Many locks to one key: N-acetylneuraminic acid binding to proteins.

Sialic acids play crucial roles in cell surface glycans of both eukaryotic and prokaryotic organisms, mediating various biological processes, including cell-cell interactions, development, immune response, oncogenesis and host-pathogen interactions. This review focuses on the ß-anomeric form of N-acetylneuraminic acid (Neu5Ac), particularly its binding affinity towards various proteins, as elucidated by solved protein structures. Specifically, we delve into the binding mechanisms of Neu5Ac to proteins involved in sequestering and transporting Neu5Ac in Gram-negative bacteria, with implications for drug design targeting these proteins as antimicrobial agents. Unlike the initial assumptions, structural analyses revealed significant variability in the Neu5Ac binding pockets among proteins, indicating diverse evolutionary origins and binding modes. By comparing these findings with existing structures from other systems, we can effectively highlight the intricate relationship between protein structure and Neu5Ac recognition, emphasizing the need for tailored drug design strategies to inhibit Neu5Ac-binding proteins across bacterial species.

Alfin-like (AL) transcription factor family in Oryza sativa L.: Genome-wide analysis and expression profiling under different stresses.

Oryza sativa L. is the world's most essential and economically important food crop. Climate change and ecological imbalances make rice plants vulnerable to abiotic and biotic stresses, threatening global food security. The Alfin-like (AL) transcription factor family plays a crucial role in plant development and stress responses. This study comprehensively analyzed this gene family and their expression profiles in rice, revealing nine AL genes, classifying them into three distinct groups based on phylogenetic analysis and identifying four segmental duplication events. RNA-seq data analysis revealed high expression levels of OsALs in different tissues, growth stages, and their responsiveness to stresses. RT-qPCR data showed significant expression of OsALs in different abiotic stresses. Identification of potential cis-regulatory elements in promoter regions has also unveiled their involvement. Tertiary structures of the proteins were predicted. These findings would lay the groundwork for future research to reveal their molecular mechanism in stress tolerance and plant development.

A predicted model-aided reconstruction algorithm for X-ray free-electron laser single-particle imaging.

Ultra-intense, ultra-fast X-ray free-electron lasers (XFELs) enable the imaging of single protein molecules under ambient temperature and pressure. A crucial aspect of structure reconstruction involves determining the relative orientations of each diffraction pattern and recovering the missing phase information. In this paper, we introduce a predicted model-aided algorithm for orientation determination and phase retrieval, which has been tested on various simulated datasets and has shown significant improvements in the success rate, accuracy and efficiency of XFEL data reconstruction.

Gel Properties and Protein Structures of Minced Pork Prepared with κ-Carrageenan and Non-Meat Proteins.

Problems with minced pork include water release and low gel strength. This study aimed to investigate the effect of treatments with κ-carrageenan (κ-CAR), egg white powder (EWP), wheat gluten (WG), soy isolate protein (SPI), and a combination of these treatments on the gel properties and protein structures of minced pork. The cooking loss and trapped water within minced pork increased when additives were incorporated; in particular, the SPI group reached 1.31 ± 0.01% and 91.42 ± 0.20%. The hardness and chewiness of minced pork reached their maximum values (38.91 ± 0.80 N, 14.73 ± 0.41 N) when the WG was added. The κ-CAR/WG-minced pork gel network structure was the densest and most stable, characterized by increased hydrophobic interactions, disulfide bonds in the mince gel, and enthalpy value. The α-helix content with κ-CAR/WG treatment decreased from 27% to 7.8%, transforming into other secondary structures. This suggests that the addition of κ-CAR/WG can be a more effective combination for improving the quality of minced pork.

Crystal structure of human peptidylarginine deiminase type VI (PAD6) provides insights into its inactivity.

Human peptidylarginine deiminase isoform VI (PAD6), which is predominantly limited to cytoplasmic lattices in the mammalian oocytes in ovarian tissue, is essential for female fertility. It belongs to the peptidylarginine deiminase (PAD) enzyme family that catalyzes the conversion of arginine residues to citrulline in proteins. In contrast to other members of the family, recombinant PAD6 was previously found to be catalytically inactive. We sought to provide structural insight into the human homologue to shed light on this observation. We report here the first crystal structure of PAD6, determined at 1.7 Šresolution. PAD6 follows the same domain organization as other structurally known PAD isoenzymes. Further structural analysis and size-exclusion chromatography show that PAD6 behaves as a homodimer similar to PAD4. Differential scanning fluorimetry suggests that PAD6 does not coordinate Ca2+ which agrees with acidic residues found to coordinate Ca2+ in other PAD homologs not being conserved in PAD6. The crystal structure of PAD6 shows similarities with the inactive state of apo PAD2, in which the active site conformation is unsuitable for catalytic citrullination. The putative active site of PAD6 adopts a non-productive conformation that would not allow protein-substrate binding due to steric hindrance with rigid secondary structure elements. This observation is further supported by the lack of activity on the histone H3 and cytokeratin 5 substrates. These findings suggest a different mechanism for enzymatic activation compared with other PADs; alternatively, PAD6 may exert a non-enzymatic function in the cytoplasmic lattice of oocytes and early embryos.

