Validation of Structures in the Protein Data Bank

Building molecular model series from heterogeneous CryoEM structures using Gaussian mixture models and deep neural networks

Cryogenic electron microscopy (CryoEM) produces structures of macromolecules at near-atomic resolution. However, building molecular models with good stereochemical geometry from those structures can be challenging and time-consuming, especially when many structures are obtained from datasets with conformational heterogeneity. Here we present a model refinement protocol that automatically generates series of molecular models from CryoEM datasets, which describe the dynamics of the macromolecular system and have near-perfect geometry scores. This method makes it easier to interpret the movement of the protein complex from heterogeneity analysis and to compare the structural dynamics observed from CryoEM data with results from other experimental and simulation techniques.

Revealing arginine-cysteine and glycine-cysteine NOS linkages by a systematic re-evaluation of protein structures

Nitrogen-oxygen-sulfur (NOS) linkages act as allosteric redox switches, modulating enzymatic activity in response to redox fluctuations. While NOS linkages in proteins were once assumed to occur only between lysine and cysteine, our investigation shows that these bonds extend beyond the well-studied lysine-NOS-cysteine examples. By systematically analyzing over 86,000 high-resolution X-ray protein structures, we uncovered 69 additional NOS bonds, including arginine-NOS-cysteine and glycine-NOS-cysteine. Our pipeline integrates machine learning, quantum-mechanical calculations, and high-resolution X-ray crystallographic data to systematically detect these subtle covalent interactions and identify key predictive descriptors for their formation. The discovery of these previously unrecognized linkages broadens the scope of protein chemistry and may enable targeted modulation in drug design and protein engineering. Although our study focuses on NOS linkages, the flexibility of this methodology allows for the investigation of a wide range of chemical bonds and covalent modifications, including structurally resolvable posttranslational modifications (PTMs). By revisiting and re-examining well-established protein models, this work underscores how systematic data-driven approaches can uncover hidden aspects of protein chemistry and inspire deeper insights into protein function and stability.

Understanding the structure and function of HPI, a rubber tree serine protease inhibitor, and its interaction with subtilisin

Protease inhibitors are crucial in regulating enzymatic activity and have extensive applications in medicine, biotechnology, and agriculture. This study characterizes a recombinant protease inhibitor from Hevea brasiliensis (rHPI), highlighting its unique structural features and inhibitory potential. Using Matrix-Assisted Laser Desorption/Ionization (MALDI) analysis, the inhibitor exhibits one distinct peak around 7.54 kDa. Enzymatic assays using N-succinyl-Ala-Ala-Pro-Phe-p-nitroanilide as a substrate confirmed the inhibitor's activity against subtilisin Carlsberg, a widely utilized serine protease in industry and biotechnology. The crystal structure of rHPI, resolved at 1.73 Å, reveals a topology closely resembling eglin c, including a single alpha-helix, two parallel beta-strands, and a distinctive binding loop spanning residues 40-51. Disordered regions at the N- and C-termini contribute to its structural uniqueness. Despite lacking disulfide bonds and featuring an Arg residue instead of Trp at the P'8 position, rHPI maintains a high affinity for subtilisin. Isothermal titration calorimetry (ITC) showed that this interaction is entropically driven. Molecular docking and dynamics simulations of the rHPI-subtilisin complex revealed the formation of antiparallel β-sheets, hydrogen bonding involving the protein backbone, and a salt bridge between His64 of subtilisin and Asp47 of rHPI. These findings provide valuable insights into the molecular basis of rHPI's inhibitory activity and offer a framework for the rational design of novel subtilisin inhibitors with potential applications in agricultural and industrial settings.

Identification of phytochemicals from genus Potentilla as estrogen receptor-α inhibitors through molecular docking, molecular dynamic simulation and DFT calculations

Breast cancer is among the most prevalent causes of death in women worldwide. About 70-75% of these cancers are hormone-dependent, expressing estrogen receptors (ERs), mainly ER-α, making it an essential target for managing breast cancer. Potentilla genus has been traditionally used worldwide for its diverse biological activities, including antidiabetic, anti-inflammatory, antioxidant, etc. In the present study, phytochemicals isolated from various species of the Potentilla species were evaluated for their in silico ER-α inhibitory activity through molecular docking, molecular dynamic simulation, Density Functional Theory calculations and free energy calculations. Four hundred seventy-one molecules were used through ligand preparation and docked inside the generated grid on ER-α protein cavity and the standard drug tamoxifen. Fourteen molecules have shown better dock (-14.42 to -12.57 kcal/mol) scores than tamoxifen (-10.71 kcal/mol). Most of the molecules belong to the category of flavonoid glycosides. Molecules with good binding free energy (-78.81 to -12.94 kcal/mol) indicate stability inside the binding pocket. Further, based on dock score, pharmacokinetic parameters, and binding free energy, two hit molecules, 1 and 2, were selected for their molecular dynamic simulation, MM/PBSA and DFT calculations for assessing their stability and structural dynamics inside the binding cavity as well as their reactivity. Through MD simulation analysis, it was evaluated that Compound 1 could distort the protein to a greater extent. In contrast, compound 2 was stable throughout the simulation time of 150 ns and can be further explored in vitro and in vivo studies as ER-α inhibitors in breast cancer.

Molecular structure and enzymatic mechanism of the human collagen hydroxylysine galactosyltransferase GLT25D1/COLGALT1

During collagen biosynthesis, lysine residues undergo extensive post-translational modifications through the alternate action of two distinct metal ion-dependent enzyme families (i.e., LH/PLODs and GLT25D/COLGALT), ultimately producing the highly conserved α-(1,2)-glucosyl-β-(1,O)-galactosyl-5-hydroxylysine pattern. Malfunctions in these enzymes are linked to developmental pathologies and extracellular matrix alterations associated to enhanced aggressiveness of solid tumors. Here, we characterized human GLT25D1/COLGALT1, revealing an elongated head-to-head homodimeric assembly. Each monomer encompasses two domains (named GT1 and GT2), both unexpectedly capable of binding metal ion cofactors and UDP-α-galactose donor substrates, resulting in four candidate catalytic sites per dimer. We identify the catalytic site in GT2, featuring an unusual Glu-Asp-Asp motif critical for Mn2+ binding, ruling out direct catalytic roles for the GT1 domain, but showing that in this domain the unexpectedly bound Ca2+ and UDP-α-galactose cofactors are critical for folding stability. Dimerization, albeit not essential for GLT25D1/COLGALT1 activity, provides a critical molecular contact site for multi-enzyme assembly interactions with partner multifunctional LH/PLOD lysyl hydroxylase-glycosyltransferase enzymes.

PDBe tools for an in-depth analysis of small molecules in the Protein Data Bank

The Protein Data Bank (PDB) is the primary global repository for experimentally determined 3D structures of biological macromolecules and their complexes with ligands, proteins, and nucleic acids. PDB contains over 47,000 unique small molecules bound to the macromolecules. Despite the extensive data available, the complexity of small-molecule data in the PDB necessitates specialized tools for effective analysis and visualization. PDBe has developed a number of tools, including PDBe CCDUtils (https://github.com/PDBeurope/ccdutils) for accessing and enriching ligand data, PDBe Arpeggio (https://github.com/PDBeurope/arpeggio) for analyzing interactions between ligands and macromolecules, and PDBe RelLig (https://github.com/PDBeurope/rellig) for identifying the functional roles of ligands (such as reactants, cofactors, or drug-like molecules) within protein-ligand complexes. The enhanced ligand annotations and data generated by these tools are presented on the novel PDBe-KB ligand pages, offering a comprehensive overview of small molecules and providing valuable insights into their biological contexts (example page for Imatinib: https://pdbe.org/chem/sti). By improving the standardization of ligand identification, adding various annotations, and offering advanced visualization capabilities, these tools help researchers navigate the complexities of small molecules and their roles in biological systems, facilitating mechanistic understanding of biological functions. The ongoing enhancements to these resources are designed to support the scientific community in gaining valuable insights into ligands and their applications across various fields, including drug discovery, molecular biology, systems biology, structural biology, and pharmacology.

