The PCDDB (Protein Circular Dichroism Data Bank): A Bioinformatics Resource for Protein Characterisations and Methods Development

The Protein Circular Dichroism Data Bank (PCDDB) [https://pcddb.cryst.bbk.ac.uk] is an established resource for the biological, biophysical, chemical, bioinformatics, and molecular biology communities. It is a freely-accessible repository of validated protein circular dichroism (CD) spectra and associated sample and metadata, with entries having links to other bioinformatics resources including, amongst others, structure (PDB), AlphaFold, and sequence (UniProt) databases, as well as to published papers which produced the data and cite the database entries. It includes primary (unprocessed) and final (processed) spectral data, which are available in both text and pictorial formats, as well as detailed sample and validation information produced for each of the entries. Recently the metadata content associated with each of the entries, as well as the number and structural breadth of the protein components included, have been expanded. The PCDDB includes data on both wild-type and mutant proteins, and because CD studies primarily examine proteins in solution, it also contains examples of the effects of different environments on their structures, plus thermal unfolding/folding series. Methods for both sequence and spectral comparisons are included.The data included in the PCDDB complement results from crystal, cryo-electron microscopy, NMR spectroscopy, bioinformatics characterisations and classifications, and other structural information available for the proteins via links to other databases. The entries in the PCDDB have been used for the development of new analytical methodologies, for interpreting spectral and other biophysical data, and for providing insight into structures and functions of individual soluble and membrane proteins and protein complexes.     

The PHY Domain Dimer Interface of Bacteriophytochromes Mediates Cross-talk between Photosensory Modules and Output Domains

Protein dynamics play a major role for the catalytic function of enzymes, the interaction of protein complexes or signal integration in regulatory proteins. In the context of multi-domain proteins involved in light-regulation of enzymatic effectors, the central role of conformational dynamics is well established. Light activation of sensory modules is followed by long-range signal transduction to different effectors; rather than domino-style structural rearrangements, a complex interplay of functional elements is required to maintain functionality. One family of such sensor-effector systems are red-light-regulated phytochromes that control diguanylate cyclases involved in cyclic-dimeric-GMP formation. Based on structural and functional studies of one prototypic family member, the central role of the coiled-coil sensor-effector linker was established. Interestingly, subfamilies with different linker lengths feature strongly varying biochemical characteristics. The dynamic interplay of the domains involved, however, is presently not understood. Here we show that the PHY domain dimer interface plays an essential role in signal integration, and that a functional coupling with the coiled-coil linker element is crucial. Chimaeras of two biochemically different family members highlight the phytochrome-spanning helical spine as an essential structural element involved in light-dependent upregulation of enzymatic turnover. However, isolated structural elements can frequently not be assigned to individual characteristics, which further emphasises the importance of global conformational dynamics. Our results provide insights into the intricate processes at play during light signal integration and transduction in these photosensory systems and thus provide additional guidelines for a more directed design of novel sensor-effector combinations with potential applications as optogenetic tools.     

New Digital Health Technologies for Insulin Initiation and Optimization for People With Type 2 Diabetes

ObjectiveThe health and economic burden of type 2 diabetes is of global significance. Many people with type 2 diabetes eventually need insulin to help reduce their risk of serious associated complications. However, barriers to the initiation and/or optimization of insulin expose people with diabetes to sustained hyperglycemia. In this review, we investigated how new and future technologies may provide opportunities to help overcome these barriers to the initiation and/or optimization of insulin.MethodsA focused literature search of PubMed and key scientific congresses was conducted. Software tools and devices developed to support the initiation and/or optimization of insulin were identified by manually filtering >300 publications and conference abstracts.ResultsMost software tools have been developed for smartphone platforms. At present, published data suggest that the use of these technologies is associated with equivalent or improved glycemic outcomes compared with standard care, with additional benefits such as reduced time burden and improved knowledge of diabetes among health care providers. However, there remains paucity of good-quality evidence. Most new devices to support insulin therapy help track the dose and timing of insulin.ConclusionNew digital health tools may help to reduce barriers to optimal insulin therapy. An integrated solution that connects glucose monitoring, dose recording, and titration advice as well as records comorbidities and lifestyle factors has the potential to reduce the complexity and burden of treatment and may improve adherence to titration and treatment, resulting in better outcomes for people with diabetes.     