Structural Insights Into the Terpene Cyclization Domains of Two Fungal Sesterterpene Synthases and Enzymatic Engineering for Sesterterpene Diversification.

Little is known about the structures and catalytic mechanisms of sesterterpene synthases (StTSs), which greatly hinders the structure-based engineering of StTSs for structural diversity expansion of sesterterpenes. We here report on the crystal structures of the terpene cyclization (TC) domains of two fungal StTSs: sesterfisherol synthase (NfSS) and sesterbrasiliatriene synthase (PbSS). Both TC structures contain benzyltriethylammonium chloride (BTAC), pyrophosphate (PPi), and magnesium ions (Mg2+), clearly defining the catalytic active sites. A combination of theory and experiments including carbocationic intermediates modeling, site-directed mutagenesis, and isotope labeling provided detailed insights into the structural basis for their catalytic mechanisms. Structure-based engineering of NfSS and PbSS resulted in the formation of 20 sesterterpenes including 13 new compounds and four pairs of epimers with different configurations at C18. These results expand the structural diversity of sesterterpenes and provide important insights for future synthetic biology research.

Including the Ensemble of Unstructured Conformations in the Analysis of Protein's Native State by High-Pressure NMR Spectroscopy.

The analysis of pressure induced changes in the chemical shift of proteins allows statements on structural fluctuations proteins exhibit at ambient pressure. The inherent issue of separating general pressure effects from structural related effects on the pressure dependence of chemical shifts has so far been addressed by considering the characteristics of random coil peptides on increasing pressure. In this work, chemically and pressure denatured states of the cold shock protein B from Bacillus subtilis (BsCspB) have been assigned in 2D 1H-15N HSQC NMR spectra and their dependence on increasing hydrostatic pressure has been evaluated. The pressure denatured polypeptide chain has been used to separate general from structural related effects on 1H and 15N chemical shifts of native BsCspB and the implications on the interpretation of pressure induced changes in the chemical shift regarding the structure of BsCspB are discussed. It has been found that the ensemble of unstructured conformations of BsCspB shows different responses to increasing pressure than random coil peptides do. Thus, the approach used for considering the general effects that arise when hydrostatic pressure increases changes the structural conclusions that are drawn from high pressure NMR spectroscopic experiments that rely on the analysis of chemical shifts.

The ABC toxin complex from Yersinia entomophaga can package three different cytotoxic components expressed from distinct genetic loci in an unfolded state: the structures of both shell and cargo.

Bacterial ABC toxin complexes (Tcs) comprise three core proteins: TcA, TcB and TcC. The TcA protein forms a pentameric assembly that attaches to the surface of target cells and penetrates the cell membrane. The TcB and TcC proteins assemble as a heterodimeric TcB-TcC subcomplex that makes a hollow shell. This TcB-TcC subcomplex self-cleaves and encapsulates within the shell a cytotoxic `cargo' encoded by the C-terminal region of the TcC protein. Here, we describe the structure of a previously uncharacterized TcC protein from Yersinia entomophaga, encoded by a gene at a distant genomic location from the genes encoding the rest of the toxin complex, in complex with the TcB protein. When encapsulated within the TcB-TcC shell, the C-terminal toxin adopts an unfolded and disordered state, with limited areas of local order stabilized by the chaperone-like inner surface of the shell. We also determined the structure of the toxin cargo alone and show that when not encapsulated within the shell, it adopts an ADP-ribosyltransferase fold most similar to the catalytic domain of the SpvB toxin from Salmonella typhimurium. Our structural analysis points to a likely mechanism whereby the toxin acts directly on actin, modifying it in a way that prevents normal polymerization.

Structural dissection of two redox proteins from the shipworm symbiont Teredinibacter turnerae.

