Experimental Electron Density Maps Research Articles

Towards a dependable data set of structures for L-asparaginase research.

The Protein Data Bank (PDB) includes a carefully curated treasury of experimentally derived structural data on biological macromolecules and their various complexes. Such information is fundamental for a multitude of projects that involve large-scale data mining and/or detailed evaluation of individual structures of importance to chemistry, biology and, most of all, to medicine, where it provides the foundation for structure-based drug discovery. However, despite extensive validation mechanisms, it is almost inevitable that among the ∼215 000 entries there will occasionally be suboptimal or incorrect structure models. It is thus vital to apply careful verification procedures to those segments of the PDB that are of direct medicinal interest. Here, such an analysis was carried out for crystallographic models of L-asparaginases, enzymes that include approved drugs for the treatment of certain types of leukemia. The focus was on the adherence of the atomic coordinates to the rules of stereochemistry and their agreement with the experimental electron-density maps. Whereas the current clinical application of L-asparaginases is limited to two bacterial proteins and their chemical modifications, the field of investigations of such enzymes has expanded tremendously in recent years with the discovery of three entirely different structural classes and with numerous reports, not always quite reliable, of the anticancer properties of L-asparaginases of different origins.

Enhancing cryo-EM structure prediction with DeepTracer and AlphaFold2 integration.

Understanding the protein structures is invaluable in various biomedical applications, such as vaccine development. Protein structure model building from experimental electron density maps is a time-consuming and labor-intensive task. To address the challenge, machine learning approaches have been proposed to automate this process. Currently, the majority of the experimental maps in the database lack atomic resolution features, making it challenging for machine learning-based methods to precisely determine protein structures from cryogenic electron microscopy density maps. On the other hand, protein structure prediction methods, such as AlphaFold2, leverage evolutionary information from protein sequences and have recently achieved groundbreaking accuracy. However, these methods often require manual refinement, which is labor intensive and time consuming. In this study, we present DeepTracer-Refine, an automated method that refines AlphaFold predicted structures by aligning them to DeepTracers modeled structure. Our method was evaluated on 39 multi-domain proteins and we improved the average residue coverage from 78.2 to 90.0% and average local Distance Difference Test score from 0.67 to 0.71. We also compared DeepTracer-Refine with Phenixs AlphaFold refinement and demonstrated that our method not only performs better when the initial AlphaFold model is less precise but also surpasses Phenix in run-time performance.

Machine learning to estimate the local quality of protein crystal structures

Low-resolution electron density maps can pose a major obstacle in the determination and use of protein structures. Herein, we describe a novel method, called quality assessment based on an electron density map (QAEmap), which evaluates local protein structures determined by X-ray crystallography and could be applied to correct structural errors using low-resolution maps. QAEmap uses a three-dimensional deep convolutional neural network with electron density maps and their corresponding coordinates as input and predicts the correlation between the local structure and putative high-resolution experimental electron density map. This correlation could be used as a metric to modify the structure. Further, we propose that this method may be applied to evaluate ligand binding, which can be difficult to determine at low resolution.

Conformational Strain of Macrocyclic Peptides in Ligand-Receptor Complexes Based on Advanced Refinement of Bound-State Conformers.

Macrocyclic peptides are an important modality in drug discovery, but molecular design is limited due to the complexity of their conformational landscape. To better understand conformational propensities, global strain energies were estimated for 156 protein-macrocyclic peptide cocrystal structures. Unexpectedly large strain energies were observed when the bound-state conformations were modeled with positional restraints. Instead, low-energy conformer ensembles were generated using xGen that fit experimental X-ray electron density maps and gave reasonable strain energy estimates. The ensembles featured significant conformational adjustments while still fitting the electron density as well or better than the original coordinates. Strain estimates suggest the interaction energy in protein-ligand complexes can offset a greater amount of strain for macrocyclic peptides than for small molecules and non-peptidic macrocycles. Across all molecular classes, the approximate upper bound on global strain energies had the same relationship with molecular size, and bound-state ensembles from xGen yielded favorable binding energy estimates.

Using MemBlob to Analyze Transmembrane Regions Based on Cryo-EM Maps.

Transmembrane proteins include membrane channels, pores, and receptors and, as such, comprise an important part of the proteome, yet our knowledge about them is much less complete than about soluble, globular proteins. An important aspect of transmembrane protein structure is their exact position within the lipid bilayer, a feature hard to investigate experimentally at the atomic level. Here we describe MemBlob, a novel approach utilizing difference electron density maps obtained by cryo-EM studies of transmembrane proteins. The idea behind is that the nonprotein part of such maps carries information on the exact localization of the membrane mimetics used in the experiment and can be used to extract the positional information of the protein within the membrane. MemBlob uses a structural model of the protein and an experimental electron density map to provide an estimation of the surface residues interacting with the membrane.

