement of that model to optimize its fit to the experimental diffraction data and prior chemical knowledge. Recent advances in phasing and model refinement and validation algorithms make it possible to arrive at better electron density maps and more accurate models.
It is widely recognized that representing a protein as a single static conformation is inadequate to describe the dynamics essential to the performance of its biological function. We contrast the amino acid displacements below and above the protein dynamical transition temperature, TD∼215K, of hen egg white lysozyme using X-ray crystallography ensembles that are analyzed by molecular dynamics simulations as a function of temperature. We show that measuring structural variations across an ensemble of X-ray derived models captures the activation of conformational states that are of functional importance just above TD, and they remain virtually identical to structural motions measured at 300K. Our results highlight the ability to observe functional structural variations across an ensemble of X-ray crystallographic data, and that residue fluctuations measured in MD simulations at room temperature are in quantitative agreement with the experimental observable.
There is a well-recognized gap between the dynamical motions of proteins required to execute function and the experimental techniques capable of capturing that motion at the atomic level. We show that much experimental detail of dynamical motion is already present in X-ray crystallographic data, which arises from being solved by different research groups using different methodologies under different crystallization conditions, which then capture an ensemble of structures whose variations can be quantified on a residue-by-residue level using local density correlations. We contrast the amino acid displacements below and above the protein dynamical transition temperature, TD∼215K, of hen egg white lysozyme by comparing the X-ray ensemble to MD ensembles as a function of temperature. We show that measuring structural variations across an ensemble of X-ray derived models captures the activation of conformational states that are of functional importance just above TD and they remain virtually identical to structural motions measured at 300K. It provides a novel analysis of large X-ray ensemble data that is useful for the broader structural biology community.