The discovery of lytic polysaccharide monooxygenases (LPMOs), a family of copper-dependent enzymes that play a major role in polysaccharide degradation, has revealed the importance of oxidoreductases in the biological utilization of biomass. In fungi, a range of redox proteins have been implicated as working in harness with LPMOs to bring about polysaccharide oxidation. In bacteria, less is known about the interplay between redox proteins and LPMOs, or how the interaction between the two contributes to polysaccharide degradation. We therefore set out to characterize two previously unstudied proteins from the shipworm symbiont Teredinibacter turnerae that were initially identified by the presence of carbohydrate binding domains appended to uncharacterized domains with probable redox functions. Here, X-ray crystal structures of several domains from these proteins are presented together with initial efforts to characterize their functions. The analysis suggests that the target proteins are unlikely to function as LPMO electron donors, raising new questions as to the potential redox functions that these large extracellular multi-haem-containing c-type cytochromes may perform in these bacteria.

De novo transcriptome sequencing and annotation of the Antarctic polychaete Microspio moorei (Spionidae) with its characterization of the heat stress-related proteins (HSP, SOD & CAT).

We present a de novo transcriptome assembly for the non-model Antarctic polychaete worm Microspio moorei (Spionidae) collected during Antarctic field expedition in Fildes Bay, King George Island, Antarctic Peninsula, in 2017. Here, we report the first transcriptome reference array for Microspio spp. The gene sequences of the spionid worm were annotated from a wide range of functions (i.e., biological, and metabolic processes, catalytic processes, and catalytic activity). HSP70, HSP90 SOD and CAT families were compared to reported annelid transcriptomes and proteomes. The phylogenetic analysis using COI, 16S, and 18S markers effectively clusters the species within the family. However, it also casts uncertainty on the monophyletic nature of the Microspio genera, indicating the necessity for additional data and potentially requiring a reevaluation of its grouping. Within these protein families, 3D model software was used to create one representative of their protein structures. Structural predictions were compared with related reported annelids living at different temperatures and a human X-ray reference. We found structural differences (RMSE >1.8) between the human HSP proteins but no significant differences between the polychaete-predicted proteins (RMSE <1.2). These results encourage further research of heat stress-related proteins, the development of genetic markers for climate change-induced temperature stress, and the study of the underlying mechanisms of the heat response. Moreover, these results motivate the extension of these findings to congeneric species.

Engineering A-type Dye-Decolorizing Peroxidases by Modification of a Conserved Glutamate Residue.

Dye-decolorizing peroxidases (DyPs) are recently identified microbial enzymes that have been used in several Biotechnology applications from wastewater treatment to lignin valorization. However, their properties and mechanism of action still have many open questions. Their heme-containing active site is buried by three conserved flexible loops with a putative role in modulating substrate access and enzyme catalysis. Here, we investigated the role of a conserved glutamate residue in stabilizing interactions in loop 2 of A-type DyPs. First, we did site saturation mutagenesis of this residue, replacing it with all possible amino acids in bacterial DyPs from Bacillus subtilis (BsDyP) and from Kitasatospora aureofaciens (KaDyP1), the latter being characterized here for the first time. We screened the resulting libraries of variants for activity towards ABTS and identified variants with increased catalytic efficiency. The selected variants were purified and characterized for activity and stability. We furthermore used Molecular Dynamics simulations to rationalize the increased catalytic efficiency and found that the main reason is the electron channeling becoming easier from surface-exposed tryptophans. Based on our findings, we also propose that this glutamate could work as a pH switch in the wild-type enzyme, preventing intracellular damage.

Polymorphic Self-Assembly with Procedural Flexibility for Monodisperse Quaternary Protein Structures of DegQ Enzymes.

As large molecular tertiary structures, some proteins can act as small robots that find, bind, and chaperone target protein clients, showing the potential to serve as smart building blocks in self-assembly fields. Instead of using such intrinsic functions, most self-assembly methodologies for proteins aim for de novo-designed structures with accurate geometric assemblies, which can limit procedural flexibility. Here, a strategy enabling polymorphic clustering of quaternary proteins, exhibiting simplicity and flexibility of self-assembling paths for proteins in forming monodisperse quaternary cage particles is presented. It is proposed that the enzyme protomer DegQ, previously solved at low resolution, may potentially be usable as a threefold symmetric building block, which can form polyhedral cages incorporated by the chaperone action of DegQ in the presence of protein clients. To obtain highly monodisperse cage particles, soft, and hence, less resistive client proteins, which can program the inherent chaperone activity of DegQ to efficient formations of polymorphic cages, depending on the size of clients are utilized. By reconstructing the atomic resolution cryogenic electron microscopy DegQ structures using obtained 12- and 24-meric clusters, the polymorphic clustering of DegQ enzymes is validated in terms of soft and rigid domains, which will provide effective routes for protein self-assemblies with procedural flexibility.