The permeation mechanism of organic cations through a CNG mimic channel.

Several channels, ranging from TRP receptors to Gap junctions, allow the exchange of small organic solute across cell membrane. However, very little is known about the molecular mechanism of their permeation. Cyclic Nucleotide Gated (CNG) channels, despite their homology with K+ channels and in contrast with them, allow the passage of larger methylated and ethylated ammonium ions like dimethylammonium (DMA) and ethylammonium (EA). We combined electrophysiology and molecular dynamics simulations to examine how DMA interacts with the pore and permeates through it. Due to the presence of hydrophobic groups, DMA enters easily in the channel and, unlike the alkali cations, does not need to cross any barrier. We also show that while the crystal structure is consistent with the presence of a single DMA ion at full occupancy, the channel is able to conduct a sizable current of DMA ions only when two ions are present inside the channel. Moreover, the second DMA ion dramatically changes the free energy landscape, destabilizing the crystallographic binding site and lowering by almost 25 kJ/mol the binding affinity between DMA and the channel. Based on the results of the simulation the experimental electron density maps can be re-interpreted with the presence of a second ion at lower occupancy. In this mechanism the flexibility of the channel plays a key role, extending the classical multi-ion permeation paradigm in which conductance is enhanced by the plain interaction between the ions.

Automatic recognition of ligands in electron density by machine learning.

The correct identification of ligands in crystal structures of protein complexes is the cornerstone of structure-guided drug design. However, cognitive bias can sometimes mislead investigators into modeling fictitious compounds without solid support from the electron density maps. Ligand identification can be aided by automatic methods, but existing approaches are based on time-consuming iterative fitting. Here we report a new machine learning algorithm called CheckMyBlob that identifies ligands from experimental electron density maps. In benchmark tests on portfolios of up to 219 931 ligand binding sites containing the 200 most popular ligands found in the Protein Data Bank, CheckMyBlob markedly outperforms the existing automatic methods for ligand identification, in some cases doubling the recognition rates, while requiring significantly less time. Our work shows that machine learning can improve the automation of structure modeling and significantly accelerate the drug screening process of macromolecule-ligand complexes. Code and data are available on GitHub at https://github.com/dabrze/CheckMyBlob. Supplementary data are available at Bioinformatics online.

Crystal Structure of the Archaeosine Synthase QueF‐Like – Insights into Amidino Transfer and tRNA Recognition by the Tunnel Fold

Crystal Structure of the Archaeosine Synthase QueF‐Like – Insights into Amidino Transfer and tRNA Recognition by the Tunnel Fold

How Nothing Boosts Affinity: Hydrophobic Ligand Binding to the Virtually Vacated S1' Pocket of Thermolysin.

We investigated the hydration state of the deep, well-accessible hydrophobic S1' specificity pocket of the metalloprotease thermolysin with purposefully designed ligands using high-resolution crystallography and isothermal titration calorimetry. The S1' pocket is known to recognize selectively a very stringent set of aliphatic side chains such as valine, leucine, and isoleucine of putative substrates. We engineered a weak-binding ligand covering the active site of the protease without addressing the S1' pocket, thus transforming it into an enclosed cavity. Its sustained accessibility could be proved by accommodating noble gas atoms into the pocket in the crystalline state. The topology and electron content of the enclosed pocket with a volume of 141 Å3 were analyzed using an experimental MAD-phased electron density map that was calibrated to an absolute electron number scale, enabling access to the total electron content within the cavity. Our analysis indicates that the S1' pocket is virtually vacated, thus free of any water molecules. The thermodynamic signature of the reduction of the void within the pocket by growing aliphatic P1' substituents (H, Me, iPr, iBu) reveals a dramatic, enthalpy-dominated gain in free energy of binding resulting in a factor of 41 000 in Kd for the H-to-iBu transformation. Substituents placing polar decoy groups into the pocket to capture putatively present water molecules could not collect any evidence for a bound solvent molecule.

An Experimental Tool to Estimate the Probability of a Nucleotide Presence in the Crystal Structures of the Nucleotide-Protein Complexes.

A correlation between the ligand-protein affinity and the identification of the ligand in the experimental electron density maps obtained by X-ray crystallography has been tested for a number of RNA-binding proteins. Bacterial translation regulators ProQ, TRAP, Rop, and Hfq together with their archaeal homologues SmAP have been used. The equilibrium dissociation constants for the N-methyl-anthraniloyl-labelled adenosine and guanosine monophosphates titrated by the proteins have been determined by the fluorescent anisotropy measurements. The estimated stability of the nucleotide-protein complexes has been matched with a presence of the nucleotides in the structures of the proposed nucleotide-protein complexes. It has been shown that the ribonucleotides can be definitely identified in the experimental electron density maps at equilibrium dissociation constant <10μM. At KD of 20-40μM, long incubation of the protein crystals in the nucleotide solution is required to obtain the structures of the complexes. The complexes with KD value higher than 50μM are not stable enough to survive in crystallization conditions.