Visualizing and analyzing 3D biomolecular structures using Mol* at RCSB.org: Influenza A H5N1 virus proteome case study

The easiest and often most useful way to work with experimentally determined or computationally predicted structures of biomolecules is by viewing their three-dimensional (3D) shapes using a molecular visualization tool. Mol* was collaboratively developed by RCSB Protein Data Bank (RCSB PDB, RCSB.org) and Protein Data Bank in Europe (PDBe, PDBe.org) as an open-source, web-based, 3D visualization software suite for examination and analyses of biostructures. It is capable of displaying atomic coordinates and related experimental data of biomolecular structures together with a variety of annotations, facilitating basic and applied research, training, education, and information dissemination. Across RCSB.org, the RCSB PDB research-focused web portal, Mol* has been implemented to support single-mouse-click atomic-level visualization of biomolecules (e.g., proteins, nucleic acids, carbohydrates) with bound cofactors, small-molecule ligands, ions, water molecules, or other macromolecules. RCSB.org Mol* can seamlessly display 3D structures from various sources, allowing structure interrogation, superimposition, and comparison. Using influenza A H5N1 virus as a topical case study of an important pathogen, we exemplify how Mol* has been embedded within various RCSB.org tools-allowing users to view polymer sequence and structure-based annotations integrated from trusted bioinformatics data resources, assess patterns and trends in groups of structures, and view structures of any size and compositional complexity. In addition to being linked to every experimentally determined biostructure and Computed Structure Model made available at RCSB.org, Standalone Mol* is freely available for visualizing any atomic-level or multi-scale biostructure at rcsb.org/3d-view.

ExploreTurns: A web tool for the exploration, analysis, and classification of beta turns and structured loops in proteins; application to beta-bulge and Schellman loops, Asx helix caps, beta hairpins, and other hydrogen-bonded motifs

The most common type of protein secondary structure after the alpha helix and beta sheet is the four-residue beta turn, which plays many key structural and functional roles. Existing tools for the study of beta turns operate in backbone dihedral-angle (Ramachandran) space, which presents challenges for the visualization, comparison and analysis of the wide range of turn conformations. In this work, a new turn-local coordinate system and structural alignment, together with a set of geometric descriptors for turn backbone shape, are incorporated into ExploreTurns, a web facility for the exploration, analysis, geometric tuning and retrieval of beta turns and their contexts which combines the advantages of Ramachandran- and Euclidean-space representations. Due to the prevalence of beta turns in proteins, this facility, supported by its interpreter for a new general nomenclature which classifies H-bonded loop motifs and beta hairpins, serves as an exploratory browser and analysis tool for most loop structure. The tool is applied to the detection of new H-bonded loops, including short and "double" Schellman loops, a large family of beta-bulge loops with a range of geometries and H-bond topologies, and other motifs. Other applications presented here include the mapping of sequence preferences in Asx helix N-caps and an investigation of the depth dependence of beta-turn geometry. ExploreTurns, available at www.betaturn.com, should prove useful in research, education, and applications such as protein design, in which an enhanced Euclidean-space picture of turn and motif structure and the ability to identify and tune structures suited to particular requirements may improve performance.

Biochemical, structural, and cellular characterization of S-but-3-yn-2-ylglycine as a mechanism-based covalent inactivator of the flavoenzyme proline dehydrogenase

The mitochondrial flavoenzymes proline dehydrogenase (PRODH) and hydroxyproline dehydrogenase (PRODH2) catalyze the first steps of proline and hydroxyproline catabolism, respectively. The enzymes are targets for chemical probe development because of their roles in cancer cell metabolism (PRODH) and primary hyperoxaluria (PRODH2). Mechanism-based inactivators of PRODH target the FAD by covalently modifying the N5 atom, with N-propargylglycine (NPPG) being the current best-in-class of this type of probe. Here we investigated a close analog of NPPG, but-3-yn-2-ylglycine (B32G), distinguished by having a methyl group adjacent to the ethynyl group of the propargyl warhead. UV-visible spectroscopy shows that a bacterial PRODH catalyzes the oxidation of the S-enantiomer of B32G, a necessary first step in mechanism-based inactivation. In contrast, the enzyme does not react with the R-enantiomer. Enzyme activity assays show that S-B32G inhibits bacterial PRODH in a time-dependent manner consistent with covalent inactivation; however, the inactivation efficiency is ∼600-times lower than NPPG. We generated the crystal structure of PRODH inactivated by S-B32G at 1.68 Å resolution and found that inactivation induces a covalent link between the FAD N5 and the ε-nitrogen of an active site lysine, confirming that S-B32G follows the same mechanism as NPPG. Despite its lower inactivation efficiency at the purified bacterial enzyme, S-B32G exhibited comparable activity to NPPG against PRODH and PRODH2 in human cells and mouse livers. Molecular modeling is used to rationalize the stereospecificity of B32G.

Structure-Activity Relationships and Biological Insights into PSMA-617 and Its Derivatives with Modified Lipophilic Linker Regions

PSMA-617 is recognized as a benchmark ligand for prostate-specific membrane antigen (PSMA) owing to its broad utilization in prostate cancer (PCa) targeted radionuclide therapy. In this study, the structure-activity relationships (SAR) of PSMA-617 and two novel analogs featuring modified linkers were investigated. In compounds P17 and P18, the 2-naphthyl-l-Ala moiety was replaced with a less lipophilic 3-styryl-l-Ala moiety while the cyclohexyl ring in P18 was replaced with a phenyl group. The first ever crystal structure of the PSMA/PSMA-617 complex reported here revealed a folded conformation of the PSMA-617 linker while for the PSMA/P17 and PSMA/P18 complexes, the extended orientations of the linkers revealed linker flexibility within the PSMA cavity, a change in binding that can be exploited for the structure-guided design of PSMA-targeting agents. Despite structural differences from PSMA-617, the analogs maintained high PSMA inhibition potency, cellular binding, and internalization. In vivo biodistribution studies revealed comparable tumor uptake across all three compounds with P18 displaying higher spleen accumulation, likely due to phenyl ring lipophilicity. These SAR findings provide a strategic framework for the rational design of PSMA ligands, paving the way for the development of next-generation theranostic agents for PCa.