N-Cyanopiperazines as Specific Covalent Inhibitors of the Deubiquitinating Enzyme UCHL1.

Cyanamides have emerged as privileged scaffolds in covalent inhibitors of deubiquitinating enzymes (DUBs). However, many compounds with a cyanopyrrolidine warhead show cross-reactivity toward small subsets of DUBs or toward the protein deglycase PARK7/DJ-1, hampering their use for the selective perturbation of a single DUB in living cells. Here, we disclose N'-alkyl,N-cyanopiperazines as structures for covalent enzyme inhibition with exceptional specificity for the DUB UCHL1 among 55 human deubiquitinases and with effective target engagement in cells. Notably, transitioning from 5-membered pyrrolidines to 6-membered heterocycles eliminated PARK7 binding and introduced context-dependent reversibility of the isothiourea linkage to the catalytic cysteine of UCHL1. Compound potency and specificity were analysed by a range of biochemical assays and with a crystal structure of a cyanopiperazine in covalent complex with UCHL1. The structure revealed a compound-induced conformational restriction of the cross-over loop, which underlies the observed inhibitory potencies. Through the rationalization of specificities of different cyanamides, we introduce a framework for the investigation of protein reactivity of bioactive nitriles of this compound class. Our results represent an encouraging case study for the refining of electrophilic compounds into chemical probes, emphasizing the potential to engineer specificity through subtle chemical modifications around the warhead.

Solving protein structures by combining structure prediction, molecular replacement and direct-methods-aided model completion.

Highly accurate protein structure prediction can generate accurate models of protein and protein-protein complexes in X-ray crystallography. However, the question of how to make more effective use of predicted models for completing structure analysis, and which strategies should be employed for the more challenging cases such as multi-helical structures, multimeric structures and extremely large structures, both in the model preparation and in the completion steps, remains open for discussion. In this paper, a new strategy is proposed based on the framework of direct methods and dual-space iteration, which can greatly simplify the pre-processing steps of predicted models both in normal and in challenging cases. Following this strategy, full-length models or the conservative structural domains could be used directly as the starting model, and the phase error and the model bias between the starting model and the real structure would be modified in the direct-methods-based dual-space iteration. Many challenging cases (from CASP14) have been tested for the general applicability of this constructive strategy, and almost complete models have been generated with reasonable statistics. The hybrid strategy therefore provides a meaningful scheme for X-ray structure determination using a predicted model as the starting point.

Free-energy landscapes of transmembrane homodimers by bias-exchange adaptively biased molecular dynamics.

Membrane proteins play essential roles in various biological functions within the cell. One of the most common functional regulations involves the dimerization of two single-pass transmembrane (TM) helices. Glycophorin A (GpA) and amyloid precursor protein (APP) form TM homodimers in the membrane, which have been investigated both experimentally and computationally. The homodimer structures are well characterized using only four collective variables (CVs) when each TM helix is stable. The CVs are the interhelical distance, the crossing angle, and the Crick angles for two TM helices. However, conformational sampling with multi-dimensional replica-exchange umbrella sampling (REUS) requires too many replicas to sample all the CVs for exploring the conformational landscapes. Here, we show that the bias-exchange adaptively biased molecular dynamics (BE-ABMD) with the four CVs effectively explores the free-energy landscapes of the TM helix dimers of GpA, wild-type APP and its mutants in the IMM1 implicit membrane. Compared to the original ABMD, the bias-exchange algorithm in BE-ABMD can provide a more rapidly converged conformational landscape. The BE-ABMD simulations could also reveal TM packing interfaces of the membrane proteins and the dependence of the free-energy landscapes on the membrane thickness. This approach is valuable for numerous other applications, including those involving explicit solvent and a lipid bilayer in all-atom force fields or Martini coarse-grained models, and enhances our understanding of protein-protein interactions in biological membranes.

Blanket antimicrobial resistance gene database with structural information, BOARDS, provides insights on historical landscape of resistance prevalence and effects of mutations in enzyme structure.