A complement to the modern crystallographer's toolbox: caged gadolinium complexes with versatile binding modes.

A set of seven caged gadolinium complexes were used as vectors for introducing the chelated Gd(3+) ion into protein crystals in order to provide strong anomalous scattering for de novo phasing. The complexes contained multidentate ligand molecules with different functional groups to provide a panel of possible interactions with the protein. An exhaustive crystallographic analysis showed them to be nondisruptive to the diffraction quality of the prepared derivative crystals, and as many as 50% of the derivatives allowed the determination of accurate phases, leading to high-quality experimental electron-density maps. At least two successful derivatives were identified for all tested proteins. Structure refinement showed that the complexes bind to the protein surface or solvent-accessible cavities, involving hydrogen bonds, electrostatic and CH-π interactions, explaining their versatile binding modes. Their high phasing power, complementary binding modes and ease of use make them highly suitable as a heavy-atom screen for high-throughput de novo structure determination, in combination with the SAD method. They can also provide a reliable tool for the development of new methods such as serial femtosecond crystallography.

De novo protein crystal structure determination from X-ray free-electron laser data

The determination of protein crystal structures is hampered by the need for macroscopic crystals. X-ray free-electron lasers (FELs) provide extremely intense pulses of femtosecond duration, which allow data collection from nanometre- to micrometre-sized crystals in a 'diffraction-before-destruction' approach. So far, all protein structure determinations carried out using FELs have been based on previous knowledge of related, known structures. Here we show that X-ray FEL data can be used for de novo protein structure determination, that is, without previous knowledge about the structure. Using the emerging technique of serial femtosecond crystallography, we performed single-wavelength anomalous scattering measurements on microcrystals of the well-established model system lysozyme, in complex with a lanthanide compound. Using Monte-Carlo integration, we obtained high-quality diffraction intensities from which experimental phases could be determined, resulting in an experimental electron density map good enough for automated building of the protein structure. This demonstrates the feasibility of determining novel protein structures using FELs. We anticipate that serial femtosecond crystallography will become an important tool for the structure determination of proteins that are difficult to crystallize, such as membrane proteins.

Refined structures of mouse P‐glycoprotein

The recently determined C. elegans P-glycoprotein (Pgp) structure revealed significant deviations compared to the original mouse Pgp structure, which suggested possible misinterpretations in the latter model. To address this concern, we generated an experimental electron density map from single-wavelength anomalous dispersion phasing of an original mouse Pgp dataset to 3.8 Å resolution. The map exhibited significantly more detail compared to the original MAD map and revealed several regions of the structure that required de novo model building. The improved drug-free structure was refined to 3.8 Å resolution with a 9.4 and 8.1% decrease in Rwork and Rfree, respectively, (Rwork = 21.2%, Rfree = 26.6%) and a significant improvement in protein geometry. The improved mouse Pgp model contains ∼95% of residues in the favorable Ramachandran region compared to only 57% for the original model. The registry of six transmembrane helices was corrected, revealing amino acid residues involved in drug binding that were previously unrecognized. Registry shifts (rotations and translations) for three transmembrane (TM)4 and TM5 and the addition of three N-terminal residues were necessary, and were validated with new mercury labeling and anomalous Fourier density. The corrected position of TM4, which forms the frame of a portal for drug entry, had backbone atoms shifted >6 Å from their original positions. The drug translocation pathway of mouse Pgp is 96% identical to human Pgp and is enriched in aromatic residues that likely play a collective role in allowing a high degree of polyspecific substrate recognition.

Electron Properties of Carbamazepine Drug in Form III

The experimental electron and electrostatic properties of carbamazepine drug molecule (form III) were determined from accurate high-resolution X-ray diffraction data collected at 100 K. The results are compared to quantum mechanics calculations for gas-phase molecule and multimers. The experimental electron density was refined using the Hansen–Coppens multipole formalism, and the deformation electron density maps are compared to the theoretical ones. Both experimental and theoretical deformation electron density maps presented here are based on Clementi’s promolecule densities used as a reference. The topological analysis of the carbamazepine electron density using Bader’s theory has been carried out, and the integrated atomic charges are presented and compared to those obtained for molecules with equivalent chemical fragments. The charge values compare qualitatively well with those obtained by theoretical calculations. The electrostatic potential features and the interaction electrostatic energies are also discussed.

Challenges and surprises that arise with nucleic acids during model building and refinement.

The process of building and refining crystal structures of nucleic acids, although similar to that for proteins, has some peculiarities that give rise to both various complications and various benefits. Although conventional isomorphous replacement phasing techniques are typically used to generate an experimental electron-density map for the purposes of determining novel nucleic acid structures, it is also possible to couple the phasing and model-building steps to permit thesolution of complex and novel RNA three-dimensional structures without the need for conventional heavy-atom phasing approaches.