Structural, functional, and regulatory evaluation of a cysteine post-translationally modified Gcn5-related N-acetyltransferase

Polyamines within the cell are tightly regulated by spermidine/spermine N-acetyltransferase (SSAT) enzymes. While several SSATs have been investigated in different bacterial species, there is still a significant gap in knowledge about which proteins are functional SSATs in many organisms. For example, while it is known that Pseudomonas aeruginosa synthesizes the polyamine spermidine, the SSAT that acetylates this molecule and its importance in regulating intracellular polyamines remains unknown. We previously identified a candidate Gcn5-related N-acetyltransferase (GNAT) protein from P. aeruginosa (PA2271) that could fulfill this role since it acetylates spermidine, but no further studies were conducted. Here, we explored the structure/function relationship of the PA2271 protein by determining its X-ray crystal structure and performing enzyme kinetics assays. We also identified active site residues that are essential for catalysis and substrate binding. As the study progressed, we encountered results that led us to explore the importance of four cysteine residues on enzyme activity and disulfide bond formation or modification of cysteine residues. We found these cysteine residues in PA2271 are important for protein solubility and activity, and there is an interrelationship between cysteine residues that contribute to these effects. Furthermore, we also found disulfide bonds could form between C121 and C165 and speculate that these residues may contribute to redox regulation of PA2271 protein activity.

PSSKB: A Web Application to Study Protein Structures

The proteins expressed during the cell cycle determine cell function and ensure signaling pathway activation in response to environmental influences. Developments in structural biology, biophysics, and bioinformatics provide information on the structure and function of particular proteins including that on the structural changes in proteins due to post-translational modification (PTM) and amino acid substitutions (AAS), which is essential for understanding protein function and life cycle. These are PTMs and AASs that often modulate the function and alter the stability and localization of a protein in a cell. PSSKB is a platform that integrates all necessary tools for modeling the five common natural modifications and all canonical AASs in proteins. The available tools are not limited to the local database, so the user can select a protein from Uniprot ID or PDB ID. The result will be a three-dimensional (3D) representation of the modified structure, as well as an analysis of the changes in the performance of the intact and modified structures after energy minimization compared with the original structure, which not only makes it possible to evaluate AAS/PTM influence of on a protein's characteristics but also to use the 3D model for further studies. Additionally, PSSKB enables the user to search, align, overlay, and determine the exact coordinates of protein structure fragments. The search results are a set of structural motifs similar to the query and ranked by statistical significance. The platform is fully functional and publicly available at https://psskb.org/. No registration is required to access the platform. A tutorial video can be found at https://psskb.org/page/about. Services provided on the platform are based on previously developed and published software. SCPacker applied for PTM Modeling and AAS services available at GitHub (https://github.com/protdb/SCPacker). SaFoldNet applied for a Similar Search service is also available at GitHub (https://github.com/protdb/ABBNet).

Q - score as a reliability measure for protein, nucleic acid, and small molecule atomic coordinate models derived from 3DEM density maps

Atomic coordinate models are important in the interpretation of 3D maps produced with cryoEM and sub-tomogram averaging in cryoET, or more generically, 3D electron microscopy (3DEM). In addition to visual inspection of such maps and models, quantitative metrics convey the reliability of the atomic coordinates, in particular how well the model is supported by the experimentally determined 3DEM map. A recently introduced metric, Q - score , was shown to correlate well with the reported resolution of the map for well-fitted models. Here we present new statistical analyses of Q - scores based on its application to ∼ 10,000 maps and models archived in EMDB and PDB. Further we introduce two new metrics based on Q - score : Q - relative - all and Q - relative - resolution to compare a map and model to all entries in the EMDB and those with similar resolution respectively. We also explore through illustrative examples of proteins, nucleic acids, and small molecules how Q - scores can indicate whether the atomic coordinates are well-fitted to 3DEM maps and whether some parts of a map may be poorly resolved due to factors such as molecular flexibility, radiation damage, and/or conformational heterogeneity. Lastly, we show examples of how Q - scores can effectively be converted to atomic B - factors . These analyses provide a basis for how Q - scores can be interpreted effectively to evaluate 3DEM maps and atomic coordinate models prior to publication and archiving.

PhiSiCal-Checkup: A Bayesian framework to validate amino acid conformations within experimental protein structures

As structural biology and drug discovery depend on high-quality protein structures, assessment tools are essential. We describe a new method for validating amino-acid conformations: "PhiSiCal ([Formula: see text]al) Checkup." Twenty new joint probability distributions in the form of statistical mixture models explain the empirical distributions of dihedral angles [Formula: see text] of canonical amino acids in experimental protein structures. Marginal and conditional probability distributions for subsets of dihedral angles are derived from these joint mixture models. Together, these distributions are employed to measure rapidly the information-theoretic "favorability" of any proposed experimental protein structure. The inferred statistical models and measures overcome several shortcomings and afford improvements over the current state of the art in amino-acid conformation verification. Experimental comparisons are made against current protein conformation verification software. In a number of examples, we pick up outliers that are invisible to current methods. We also calculate, as part of verification, the sensitivity of favorability to small changes in a proposed structure accounting for the precision of coordinates. In some cases a near neighbor of a proposed amino-acid conformation may be either less or more favorable. This raises the question, is the current reliance on fixed "thresholds" for validation a good thing? PhiSiCal-Checkup is freely available for online and offline (open-source) use from https://lcb.infotech.monash.edu.au/phisical/checkup.

The 1.3 Å resolution structure of the truncated group Ia type IV pilin from Pseudomonas aeruginosa strain P1

The type IV pilus is a diverse molecular machine capable of conferring a variety of functions and is produced by a wide range of bacterial species. The ability of the pilus to perform host-cell adherence makes it a viable target for the development of vaccines against infection by human pathogens such as Pseudomonas aeruginosa. Here, the 1.3 Å resolution crystal structure of the N-terminally truncated type IV pilin from P. aeruginosa strain P1 (ΔP1) is reported, the first structure of its phylogenetically linked group (group I) to be discussed in the literature. The structure was solved from X-ray diffraction data that were collected 20 years ago with a molecular-replacement search model generated using AlphaFold; the effectiveness of other search models was analyzed. Examination of the high-resolution ΔP1 structure revealed a solvent network that aids in maintaining the fold of the protein. On comparing the sequence and structure of P1 with a variety of type IV pilins, it was observed that there are cases of higher structural similarities between the phylogenetic groups of P. aeruginosa than there are between the same phylogenetic group, indicating that a structural grouping of pilins may be necessary in developing antivirulence drugs and vaccines. These analyses also identified the α-β loop as the most structurally diverse domain of the pilins, which could allow it to serve a role in pilus recognition. Studies of ΔP1 in vitro polymerization demonstrate that the optimal hydrophobic catalyst for the oligomerization of the pilus from strain K122 is not conducive for pilus formation of ΔP1; a model of a three-start helical assembly using the ΔP1 structure indicates that the α-β loop and the D-loop prevent in vitro polymerization.

Everyone is using biological structures, but how does one find the structure(s) one wants?

A comment on how easy (or difficult) it is to find a stucture of interest and some suggestions on what could be done to start to address the problem.

Structural basis of α-latrotoxin transition to a cation-selective pore

The potent neurotoxic venom of the black widow spider contains a cocktail of seven phylum-specific latrotoxins (LTXs), but only one, α-LTX, targets vertebrates. This 130 kDa toxin binds to receptors at presynaptic nerve terminals and triggers a massive release of neurotransmitters. It is widely accepted that LTXs tetramerize and insert into the presynaptic membrane, thereby forming Ca2+-conductive pores, but the underlying mechanism remains poorly understood. LTXs are homologous and consist of an N-terminal region with three distinct domains, along with a C-terminal domain containing up to 22 consecutive ankyrin repeats. Here we report cryoEM structures of the vertebrate-specific α-LTX tetramer in its prepore and pore state. Our structures, in combination with AlphaFold2-based structural modeling and molecular dynamics simulations, reveal dramatic conformational changes in the N-terminal region of the complex. Four distinct helical bundles rearrange and together form a highly stable, 15 nm long, cation-impermeable coiled-coil stalk. This stalk, in turn, positions an N-terminal pair of helices within the membrane, thereby enabling the assembly of a cation-permeable channel. Taken together, these data give insight into a unique mechanism for membrane insertion and channel formation, characteristic of the LTX family, and provide the necessary framework for advancing novel therapeutics and biotechnological applications.