Antimicrobial resistance (AMR) in pathogenic bacteria poses a significant threat to public health, yet there is still a need for development in the tools to deeply understand AMR genes based on genetic or structural information. In this study, we present an interactive web database named Blanket Overarching Antimicrobial-Resistance gene Database with Structural information (BOARDS, sbml.unist.ac.kr), a database that comprehensively includes 3,943 reported AMR gene information for 1,997 extended spectrum beta-lactamase (ESBL) and 1,946 other genes as well as a total of 27,395 predicted protein structures. These structures, which include both wild-type AMR genes and their mutants, were derived from 80,094 publicly available whole-genome sequences. In addition, we developed the rapid analysis and detection tool of antimicrobial-resistance (RADAR), a one-stop analysis pipeline to detect AMR genes across whole-genome sequencing (WGSs). By integrating BOARDS and RADAR, the AMR prevalence landscape for eight multi-drug resistant pathogens was reconstructed, leading to unexpected findings such as the pre-existence of the MCR genes before their official reports. Enzymatic structure prediction-based analysis revealed that the occurrence of mutations found in some ESBL genes was found to be closely related to the binding affinities with their antibiotic substrates. Overall, BOARDS can play a significant role in performing in-depth analysis on AMR.IMPORTANCEWhile the increasing antibiotic resistance (AMR) in pathogen has been a burden on public health, effective tools for deep understanding of AMR based on genetic or structural information remain limited. In this study, a blanket overarching antimicrobial-resistance gene database with structure information (BOARDS)-a web-based database that comprehensively collected AMR gene data with predictive protein structural information was constructed. Additionally, we report the development of a RADAR pipeline that can analyze whole-genome sequences as well. BOARDS, which includes sequence and structural information, has shown the historical landscape and prevalence of the AMR genes and can provide insight into single-nucleotide polymorphism effects on antibiotic degrading enzymes within protein structures.

Machine Learning Models to Interrogate Proteomewide Covalent Ligandabilities Directed at Cysteines.

Machine learning (ML) identification of covalently ligandable sites may accelerate targeted covalent inhibitor design and help expand the druggable proteome space. Here we report the rigorous development and validation of the tree-based models and convolutional neural networks (CNNs) trained on a newly curated database (LigCys3D) of over 1,000 liganded cysteines in nearly 800 proteins represented by over 10,000 three-dimensional structures in the protein data bank. The unseen tests yielded 94% and 93% AUCs (area under the receiver operating characteristic curve) for the tree models and CNNs, respectively. Based on the AlphaFold2 predicted structures, the ML models recapitulated the newly liganded cysteines in the PDB with over 90% recall values. To assist the community of covalent drug discoveries, we report the predicted ligandable cysteines in 392 human kinases and their locations in the sequence-aligned kinase structure including the PH and SH2 domains. Furthermore, we disseminate a searchable online database LigCys3D (https://ligcys.computchem.org/) and a web prediction server DeepCys (https://deepcys.computchem.org/), both of which will be continuously updated and improved by including newly published experimental data. The present work represents a first step towards the ML-led integration of big genome data and structure models to annotate the human proteome space for the next-generation covalent drug discoveries.

A Mechanistic Understanding of the Distinct Regio- and Chemoselectivity of Multifunctional P450s by Structural Comparison of IkaD and CftA Complexed with Common Substrates.

Regio- and chemoselective C-H activation at multi-positions of a single molecule is fascinating but chemically challenging. The homologous cytochrome P450 enzymes IkaD and CftA catalyze multiple C-H oxidations on the same polycyclic tetramate macrolactam (PoTeM) ikarugamycin, with distinct regio- and chemoselectivity. Herein we provide mechanistic understanding of their functional differences by solving crystal structures of IkaD and CftA in complex with ikarugamycin and unnatural substrates. Distinct conformations of the F/G region in IkaD and CftA are found to differentiate the orientation of PoTeM substrates, by causing different binding patterns with polar moieties to determine site selection, oxidation order, and chemoselectivity. Fine-tuning the polar subpocket altered the regioselectivity of IkaD, indicating that substrate re-orientation by mutating residues distal to the oxidation site could serve as an important method in future engineering of P450 enzymes.

Challenges in bridging the gap between protein structure prediction and functional interpretation.

The rapid evolution of protein structure prediction tools has significantly broadened access to protein structural data. Although predicted structure models have the potential to accelerate and impact fundamental and translational research significantly, it is essential to note that they are not validated and cannot be considered the ground truth. Thus, challenges persist, particularly in capturing protein dynamics, predicting multi-chain structures, interpreting protein function, and assessing model quality. Interdisciplinary collaborations are crucial to overcoming these obstacles. Databases like the AlphaFold Protein Structure Database, the ESM Metagenomic Atlas, and initiatives like the 3D-Beacons Network provide FAIR access to these data, enabling their interpretation and application across a broader scientific community. Whilst substantial advancements have been made in protein structure prediction, further progress is required to address the remaining challenges. Developing training materials, nurturing collaborations, and ensuring open data sharing will be paramount in this pursuit. The continued evolution of these tools and methodologies will deepen our understanding of protein function and accelerate disease pathogenesis and drug development discoveries.