Recent Advances in the Structural Biology of Mg2+ Channels and Transporters

Magnesium ions (Mg²⁺) are the most abundant divalent cations in living organisms and are essential for various physiological processes, including ATP utilization and the catalytic activity of numerous enzymes. Therefore, the homeostatic mechanisms associated with cellular Mg²⁺ are crucial for both eukaryotic and prokaryotic organisms and are thus strictly controlled by Mg²⁺ channels and transporters. Technological advances in structural biology, such as the expression screening of membrane proteins, in meso phase crystallization, and recent cryo-EM techniques, have enabled the structure determination of numerous Mg²⁺ channels and transporters. In this review article, we provide an overview of the families of Mg²⁺ channels and transporters (MgtE/SLC41, TRPM6/7, CorA/Mrs2, CorC/CNNM), and discuss the structural biology prospects based on the known structures of MgtE, TRPM7, CorA and CorC.     

Multiple Layers of Complexity in O-Glycosylation Illustrated With the Urinary Glycoproteome

While N-glycopeptides are relatively easy to characterize, O-glycosylation analysis is more complex. In this article, we illustrate the multiple layers of O-glycopeptide characterization that make this task so challenging. We believe our carefully curated dataset represents perhaps the largest intact human glycopeptide mixture derived from individuals, not from cell lines. The samples were collected from healthy individuals, patients with superficial or advanced bladder cancer (three of each group), and a single bladder inflammation patient. The data were scrutinized manually and interpreted using three different search engines: Byonic, Protein Prospector, and O-Pair, and the tool MS-Filter. Despite all the recent advances, reliable automatic O-glycopeptide assignment has not been solved yet. Our data reveal such diversity of site-specific O-glycosylation that has not been presented before. In addition to the potential biological implications, this dataset should be a valuable resource for software developers in the same way as some of our previously released data has been used in the development of O-Pair and O-Glycoproteome Analyzer. Based on the manual evaluation of the performance of the existing tools with our data, we lined up a series of recommendations that if implemented could significantly improve the reliability of glycopeptide assignments.     

PubChem Protein,Gene, Pathway,and Taxonomy Data Collections: Bridging Biology and Chemistry through Target-Centric Views of PubChem Data

PubChem (https://pubchem.ncbi.nlm.nih.gov) is a public chemical database at the U.S. National Institutes of Health. Visited by millions of users every month, it plays a role as a key chemical information resource for biomedical research communities. Data in PubChem is from hundreds of contributors and organized into multiple collections by record type. Among these are the Protein, Gene, Pathway, and Taxonomy data collections. Records in these collections contain information on chemicals related to a given biological target (i.e., protein, gene, pathway, or taxon), helping users to analyze and interpret the biological activity data of molecules. In addition, annotations about the biological targets are collected from authoritative or curated data sources and integrated into the four collections. The content can be programmatically accessed through PubChem’s web service interfaces (including PUG View). A machine-readable representation of this content is also provided within PubChemRDF.     

Building Structural Models of a Whole Mycoplasma Cell

Building structural models of entire cells has been a long-standing cross-discipline challenge for the research community, as it requires an unprecedented level of integration between multiple sources of biological data and enhanced methods for computational modeling and visualization. Here, we present the first 3D structural models of an entire Mycoplasma genitalium (MG) cell, built using the CellPACK suite of computational modeling tools. Our model recapitulates the data described in recent whole-cell system biology simulations and provides a structural representation for all MG proteins, DNA and RNA molecules, obtained by combining experimental and homology-modeled structures and lattice-based models of the genome. We establish a framework for gathering, curating and evaluating these structures, exposing current weaknesses of modeling methods and the boundaries of MG structural knowledge, and visualization methods to explore functional characteristics of the genome and proteome. We compare two approaches for data gathering, a manually-curated workflow and an automated workflow that uses homologous structures, both of which are appropriate for the analysis of mesoscale properties such as crowding and volume occupancy. Analysis of model quality provides estimates of the regularization that will be required when these models are used as starting points for atomic molecular dynamics simulations.     

Missense Variants Reveal Functional Insights Into the Human ARID Family of Gene Regulators

Missense variants are alterations to protein coding sequences that result in amino acid substitutions. They can be deleterious if the amino acid is required for maintaining structure or/and function, but are likely to be tolerated at other sites. Consequently, missense variation within a healthy population can mirror the effects of negative selection on protein structure and function, such that functional sites on proteins are often depleted of missense variants. Advances in high-throughput sequencing have dramatically increased the sample size of available human variation data, allowing for population-wide analysis of selective pressures. In this study, we developed a convenient set of tools, called 1D-to-3D, for visualizing the positions of missense variants on protein sequences and structures. We used these tools to characterize human homologues of the ARID family of gene regulators. ARID family members are implicated in multiple cancer types, developmental disorders, and immunological diseases but current understanding of their mechanistic roles is incomplete. Combined with phylogenetic and structural analyses, our approach allowed us to characterise sites important for protein-protein interactions, histone modification recognition, and DNA binding by the ARID proteins. We find that comparing missense depletion patterns among paralogs can reveal sub-functionalization at the level of domains. We propose that visualizing missense variants and their depletion on structures can serve as a valuable tool for complementing evolutionary and experimental findings.     