Building molecular model series from heterogeneous CryoEM structures using Gaussian mixture models and deep neural networks

Cryogenic electron microscopy (CryoEM) produces structures of macromolecules at near-atomic resolution. However, building molecular models with good stereochemical geometry from those structures can be challenging and time-consuming, especially when many structures are obtained from datasets with conformational heterogeneity. Here we present a model refinement protocol that automatically generates series of molecular models from CryoEM datasets, which describe the dynamics of the macromolecular system and have near-perfect geometry scores.

Molecular Mechanism of pH-Induced Protrusion Configuration Switching in Piscine Betanodavirus Implies a Novel Antiviral Strategy

Many viruses contain surface spikes or protrusions that are essential for virus entry. These surface structures can thereby be targeted by antiviral drugs to treat viral infections. Nervous necrosis virus (NNV), a simple nonenveloped virus in the genus of betanodavirus, infects fish and damages aquaculture worldwide. NNV has 60 conspicuous surface protrusions, each comprising three protrusion domains (P-domain) of its capsid protein. NNV uses protrusions to bind to common receptors of sialic acids on the host cell surface to initiate its entry via the endocytic pathway. However, structural alterations of NNV in response to acidic conditions encountered during this pathway remain unknown, while detailed interactions of protrusions with receptors are unclear. Here, we used cryo-EM to discover that Grouper NNV protrusions undergo low-pH-induced compaction and resting. NMR and molecular dynamics (MD) simulations were employed to probe the atomic details. A solution structure of the P-domain at pH 7.0 revealed a long flexible loop (amino acids 311-330) and a pocket outlined by this loop. Molecular docking analysis showed that the N-terminal moiety of sialic acid inserted into this pocket to interact with conserved residues inside. MD simulations demonstrated that part of this loop converted to a β-strand under acidic conditions, allowing for P-domain trimerization and compaction. Additionally, a low-pH-favored conformation is attained for the linker connecting the P-domain to the NNV shell, conferring resting protrusions. Our findings uncover novel pH-dependent conformational switching mechanisms underlying NNV protrusion dynamics potentially utilized for facilitating NNV entry, providing new structural insights into complex NNV-host interactions with the identification of putative druggable hotspots on the protrusion.

Characterization of thermostable carboxypeptidase from high-altitude hot spring metagenome

This study explored the metagenome of the Pir Panjal Hot Spring (PPHS) to identify thermostable hydrolases. The carboxypeptidase (CarP) gene was successfully amplified and cloned into Escherichia coli DH5-α cells, followed by expression in E. coli BL21-DE3 cells. The CarP enzyme was comprehensively characterized in vitro. Sequencing analysis revealed an open reading frame encoding a functional protein of 504 amino acids, with a molecular weight of 58.65 kDa and an isoelectric point of 4.81. The CarP protein was purified using Ni-His affinity chromatography, and the experimental molecular weight matched in silico predictions. The enzyme exhibited significant thermostability and alkaliphilic properties, with optimal activity at 70 °C and pH 10.0. Additionally, the presence of Zn+2 ions at concentrations of 5 and 10 mmol/L enhanced protease activity by 1.4 and 1.5-fold, respectively. This study reports the discovery of a novel, multifunctional, and thermostable CarP from hot-spring metagenomes. The enzyme's stability against high temperatures, metal ions, surfactants, and inhibitors, along with its specific substrate interactions, highlights its potential for various biotechnological applications.

Geometric descriptors for beta turns

Beta turns, in which the protein backbone abruptly changes direction over four amino acid residues, are the most common type of protein secondary structure after alpha helices and beta sheets and play key structural and functional roles. Previous work has produced classification systems for turn geometry at multiple levels of precision, but these operate in backbone dihedral-angle (Ramachandran) space, and the absence of a local Euclidean-space coordinate system and structural alignment for turns, or of any systematic Euclidean-space characterization of turn backbone shape, presents challenges for the visualization, comparison and analysis of the wide range of turn conformations and the design of turns and the structures that incorporate them. This work derives a turn-local coordinate system that implicitly aligns turns, together with a set of geometric descriptors that characterize the bulk BB shapes of turns and describe modes of structural variation not explicitly captured by existing systems. These modes are shown to be meaningful by the demonstration of clear relationships between descriptor values and the electrostatic energy of the beta-turn H-bond, the overrepresentations of key side-chain motifs, and the structural contexts of turns. Geometric turn descriptors complement Ramachandran-space classifications, and they can be used to select turn structures for compatibility with particular side-chain interactions or contexts. Potential applications include protein design and other tasks in which an enhanced Euclidean-space characterization of turns may improve understanding or performance. The web-based tools ExploreTurns, MapTurns, and ProfileTurn, available at www.betaturn.com, incorporate turn-local coordinates and turn descriptors and demonstrate their utility.

Structural insights into binding of polyglutamylated tetrahydrofolate by serine hydroxymethyltransferase 8 from soybean

Tetrahydrofolate and its derivatives participate in one-carbon transfer reactions in all organisms. The cellular form of tetrahydrofolate (THF) is modified by multiple glutamate residues and polyglutamylation plays a key role in organellar and cellular folate homeostasis. In addition, polyglutamylation of THF is known to increase the binding affinity to enzymes in the folate cycle, many of which can utilize polyglutamylated THF as a substrate. Here, we use X-ray crystallography to provide a high-resolution view of interactions between the enzyme serine hydroxymethyltransferase (SHMT), which provides one carbon precursors for the folate cycle, and a polyglutamylated form of THF. Our 1.7 Å crystal structure of soybean SHMT8 in complex with diglutamylated 5-formyl-THF reveals, for the first time, a structural rearrangement of a loop at the entrance to the folate binding site accompanied by the formation of novel specific interactions between the enzyme and the diglutamyl tail of the ligand. Biochemical assays show that additional glutamate moieties on the folate ligand increase both enzyme stability and binding affinity. Together these studies provide new information on SHMT structure and function and inform the design of anti-folate agents.

MDavocado: Analysis and Visualization of Protein Motion by Time-Dependent Angular Diagrams

Extracting meaningful information from atomistic molecular dynamics (MD) simulations of proteins remains a challenging task due to the high-dimensionality and complexity of the data. MD simulations yield trajectories that contain the positions of thousands of atoms in millions of steps. Gaining a comprehensive understanding of local dynamical events across the entire trajectory is often difficult. Here, we present a novel approach to visualize MD trajectories in the form of time-dependent Ramachandran plots. Specialized data aggregation techniques are employed to address the challenge of plotting millions of data points on a single image, thereby ensuring that the analysis is independent of the molecule size and/or length of the MD simulation. This approach facilitates quick identification of flexible and dynamic regions, and its strength is the ability to simultaneously observe the movements of all amino acids over time. The Python program MDavocado is freely available at GitHub (https://github.com/zoranstefanic/MDavocado).