Structure of the Membrane-tethering GRASP Domain Reveals a Unique PDZ Ligand Interaction That Mediates Golgi Biogenesis

Biogenesis of the ribbon-like membrane network of the mammalian Golgi requires membrane tethering by the conserved GRASP domain in GRASP65 and GRASP55, yet the tethering mechanism is not fully understood. Here, we report the crystal structure of the GRASP55 GRASP domain, which revealed an unusual arrangement of two tandem PDZ folds that more closely resemble prokaryotic PDZ domains. Biochemical and functional data indicated that the interaction between the ligand-binding pocket of PDZ1 and an internal ligand on PDZ2 mediates the GRASP self-interaction, and structural analyses suggest that this occurs via a unique mode of internal PDZ ligand recognition. Our data uncover the structural basis for ligand specificity and provide insight into the mechanism of GRASP-dependent membrane tethering of analogous Golgi cisternae.

Mechanism for the Alteration of the Substrate Specificities of Template-Independent RNA Polymerases

PolyA polymerase (PAP) adds a polyA tail onto the 3'-end of RNAs without a nucleic acid template, using adenosine-5'-triphosphate (ATP) as a substrate. The mechanism for the substrate selection by eubacterial PAP remains obscure. Structural and biochemical studies of Escherichia coli PAP (EcPAP) revealed that the shape and size of the nucleobase-interacting pocket of EcPAP are maintained by an intra-molecular hydrogen-network, making it suitable for the accommodation of only ATP, using a single amino acid, Arg(197). The pocket structure is sustained by interactions between the catalytic domain and the RNA-binding domain. EcPAP has a flexible basic C-terminal region that contributes to optimal RNA translocation for processive adenosine 5'-monophosphate (AMP) incorporations onto the 3'-end of RNAs. A comparison of the EcPAP structure with those of other template-independent RNA polymerases suggests that structural changes of domain(s) outside the conserved catalytic core domain altered the substrate specificities of the template-independent RNA polymerases.

Using lanthanoid complexes to phase large macromolecular assemblies.

Lanthanoid ions exhibit extremely large anomalous X-ray scattering at their L(III) absorption edge. They are thus well suited for anomalous diffraction experiments. A novel class of lanthanoid complexes has been developed that combines the physical properties of lanthanoid atoms with functional chemical groups that allow non-covalent binding to proteins. Two structures of large multimeric proteins have already been determined by using such complexes. Here the use of the luminescent europium tris-dipicolinate complex [Eu(DPA)(3)](3-) to solve the low-resolution structure of a 444 kDa homododecameric aminopeptidase, called PhTET1-12s from the archaea Pyrococcus horikoshii, is reported. Surprisingly, considering the low resolution of the data, the experimental electron density map is very well defined. Experimental phases obtained by using the lanthanoid complex lead to maps displaying particular structural features usually observed in higher-resolution maps. Such complexes open a new way for solving the structure of large molecular assemblies, even with low-resolution data.

Interpreting a Low Resolution Map of Human U1 snRNP Using Anomalous Scatterers

SummaryWe recently determined the crystal structure of the functional core of human U1 snRNP, consisting of nine proteins and one RNA, based on a 5.5 Å resolution electron density map. At 5–7 Å resolution, α helices and β sheets appear as rods and slabs, respectively, hence it is not possible to determine protein fold de novo. Using inverse beam geometry, accurate anomalous signals were obtained from weakly diffracting and radiation sensitive P1 crystals. We were able to locate anomalous scatterers with positional errors below 2 Å. This enabled us not only to place protein domains of known structure accurately into the map but also to trace an extended polypeptide chain, of previously undetermined structure, using selenomethionine derivatives of single methionine mutants spaced along the sequence. This method of Se-Met scanning, in combination with structure prediction, is a powerful tool for building a protein of unknown fold into a low resolution electron density map.

A fast selenium derivatization strategy for crystallization and phasing of RNA structures.

Site-specific 2'-methylseleno RNA labeling is a promising tool for tackling the phase problem in RNA crystallography. We have developed an efficient strategy for crystallization and structure determination of RNA and RNA/protein complexes based on preliminary crystallization screening of 2'-OCH(3)-modified RNA sequences, prior to the replacement of 2'-OCH(3) groups with their 2'-SeCH(3) counterparts. The method exploits the similar crystallization properties of 2'-OCH(3)- and 2'-SeCH(3)-modified RNAs and has been successfully validated for two test cases. In addition, our data show that 2'-SeCH(3)-modified RNA have an increased resistance to X-ray radiolysis in comparison with commonly used 5-halogen-modified RNA, which permits collection of experimental electron density maps of remarkable quality.