Coupling chemical biology and vibrational spectroscopy for studies of amyloids in vitro and in cells

Amyloid diseases are characterized by the aggregation of various proteins to form insoluble β-sheet–rich fibrils leading to cell death. Vibrational spectroscopies have emerged as attractive methods to study this process because of the rich structural information that can be extracted without large, perturbative probes. Importantly, specific vibrations such as the amide-I band directly report on secondary structure changes, which are key features of amyloid formation. Beyond intrinsic vibrations, the incorporation of unnatural vibrational probes can improve sensitivity for secondary structure determination (e.g. isotopic labeling), can provide residue-specific information of the surrounding polarity (e.g. unnatural amino acid), and are translatable into cellular studies. Here, we review the latest studies that have leveraged tools from chemical biology for the incorporation of novel vibrational probes into amyloidogenic proteins for both mechanistic and cellular studies.     

Reanalysis of ProteomicsDB Using an Accurate,Sensitive, and Scalable False Discovery Rate Estimation Approach for Protein Groups

Estimating false discovery rates (FDRs) of protein identification continues to be an important topic in mass spectrometry–based proteomics, particularly when analyzing very large datasets. One performant method for this purpose is the Picked Protein FDR approach which is based on a target-decoy competition strategy on the protein level that ensures that FDRs scale to large datasets. Here, we present an extension to this method that can also deal with protein groups, that is, proteins that share common peptides such as protein isoforms of the same gene. To obtain well-calibrated FDR estimates that preserve protein identification sensitivity, we introduce two novel ideas. First, the picked group target-decoy and second, the rescued subset grouping strategies. Using entrapment searches and simulated data for validation, we demonstrate that the new Picked Protein Group FDR method produces accurate protein group-level FDR estimates regardless of the size of the data set. The validation analysis also uncovered that applying the commonly used Occam’s razor principle leads to anticonservative FDR estimates for large datasets. This is not the case for the Picked Protein Group FDR method. Reanalysis of deep proteomes of 29 human tissues showed that the new method identified up to 4% more protein groups than MaxQuant. Applying the method to the reanalysis of the entire human section of ProteomicsDB led to the identification of 18,000 protein groups at 1% protein group-level FDR. The analysis also showed that about 1250 genes were represented by ≥2 identified protein groups. To make the method accessible to the proteomics community, we provide a software tool including a graphical user interface that enables merging results from multiple MaxQuant searches into a single list of identified and quantified protein groups.     

Comparative Study of Initial Post-Therapeutic 131I Single-Photon Emission Computed Tomography/Computed Tomography and Reoperation for the Detection of Residual Lymph Node Metastasis in Patients With Papillary Thyroid Cancer

ObjectiveTo assess the diagnostic performance of initial post-therapeutic ¹³¹I single-photon emission computed tomography/computed tomography (SPECT/CT) compared with that of reoperation in detecting residual lymph node metastasis (LNM).MethodsPatients with iodine-avid LNM detected on the initial post-therapeutic ¹³¹I SPECT/CT and who underwent reoperative dissection within 6 months were included. LNMs (numbers and locations) detected via both methods were compared. The American Thyroid Association dynamic risk stratification was performed for patients receiving second radioactive iodine therapy after reoperation.ResultsFifty-three patients with 95 iodine-avid LNMs detected by ¹³¹I SPECT/CT were enrolled. Fifty-one (96.2%) patients had 212 LNMs confirmed by reoperation (P = .004). The sensitivity and specificity of ¹³¹I SPECT/CT in detecting LNM were 44.8% (95/212) and 91.6% (87/95), respectively. The location frequency of residual LNMs found by ¹³¹I SPECT/CT was similar to that of reoperation (P = .057). Thirty-two patients received a second radioactive iodine treatment, and 6 (18.8%) patients still had residual iodine-avid LNM on SPECT/CT. Therapeutic response was evaluated by American Thyroid Association dynamic risk stratification in 16 patients. The number of patients with structural incomplete response, biochemical incomplete response, indeterminate response, and excellent response was 4 (23.5%), 4 (23.5%), 5 (29.4%), and 3 (17.6%), respectively.Conclusion¹³¹I SPECT/CT has high specificity but relatively low sensitivity in detecting all residual LNMs. Approximately 80% of patients were rendered structurally disease free after reoperation.     