The structure assessment web server: for proteins, complexes and more

The 'structure assessment' web server is a one-stop shop for interactive evaluation and benchmarking of structural models of macromolecular complexes including proteins and nucleic acids. A user-friendly web dashboard links sequence with structure information and results from a variety of state-of-the-art tools, which facilitates the visual exploration and evaluation of structure models. The dashboard integrates stereochemistry information, secondary structure information, global and local model quality assessment of the tertiary structure of comparative protein models, as well as prediction of membrane location. In addition, a benchmarking mode is available where a model can be compared to a reference structure, providing easy access to scores that have been used in recent CASP experiments and CAMEO. The structure assessment web server is available at https://swissmodel.expasy.org/assess.

Outcomes of the EMDataResource cryo-EM Ligand Modeling Challenge

The EMDataResource Ligand Model Challenge aimed to assess the reliability and reproducibility of modeling ligands bound to protein and protein-nucleic acid complexes in cryogenic electron microscopy (cryo-EM) maps determined at near-atomic (1.9-2.5 Å) resolution. Three published maps were selected as targets: Escherichia coli beta-galactosidase with inhibitor, SARS-CoV-2 virus RNA-dependent RNA polymerase with covalently bound nucleotide analog and SARS-CoV-2 virus ion channel ORF3a with bound lipid. Sixty-one models were submitted from 17 independent research groups, each with supporting workflow details. The quality of submitted ligand models and surrounding atoms were analyzed by visual inspection and quantification of local map quality, model-to-map fit, geometry, energetics and contact scores. A composite rather than a single score was needed to assess macromolecule+ligand model quality. These observations lead us to recommend best practices for assessing cryo-EM structures of liganded macromolecules reported at near-atomic resolution.

Validation of electron-microscopy maps using solution small-angle X-ray scattering

The determination of the atomic resolution structure of biomacromolecules is essential for understanding details of their function. Traditionally, such a structure determination has been performed with crystallographic or nuclear resonance methods, but during the last decade, cryogenic transmission electron microscopy (cryo-TEM) has become an equally important tool. As the blotting and flash-freezing of the samples can induce conformational changes, external validation tools are required to ensure that the vitrified samples are representative of the solution. Although many validation tools have already been developed, most of them rely on fully resolved atomic models, which prevents early screening of the cryo-TEM maps. Here, a novel and automated method for performing such a validation utilizing small-angle X-ray scattering measurements, publicly available through the new software package AUSAXS, is introduced and implemented. The method has been tested on both simulated and experimental data, where it was shown to work remarkably well as a validation tool. The method provides a dummy atomic model derived from the EM map which best represents the solution structure.

Screening a knowledge-based library of low molecular weight compounds against the proline biosynthetic enzyme 1-pyrroline-5-carboxylate 1 (PYCR1)

Δ1-pyrroline-5-carboxylate reductase isoform 1 (PYCR1) is the last enzyme of proline biosynthesis and catalyzes the NAD(P)H-dependent reduction of Δ1-pyrroline-5-carboxylate to L-proline. High PYCR1 gene expression is observed in many cancers and linked to poor patient outcomes and tumor aggressiveness. The knockdown of the PYCR1 gene or the inhibition of PYCR1 enzyme has been shown to inhibit tumorigenesis in cancer cells and animal models of cancer, motivating inhibitor discovery. We screened a library of 71 low molecular weight compounds (average MW of 131 Da) against PYCR1 using an enzyme activity assay. Hit compounds were validated with X-ray crystallography and kinetic assays to determine affinity parameters. The library was counter-screened against human Δ1-pyrroline-5-carboxylate reductase isoform 3 and proline dehydrogenase (PRODH) to assess specificity/promiscuity. Twelve PYCR1 and one PRODH inhibitor crystal structures were determined. Three compounds inhibit PYCR1 with competitive inhibition parameter of 100 μM or lower. Among these, (S)-tetrahydro-2H-pyran-2-carboxylic acid (70 μM) has higher affinity than the current best tool compound N-formyl-l-proline, is 30 times more specific for PYCR1 over human Δ1-pyrroline-5-carboxylate reductase isoform 3, and negligibly inhibits PRODH. Structure-affinity relationships suggest that hydrogen bonding of the heteroatom of this compound is important for binding to PYCR1. The structures of PYCR1 and PRODH complexed with 1-hydroxyethane-1-sulfonate demonstrate that the sulfonate group is a suitable replacement for the carboxylate anchor. This result suggests that the exploration of carboxylic acid isosteres may be a promising strategy for discovering new classes of PYCR1 and PRODH inhibitors. The structure of PYCR1 complexed with l-pipecolate and NADH supports the hypothesis that PYCR1 has an alternative function in lysine metabolism.

Protein purification, crystallization, and structure determination of transcription factor YhaJ in complex with DNT metabolites

The microbial transcription factor YhaJ responds to 2,4-dinitrotoluene (DNT) derivatives. Here, we describe steps for overexpression and purification of the protein, characterization for the binding of a DNT derivative methylhydroquinone, and crystallization by using a random seeding technique. We then detail procedures for structure determination by employing the crystal-twin resolving processes. This protocol can also be performed using other DNT derivatives. For complete details on the use and execution of this protocol, please refer to Kim et al.1.

Restraint validation of biomolecular structures determined by NMR in the Protein Data Bank

Biomolecular structure analysis from experimental NMR studies generally relies on restraints derived from a combination of experimental and knowledge-based data. A challenge for the structural biology community has been a lack of standards for representing these restraints, preventing the establishment of uniform methods of model-vs-data structure validation against restraints and limiting interoperability between restraint-based structure modeling programs. The NEF and NMR-STAR formats provide a standardized approach for representing commonly used NMR restraints. Using these restraint formats, a standardized validation system for assessing structural models of biopolymers against restraints has been developed and implemented in the wwPDB OneDep data deposition-validation-biocuration system. The resulting wwPDB restraint violation report provides a model vs. data assessment of biomolecule structures determined using distance and dihedral restraints, with extensions to other restraint types currently being implemented. These tools are useful for assessing NMR models, as well as for assessing biomolecular structure predictions based on distance restraints.

RCSB Protein Data Bank: supporting research and education worldwide through explorations of experimentally determined and computationally predicted atomic level 3D biostructures

The Protein Data Bank (PDB) was established as the first open-access digital data resource in biology and medicine in 1971 with seven X-ray crystal structures of proteins. Today, the PDB houses >210 000 experimentally determined, atomic level, 3D structures of proteins and nucleic acids as well as their complexes with one another and small molecules (e.g. approved drugs, enzyme cofactors). These data provide insights into fundamental biology, biomedicine, bioenergy and biotechnology. They proved particularly important for understanding the SARS-CoV-2 global pandemic. The US-funded Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) and other members of the Worldwide Protein Data Bank (wwPDB) partnership jointly manage the PDB archive and support >60 000 `data depositors' (structural biologists) around the world. wwPDB ensures the quality and integrity of the data in the ever-expanding PDB archive and supports global open access without limitations on data usage. The RCSB PDB research-focused web portal at https://www.rcsb.org/ (RCSB.org) supports millions of users worldwide, representing a broad range of expertise and interests. In addition to retrieving 3D structure data, PDB `data consumers' access comparative data and external annotations, such as information about disease-causing point mutations and genetic variations. RCSB.org also provides access to >1 000 000 computed structure models (CSMs) generated using artificial intelligence/machine-learning methods. To avoid doubt, the provenance and reliability of experimentally determined PDB structures and CSMs are identified. Related training materials are available to support users in their RCSB.org explorations.