In silico reconstitution of DNA replication. Lessons from single-molecule imaging and cryo-tomography applied to single-particle cryo-EM

DNA replication has been reconstituted in vitro with yeast proteins, and the minimal system requires the coordinated assembly of 16 distinct replication factors, consisting of 42 polypeptides. To understand the molecular interplay between these factors at the single residue level, new structural biology tools are being developed. Inspired by advances in single-molecule fluorescence imaging and cryo-tomography, novel single-particle cryo-EM experiments have been used to characterise the structural mechanism for the loading of the replicative helicase. Here, we discuss how in silico reconstitution of single-particle cryo-EM data can help describe dynamic systems that are difficult to approach with conventional three-dimensional classification tools.     

Reprogramming Substrate and Catalytic Promiscuity of Tryptophan Prenyltransferases

Prenylation is a process widely prevalent in primary and secondary metabolism, contributing to functionality and chemical diversity in natural systems. Due to their high regio- and chemoselectivities, prenyltransferases are also valuable tools for creation of new compounds by chemoenzymatic synthesis and synthetic biology. Over the last ten years, biochemical and structural investigations shed light on the mechanism and key residues that control the catalytic process, but to date crucial information on how certain prenyltransferases control regioselectivity and chemoselectivity is still lacking. Here, we advance a general understanding of the enzyme family by contributing the first structure of a tryptophan C5-prenyltransferase 5-DMATS. Additinally, the structure of a bacterial tryptophan C6-prenyltransferase 6-DMATS was solved. Analysis and comparison of both substrate-bound complexes led to the identification of key residues for catalysis. Next, site-directed mutagenesis was successfully implemented to not only modify the prenyl donor specificity but also to redirect the prenylation, thereby switching the regioselectivity of 6-DMATS to that of 5-DMATS. The general strategy of structure-guided protein engineering should be applicable to other related prenyltransferases, thus enabling the production of novel prenylated compounds.     

Arena: Rapid and Accurate Reconstruction of Full Atomic RNA Structures From Coarse-grained Models

RNA tertiary structures from experiments or computational predictions often contain missing atoms, which prevent analyses requiring full atomic structures. Current programs for RNA reconstruction can be slow, inaccurate, and/or require specific atoms to be present in the input. We present Arena (Atomic Reconstruction of RNA), which reconstructs a full atomic RNA structure from residues that can have as few as one atom. Arena first fills in missing atoms and then iteratively refines their placement to reduce nonideal geometries. We benchmarked Arena on a dataset of 361 RNA structures, where Arena achieves high accuracy and speed compared to other structure reconstruction programs. For example, Arena was used to reconstruct full atomic structures from a single phosphorus atom per nucleotide to, on average, within 3.63 Å RMSD of the experimental structure, while virtually removing all clashes and running in <3 s, which is 353× and 46× faster than state-of-the-art programs PDBFixer and C2A, respectively. The Arena source code is available at https://github.com/pylelab/Arena and the webserver at https://zhanggroup.org/Arena/.     

PARP–nucleic acid interactions: Allosteric signaling,PARP inhibitor types,DNA bridges,and viral RNA surveillance

PARP enzymes create ADP-ribose modifications to regulate multiple facets of human biology, and some prominent PARP family members are best known for the nucleic acid interactions that regulate their activities and functions. Recent structural studies have highlighted PARP interactions with nucleic acids, in particular for PARP enzymes that detect and respond to DNA strand break damage. These studies build on our understanding of how DNA break detection is linked to the catalysis of ADP-ribose modifications, provide insights into distinct modes of DNA interaction, and shed light on the mechanisms of PARP inhibitor action. PARP enzymes have several connections to RNA biology, including the detection of the genomes of RNA viruses, and recent structural work has highlighted how PARP13/ZAP specifically targets viral genomes enriched in CG dinucleotides.     

Principles of Alternating Access in Multidrug and Toxin Extrusion (MATE) Transporters

The multidrug and toxin extrusion (MATE) transporters catalyze active efflux of a broad range of chemically- and structurally-diverse compounds including antimicrobials and chemotherapeutics, thus contributing to multidrug resistance in pathogenic bacteria and cancers. Multiple methodological approaches have been taken to investigate the structural basis of energy transduction and substrate translocation in MATE transporters. Crystal structures representing members from all three MATE subfamilies have been interpreted within the context of an alternating access mechanism that postulates occupation of distinct structural intermediates in a conformational cycle powered by electrochemical ion gradients. Here we review the structural biology of MATE transporters, integrating the crystallographic models with biophysical and computational studies to define the molecular determinants that shape the transport energy landscape. This holistic analysis highlights both shared and disparate structural and functional features within the MATE family, which underpin an emerging theme of mechanistic diversity within the framework of a conserved structural scaffold.     