A database overview of metal-coordination distances in metalloproteins

Metalloproteins are ubiquitous in all living organisms and take part in a very wide range of biological processes. For this reason, their experimental characterization is crucial to obtain improved knowledge of their structure and biological functions. The three-dimensional structure represents highly relevant information since it provides insight into the interaction between the metal ion(s) and the protein fold. Such interactions determine the chemical reactivity of the bound metal. The available PDB structures can contain errors due to experimental factors such as poor resolution and radiation damage. A lack of use of distance restraints during the refinement and validation process also impacts the structure quality. Here, the aim was to obtain a thorough overview of the distribution of the distances between metal ions and their donor atoms through the statistical analysis of a data set based on more than 115 000 metal-binding sites in proteins. This analysis not only produced reference data that can be used by experimentalists to support the structure-determination process, for example as refinement restraints, but also resulted in an improved insight into how protein coordination occurs for different metals and the nature of their binding interactions. In particular, the features of carboxylate coordination were inspected, which is the only type of interaction that is commonly present for nearly all metals.

Biochemical, structural, and computational analyses of two new clinically identified missense mutations of ALDH7A1

Aldehyde dehydrogenase 7A1 (ALDH7A1) catalyzes a step of lysine catabolism. Certain missense mutations in the ALDH7A1 gene cause pyridoxine dependent epilepsy (PDE), a rare autosomal neurometabolic disorder with recessive inheritance that affects almost 1:65,000 live births and is classically characterized by recurrent seizures from the neonatal period. We report a biochemical, structural, and computational study of two novel ALDH7A1 missense mutations that were identified in a child with rare recurrent seizures from the third month of life. The mutations affect two residues in the oligomer interfaces of ALDH7A1, Arg134 and Arg441 (Arg162 and Arg469 in the HGVS nomenclature). The corresponding enzyme variants R134S and R441C (p.Arg162Ser and p.Arg469Cys in the HGVS nomenclature) were expressed in Escherichia coli and purified. R134S and R441C have 10,000- and 50-fold lower catalytic efficiency than wild-type ALDH7A1, respectively. Sedimentation velocity analytical ultracentrifugation shows that R134S is defective in tetramerization, remaining locked in a dimeric state even in the presence of the tetramer-inducing coenzyme NAD+. Because the tetramer is the active form of ALDH7A1, the defect in oligomerization explains the very low catalytic activity of R134S. In contrast, R441C exhibits wild-type oligomerization behavior, and the 2.0 Å resolution crystal structure of R441C complexed with NAD+ revealed no obvious structural perturbations when compared to the wild-type enzyme structure. Molecular dynamics simulations suggest that the mutation of Arg441 to Cys may increase intersubunit ion pairs and alter the dynamics of the active site gate. Our biochemical, structural, and computational data on two novel clinical variants of ALDH7A1 add to the complexity of the molecular determinants underlying pyridoxine dependent epilepsy.

Conformational changes in the Niemann-Pick type C1 protein NCR1 drive sterol translocation

The membrane protein Niemann-Pick type C1 (NPC1, named NCR1 in yeast) is central to sterol homeostasis in eukaryotes. Saccharomyces cerevisiae NCR1 is localized to the vacuolar membrane, where it is suggested to carry sterols across the protective glycocalyx and deposit them into the vacuolar membrane. However, documentation of a vacuolar glycocalyx in fungi is lacking, and the mechanism for sterol translocation has remained unclear. Here, we provide evidence supporting the presence of a glycocalyx in isolated S. cerevisiae vacuoles and report four cryo-EM structures of NCR1 in two distinct conformations, named tense and relaxed. These two conformations illustrate the movement of sterols through a tunnel formed by the luminal domains, thus bypassing the barrier presented by the glycocalyx. Based on these structures and on comparison with other members of the Resistance-Nodulation-Division (RND) superfamily, we propose a transport model that links changes in the luminal domains with a cycle of protonation and deprotonation within the transmembrane region of the protein. Our model suggests that NPC proteins work by a generalized RND mechanism where the proton motive force drives conformational changes in the transmembrane domains that are allosterically coupled to luminal/extracellular domains to promote sterol transport.

Novel Fragment Inhibitors of PYCR1 from Docking-Guided X-ray Crystallography

The proline biosynthetic enzyme Δ1-pyrroline-5-carboxylate (P5C) reductase 1 (PYCR1) is one of the most consistently upregulated enzymes across multiple cancer types and central to the metabolic rewiring of cancer cells. Herein, we describe a fragment-based, structure-first approach to the discovery of PYCR1 inhibitors. Thirty-seven fragment-like carboxylic acids in the molecular weight range of 143-289 Da were selected from docking and then screened using X-ray crystallography as the primary assay. Strong electron density was observed for eight compounds, corresponding to a crystallographic hit rate of 22%. The fragments are novel compared to existing proline analog inhibitors in that they block both the P5C substrate pocket and the NAD(P)H binding site. Four hits showed inhibition of PYCR1 in kinetic assays, and one has lower apparent IC50 than the current best proline analog inhibitor. These results show proof-of-concept for our inhibitor discovery approach and provide a basis for fragment-to-lead optimization.

Community recommendations on cryoEM data archiving and validation

In January 2020, a workshop was held at EMBL-EBI (Hinxton, UK) to discuss data requirements for the deposition and validation of cryoEM structures, with a focus on single-particle analysis. The meeting was attended by 47 experts in data processing, model building and refinement, validation, and archiving of such structures. This report describes the workshop's motivation and history, the topics discussed, and the resulting consensus recommendations. Some challenges for future methods-development efforts in this area are also highlighted, as is the implementation to date of some of the recommendations.

Structural, Biochemical, and Computational Characterization of Sulfamides as Bimetallic Peptidase Inhibitors

The sulfonamide function is used extensively as a general building block in various inhibitory scaffolds and, more specifically, as a zinc-binding group (ZBG) of metalloenzyme inhibitors. Here, we provide biochemical, structural, and computational characterization of a metallopeptidase in complex with inhibitors, where the mono- and bisubstituted sulfamide functions are designed to directly engage zinc ions of a bimetallic enzyme site. Structural data showed that while monosubstituted sulfamides coordinate active-site zinc ions via the free negatively charged amino group in a canonical manner, their bisubstituted counterparts adopt an atypical binding pattern divergent from expected positioning of corresponding tetrahedral reaction intermediates. Accompanying quantum mechanics calculations revealed that electroneutrality of the sulfamide function is a major factor contributing to the markedly lower potency of bisubstituted compounds by considerably lowering their interaction energy with the enzyme. Overall, while bisubstituted uncharged sulfamide functions can bolster favorable pharmacological properties of a given inhibitor, their use as ZBGs in metalloenzyme inhibitors might be less advantageous due to their suboptimal metal-ligand properties.

Community recommendations on cryoEM data archiving and validation: Outcomes of a wwPDB/EMDB workshop on cryoEM data management, deposition and validation

In January 2020, a workshop was held at EMBL-EBI (Hinxton, UK) to discuss data requirements for deposition and validation of cryoEM structures, with a focus on single-particle analysis. The meeting was attended by 47 experts in data processing, model building and refinement, validation, and archiving of such structures. This report describes the workshop's motivation and history, the topics discussed, and consensus recommendations resulting from the workshop. Some challenges for future methods-development efforts in this area are also highlighted, as is the implementation to date of some of the recommendations.