Recent progress in dissecting ubiquitin signals with chemical biology tools

Protein ubiquitination regulates almost all eukaryotic cellular processes, and is of very high complexity due to the diversity of ubiquitin (Ub) modifications including mono-, multiply mono-, homotypic poly-, and even heterotypic poly-ubiquitination. To accurately elucidate the role of each specific Ub signal in different cells with spatiotemporal resolutions, a variety of chemical biology tools have been developed. In this review, we summarize some recently developed chemical biology tools for ubiquitination studies and their applications in molecular and cellular biology.     

Contact toxicity and transcriptomic analysis of terpinen‐4‐ol exposure in Tribolium castaneum

The terpene, terpinen-4-ol (T4ol), exhibits contact toxicity in Tribolium castaneum. However, the molecular mechanisms underlying this toxicity have not been elucidated. This study examined changes in the expression of four classic enzymes after exposure of T. castaneum to T4ol. Acetylcholinesterase and glutathione S-transferase activities were markedly inhibited after exposure to T4ol, while that of the detoxifying enzyme cytochrome oxidase P450 increased markedly. Carboxylesterase activity did not show significant changes. Furthermore, RNA sequencing revealed 260 differentially expressed genes (DEG) between the T4ol-treated and control samples, and qRT-PCR was used to validate the RNA-Seq data. The Gene Ontology analysis classified the DEGs into 36 functional groups, including the immune system processes, response to stimulus, and developmental processes. T4ol altered the response to stimulus and the immune system process of beetles by inducing the expression of the genes Stabilin-1, Attacin 1, and Defensin 1. Furthermore, the DEGs receptor tyrosine kinase Torso-like protein (RTKTsl), Frizzled 4 (Fz4), Protein Wnt-5b, Ecdysone-induced protein 78C (E78), Zinc finger protein GLIS1 (ZFPGLIS1) were classified as participating in beetle development, and Fz4 and Protein Wnt-5b also mapped to the Wnt signaling pathway. This indicated that pathways associated with development are inhibited after exposure to T4ol. T4ol also induced CYP9Z6/GSTs7 overexpression, and RNAi targeting these genes significantly increased larvae mortality on T4ol exposure, supporting the participation of CYP9Z6/GSTs7 in the response to T4ol in T. castaneum. The results of this study will facilitate understanding of the toxic mechanisms of T4ol and provide a basis for controlling the pests of stored products.     

Parathyroid Cystic Adenoma: A Systematic Review and Meta-Analysis

ObjectiveTo review diagnostic imaging modalities for parathyroid cystic adenomas (PCA). Since PCAs are a rare (0.5%-1%) subclass of parathyroid adenomas, and due to their cystic component, imaging modalities known to be efficient for diagnosing solid adenomas might fail in localizing them.MethodsWe conducted a systematic review using the PubMed and Cochrane databases for English articles on PCAs published between 1995 and 2020. A meta-analysis of the retrieved data was performed.ResultsOverall, 39 studies, reporting on a total of 160 patients, were included in the analysis. Two thirds (68%) of the patients were female, with a mean age of 53.9 years. A single cystic adenoma was detected in 98.1% of cases. The mean blood calcium corrected for albumin level was 12.6 ± 2.7 mg/dL, and the mean parathyroid hormone level was 565.5 ± 523.8 pg/mL. The mean PCA sizes as measured by ultrasound (US), computed tomography (CT), and ex vivo measurement were 4.8 ± 3.6, 5.2 ± 3.2, and 3.5 cm, respectively. The median weight was 8.1 g. PCA was detected in 86% of US examinations; 100% of US-guided fine needle aspiration, 4-dimensional computed tomography (4D-CT), or magnetic resonance imaging examinations; and 61% of 99m-technetium sestamibi scan with single-photon emission computed tomography ((99m)Tc-SPECT). (99m)Tc-SPECT showed a significantly lower diagnostic rate than US (odds ratio, 3.589), US-guided fine needle aspiration, CT combined with 4D-CT, and the combination of US, CT, 4D-CT, and magnetic resonance imaging (P < .001).ConclusionAlthough US and 4D-CT showed a significantly high rate in diagnosing PCA, (99m)Tc-SPECT showed a lower PCA diagnostic rate. These findings suggest that larger cystic lesions suspected as PCAs should be further evaluated using 4D-CT rather than (99m)Tc-SPECT.