Outcomes of the EMDataResource Cryo-EM Ligand Modeling Challenge

The EMDataResource Ligand Model Challenge aimed to assess the reliability and reproducibility of modeling ligands bound to protein and protein/nucleic-acid complexes in cryogenic electron microscopy (cryo-EM) maps determined at near-atomic (1.9-2.5 Å) resolution. Three published maps were selected as targets: E. coli beta-galactosidase with inhibitor, SARS-CoV-2 RNA-dependent RNA polymerase with covalently bound nucleotide analog, and SARS-CoV-2 ion channel ORF3a with bound lipid. Sixty-one models were submitted from 17 independent research groups, each with supporting workflow details. We found that (1) the quality of submitted ligand models and surrounding atoms varied, as judged by visual inspection and quantification of local map quality, model-to-map fit, geometry, energetics, and contact scores, and (2) a composite rather than a single score was needed to assess macromolecule+ligand model quality. These observations lead us to recommend best practices for assessing cryo-EM structures of liganded macromolecules reported at near-atomic resolution.

Restraint Validation of Biomolecular Structures Determined by NMR in the Protein Data Bank

Biomolecular structure analysis from experimental NMR studies generally relies on restraints derived from a combination of experimental and knowledge-based data. A challenge for the structural biology community has been a lack of standards for representing these restraints, preventing the establishment of uniform methods of model-vs-data structure validation against restraints and limiting interoperability between restraint-based structure modeling programs. The NMR exchange (NEF) and NMR-STAR formats provide a standardized approach for representing commonly used NMR restraints. Using these restraint formats, a standardized validation system for assessing structural models of biopolymers against restraints has been developed and implemented in the wwPDB OneDep data deposition-validation-biocuration system. The resulting wwPDB Restraint Violation Report provides a model vs. data assessment of biomolecule structures determined using distance and dihedral restraints, with extensions to other restraint types currently being implemented. These tools are useful for assessing NMR models, as well as for assessing biomolecular structure predictions based on distance restraints.

The wwPDB Consortium, Turner J, Abbott S, Fonseca N, Pye R, Carrijo L, Duraisamy AK, Salih O, Wang Z, Kleywegt GJ, Morris KL, Patwardhan A, Burley SK, Crichlow G, Feng Z, Flatt JW, Ghosh S, Hudson BP, Lawson CL, Liang Y, Peisach E, Persikova I, Sekharan M, Shao C, Young J, Velankar S, Armstrong D, Bage M, Bueno WM, Evans G, Gaborova R, Ganguly S, Gupta D, Harrus D, Tanweer A, Bansal M, Rangannan V, Kurisu G, Cho H, Ikegawa Y, Kengaku Y, Kim JY, Niwa S, Sato J, Takuwa A, Yu J, Hoch JC, Baskaran K, Xu W, Zhang W, Ma X. EMDB-the Electron Microscopy Data Bank

The Electron Microscopy Data Bank (EMDB) is the global public archive of three-dimensional electron microscopy (3DEM) maps of biological specimens derived from transmission electron microscopy experiments. As of 2021, EMDB is managed by the Worldwide Protein Data Bank consortium (wwPDB; wwpdb.org) as a wwPDB Core Archive, and the EMDB team is a core member of the consortium. Today, EMDB houses over 30 000 entries with maps containing macromolecules, complexes, viruses, organelles and cells. Herein, we provide an overview of the rapidly growing EMDB archive, including its current holdings, recent updates, and future plans.

Determining Protein Structures Using X-Ray Crystallography

X-ray crystallography is a robust and widely used technique that facilitates the three-dimensional structure determination of proteins at an atomic scale. This methodology entails the growth of protein crystals under controlled conditions followed by their exposure to X-ray beams and the subsequent analysis of the resulting diffraction patterns via computational tools to determine the three-dimensional architecture of the protein. However, achieving high-resolution structures through X-ray crystallography can be quite challenging due to complexities associated with protein purity, crystallization efficiency, and crystal quality.In this chapter, we provide a detailed overview of the gene to structure determination pipeline used in X-ray crystallography, a crucial tool for understanding protein structures. The chapter covers the steps in protein crystallization, along with the processes of data collection, processing, structure determination, and refinement. The most commonly faced challenges throughout this procedure are also addressed. Finally, the importance of standardized protocols for reproducibility and accuracy is emphasized, as they are crucial for advancing the understanding of protein structure and function.

In silico prediction and in vitro assessment of novel heterocyclics with antimalarial activity

The development of new antimalarials is paramount to keep the goals on reduction of malaria cases in endemic regions. The search for quality hits has been challenging as many inhibitory molecules may not progress to the next development stage. The aim of this work was to screen an in-house library of heterocyclic compounds (HCUV) for antimalarial activity combining computational predictions and phenotypic techniques to find quality hits. The physicochemical determinants, pharmacokinetic properties (ADME), and drug-likeness of HCUV were evaluated in silico, and compounds were selected for structure-based virtual screening and in vitro analysis. Seven Plasmodium target proteins were selected from the DrugBank Database, and ligands and receptors were processed using UCSF Chimera and Open Babel before being subjected to docking using Autodock Vina and Autodock 4. Growth inhibition of P. falciparum (3D7) cultures was tested by SYBR Green assays, and toxicity was assessed using hemolytic activity tests and the Galleria mellonella in vivo model. From a total of 792 compounds, 341 with good ADME properties, drug-likeness, and no interference structures were subjected to in vitro analysis. Eight compounds showed IC50 ranging from 0.175 to 0.990 µM, and active compounds included pyridyl-diaminopyrimido-diazepines, pyridyl-N-acetyl- and pyridyl-N-phenyl-pyrazoline derivatives. The most potent compound (UV802, IC50 0.178 µM) showed no toxicophoric and was predicted to interact with P. falciparum 1-cysperoxidredoxin (PfPrx1). For the remaining 7 hits (IC50 < 1 μM), 3 showed in silico binding to PfPrx1, one was predicted to bind the haloacid dehalogenase-like hydrolase and plasmepsin II, and one interacted with the plasmodial heat shock protein 90.

Virtual Model Compound Approach for Calculating Redox Potentials of [Fe2S2]-Cys4 Centers in Proteins - Structure Quality Matters

The midpoint potential of the [Fe2S2]-Cys4-cluster in proteins is known to vary between -200 and -450 mV. This variation is caused by the different electrostatic environment of the cluster in the respective proteins. Continuum electrostatics can quantify the impact of the protein environment on the redox potential. Thus, if the redox potential of a [Fe2S2]-Cys4-cluster model compound in aqueous solution would be known, then redox potentials in various protein complexes could be calculated. However, [Fe2S2]-Cys4-cluster models are not water-soluble, and thus, their redox potential can not be measured in aqueous solution. To overcome this problem, we introduce a method that we call Virtual Model Compound Approach (VMCA) to extrapolate the model redox potential from known redox potentials of proteins. We carefully selected high-resolution structures for our analysis and divide them into a fit set, for fitting the model redox potential, and an independent test set, to check the validity of the model redox potential. However, from our analysis, we realized that the some structures can not be used as downloaded from the PDB but had to be re-refined in order to calculate reliable redox potentials. Because of the re-refinement, we were able to significantly reduce the standard deviation of our derived model redox potential for the [Fe2S2]-Cys4-cluster from 31 mV to 10 mV. As the model redox potential, we obtained -184 mV. This model redox potential can be used to analyze the redox behavior of [Fe2S2]-Cys4-clusters in larger protein complexes.

Automated benchmarking of combined protein structure and ligand conformation prediction

The prediction of protein-ligand complexes (PLC), using both experimental and predicted structures, is an active and important area of research, underscored by the inclusion of the Protein-Ligand Interaction category in the latest round of the Critical Assessment of Protein Structure Prediction experiment CASP15. The prediction task in CASP15 consisted of predicting both the three-dimensional structure of the receptor protein as well as the position and conformation of the ligand. This paper addresses the challenges and proposed solutions for devising automated benchmarking techniques for PLC prediction. The reliability of experimentally solved PLC as ground truth reference structures is assessed using various validation criteria. Similarity of PLC to previously released complexes are employed to judge PLC diversity and the difficulty of a PLC as a prediction target. We show that the commonly used PDBBind time-split test-set is inappropriate for comprehensive PLC evaluation, with state-of-the-art tools showing conflicting results on a more representative and high quality dataset constructed for benchmarking purposes. We also show that redocking on crystal structures is a much simpler task than docking into predicted protein models, demonstrated by the two PLC-prediction-specific scoring metrics created. Finally, we introduce a fully automated pipeline that predicts PLC and evaluates the accuracy of the protein structure, ligand pose, and protein-ligand interactions.

Structural and functional insights into the delivery of a bacterial Rhs pore-forming toxin to the membrane

Bacterial competition is a significant driver of toxin polymorphism, which allows continual compensatory evolution between toxins and the resistance developed to overcome their activity. Bacterial Rearrangement hot spot (Rhs) proteins represent a widespread example of toxin polymorphism. Here, we present the 2.45 Å cryo-electron microscopy structure of Tse5, an Rhs protein central to Pseudomonas aeruginosa type VI secretion system-mediated bacterial competition. This structural insight, coupled with an extensive array of biophysical and genetic investigations, unravels the multifaceted functional mechanisms of Tse5. The data suggest that interfacial Tse5-membrane binding delivers its encapsulated pore-forming toxin fragment to the target bacterial membrane, where it assembles pores that cause cell depolarisation and, ultimately, bacterial death.

Crystal Structure of Inhibitor-Bound GII.4 Sydney 2012 Norovirus 3C-Like Protease

Norovirus is the leading cause of viral gastroenteritis worldwide, and there are no approved vaccines or therapeutic treatments for chronic or severe norovirus infections. The structural characterisation of the norovirus protease and drug development has predominantly focused upon GI.1 noroviruses, despite most global outbreaks being caused by GII.4 noroviruses. Here, we determined the crystal structures of the GII.4 Sydney 2012 ligand-free norovirus protease at 2.79 Å and at 1.83 Å with a covalently bound high-affinity (IC50 = 0.37 µM) protease inhibitor (NV-004). We show that the active sites of the ligand-free protease structure are present in both open and closed conformations, as determined by their Arg112 side chain orientation. A comparative analysis of the ligand-free and ligand-bound protease structures reveals significant structural differences in the active site cleft and substrate-binding pockets when an inhibitor is covalently bound. We also report a second molecule of NV-004 non-covalently bound within the S4 substrate binding pocket via hydrophobic contacts and a water-mediated hydrogen bond. These new insights can guide structure-aided drug design against the GII.4 genogroup of noroviruses.

SARS-CoV-2 proteins structural studies using synchrotron radiation

In the process of the development of structural biology, both the size and the complexity of the determined macromolecular structures have grown significantly. As a result, the range of application areas for the results of structural studies of biological macromolecules has expanded. Significant progress in the development of structural biology methods has been largely achieved through the use of synchrotron radiation. Modern sources of synchrotron radiation allow to conduct high-performance structural studies with high temporal and spatial resolution. Thus, modern techniques make it possible to obtain not only static structures, but also to study dynamic processes, which play a key role in understanding biological mechanisms. One of the key directions in the development of structural research is the drug design based on the structures of biomolecules. Synchrotron radiation offers insights into the three-dimensional time-resolved structure of individual viral proteins and their complexes at atomic resolution. The rapid and accurate determination of protein structures is crucial for understanding viral pathogenicity and designing targeted therapeutics. Through the application of experimental techniques, including X-ray crystallography and small-angle X-ray scattering (SAXS), it is possible to elucidate the structural details of SARS-CoV-2 virion containing 4 structural, 16 nonstructural proteins (nsp), and several accessory proteins. The most studied potential targets for vaccines and drugs are the structural spike (S) protein, which is responsible for entering the host cell, as well as nonstructural proteins essential for replication and transcription, such as main protease (Mpro), papain-like protease (PLpro), and RNA-dependent RNA polymerase (RdRp). This article provides a brief overview of structural analysis techniques, with focus on synchrotron radiation-based methods applied to the analysis of SARS-CoV-2 proteins.

Announcing the launch of Protein Data Bank China as an Associate Member of the Worldwide Protein Data Bank Partnership

The Protein Data Bank (PDB) is the single global archive of atomic-level, three-dimensional structures of biological macromolecules experimentally determined by macromolecular crystallography, nuclear magnetic resonance spectroscopy or three-dimensional cryo-electron microscopy. The PDB is growing continuously, with a recent rapid increase in new structure depositions from Asia. In 2022, the Worldwide Protein Data Bank (wwPDB; https://www.wwpdb.org/) partners welcomed Protein Data Bank China (PDBc; https://www.pdbc.org.cn) to the organization as an Associate Member. PDBc is based in the National Facility for Protein Science in Shanghai which is associated with the Shanghai Advanced Research Institute of Chinese Academy of Sciences, the Shanghai Institute for Advanced Immunochemical Studies and the iHuman Institute of ShanghaiTech University. This letter describes the history of the wwPDB, recently established mechanisms for adding new wwPDB data centers and the processes developed to bring PDBc into the partnership.

N-acetylmuramic acid recognition by MurK kinase from the MurNAc auxotrophic oral pathogen Tannerella forsythia

The bacterial cell wall consists of a three-dimensional peptidoglycan layer, composed of peptides linked to the sugars N-acetylmuramic acid (MurNAc) and GlcNAc. Unlike other bacteria, the pathogenic Tannerella forsythia, a member of the red complex group of bacteria associated with the late stages of periodontitis, lacks biosynthetic pathways for MurNAc production and therefore obtains MurNAc from the environment. Sugar kinases play a crucial role in the MurNAc recycling process, activating the sugar molecules by phosphorylation. In this study, we present the first crystal structures of a MurNAc kinase, called murein sugar kinase (MurK), in its unbound state as well as in complexes with the ATP analog β-γ-methylene adenosine triphosphate (AMP-PCP) and with MurNAc. We also determined the crystal structures of K1058, a paralogous MurNAc kinase of T. forsythia, in its unbound state and in complex with MurNAc. We identified the active site and residues crucial for MurNAc specificity as the less bulky side chains of S133, P134, and L135, which enlarge the binding cavity for the lactyl ether group, unlike the glutamate or histidine residues present in structural homologs. In establishing the apparent kinetic parameters for both enzymes, we showed a comparable affinity for MurNAc (Km 180 μM and 30 μM for MurK and K1058, respectively), with MurK being over two hundred times faster than K1058 (Vmax 80 and 0.34 μmol min-1 mg-1, respectively). These data might support a structure-guided approach to development of inhibitory MurNAc analogs for pathogen MurK enzymes.