Biothiols such as cysteine (Cys), homocysteine (Hcy), and glutathione (GSH) play crucial roles in maintaining redox homeostasis in biological systems. This Minireview summarizes the most significant ...current challenges in the field of thiol‐reactive probes for biomedical research and diagnostics, emphasizing the needs and opportunities that have been under‐investigated by chemists in the selective probe and sensor field. Progress on multiple binding site probes to distinguish Cys, Hcy, and GSH is highlighted as a creative new direction in the field that can enable simultaneous, accurate ratiometric monitoring. New probe design strategies and researcher priorities can better help address current challenges, including the monitoring of disease states such as autism and chronic diseases involving oxidative stress that are characterized by divergent levels of GSH, Cys, and Hcy.
Probing biothiols: Cysteine (Cys), homocysteine (Hcy), and glutathione (GSH) play crucial roles in human health. There are very few molecular probes and abiotic sensors that can simultaneously discriminate among biothiols. Recent progress on probes featuring multiple binding sites to distinguish Cys, Hcy, and GSH is summarized, and a variety of unmet critical needs and opportunities for chemists in the thiol probe field are discussed.
• Powdery mildew, a fungal disease caused by Blumeria graminis f. sp. tritici (Bgt), has a serious impact on wheat production. Loss of resistance in cultivars prompts a continuing search for new ...sources of resistance.
• Wild emmer wheat (Triticum turgidum ssp. dicoccoides, WEW), the progenitor of both modern tetraploid and hexaploid wheats, harbors many powdery mildew resistance genes. We report here the positional cloning and functional characterization of Pm41, a powdery mildew resistance gene derived from WEW, which encodes a coiled-coil, nucleotide-binding site and leucine-rich repeat protein (CNL). Mutagenesis and stable genetic transformation confirmed the function of Pm41 against Bgt infection in wheat.
• We demonstrated that Pm41 was present at a very low frequency (1.81%) only in southern WEW populations. It was absent in other WEW populations, domesticated emmer, durum, and common wheat, suggesting that the ancestral Pm41 was restricted to its place of origin and was not incorporated into domesticated wheat.
• Our findings emphasize the importance of conservation and exploitation of the primary WEW gene pool, as a valuable resource for discovery of resistance genes for improvement of modern wheat cultivars.
Summary
Although at first glance the diversity of the immunoglobulin repertoire appears random, there are a number of mechanisms that act to constrain diversity. For example, key mechanisms ...controlling the diversity of the third complementarity determining region of the immunoglobulin heavy chain (CDR‐H3) include natural selection of germline diversity (DH) gene segment sequence and somatic selection upon passage through successive B‐cell developmental checkpoints. To test the role of DH gene segment sequence, we generated a panel of mice limited to the use of a single germline or frameshifted DH gene segment. Specific individual amino acids within core DH gene segment sequence heavily influenced the absolute numbers of developing and mature B‐cell subsets, antibody production, epitope recognition, protection against pathogen challenge, and susceptibility to the production of autoreactive antibodies. At the tip of the antigen‐binding loop (PDB position 101) in CDR‐H3, both natural (germline) and somatic selection favored tyrosine while disfavoring the presence of hydrophobic amino acids. Enrichment for arginine in CDR‐H3 appeared to broaden recognition of epitopes of varying hydrophobicity, but led to diminished binding intensity and an increased likelihood of generating potentially pathogenic dsDNA‐binding autoreactive antibodies. The phenotype of altering the sequence of the DH was recessive for T‐independent antibody production, but dominant for T‐cell‐dependent responses. Our work suggests that the antibody repertoire is structured, with the sequence of individual DH selected by evolution to preferentially generate an apparently preferred category of antigen‐binding sites. The result of this structured approach appears to be a repertoire that has been adapted, or optimized, to produce protective antibodies for a wide range of pathogen epitopes while reducing the likelihood of generating autoreactive specificities.
Influenza A viruses contain sialic acid (SIA) receptor‐binding hemagglutinin (HA) and receptor‐destroying neuraminidase (NA). The balance between HA and NA is adjusted to the SIA receptor repertoire ...of the host species. Besides a conserved catalytic site, NA carries a 2nd SIA‐binding site (2SBS). The 2SBS enhances the activity of the catalytic site and affects the HA‐NA balance. Conservation or loss of the 2SBS is associated with (changes in) host tropism.
Influenza A viruses (IAVs) are a major cause of human respiratory tract infections and cause significant disease and mortality. Human IAVs originate from animal viruses that breached the host species barrier. IAV particles contain sialoglycan receptor‐binding hemagglutinin (HA) and receptor‐destroying neuraminidase (NA) in their envelope. When IAV crosses the species barrier, the functional balance between HA and NA needs to be adjusted to the sialoglycan repertoire of the novel host species. Relatively little is known about the role of NA in host adaptation in contrast to the extensively studied HA. NA prevents virion aggregation and facilitates release of (newly assembled) virions from cell surfaces and from decoy receptors abundantly present in mucus and cell glycocalyx. In addition to a highly conserved catalytic site, NA carries a second sialic acid‐binding site (2SBS). The 2SBS preferentially binds α2,3‐linked sialic acids and enhances activity of the neighboring catalytic site by bringing/keeping multivalent substrates in close contact with this site. In this way, the 2SBS contributes to the HA‐NA balance of virus particles and affects virus replication. The 2SBS is highly conserved in all NA subtypes of avian IAVs, with some notable exceptions associated with changes in the receptor‐binding specificity of HA and host tropism. Conservation of the 2SBS is invariably lost in human (pandemic) viruses and in several other viruses adapted to mammalian host species. Preservation or loss of the 2SBS is likely to be an important factor of the viral host range.
The γ-aminobutyric acid (GABA) type B receptor (GABAB-R) belongs to class C of the G-protein coupled receptors (GPCRs). Together with the GABAA receptor, the receptor mediates the neurotransmission ...of GABA, the main inhibitory neurotransmitter in the central nervous system (CNS). In recent decades, the receptor has been extensively studied with the intention being to understand pathophysiological roles, structural mechanisms and develop drugs. The dysfunction of the receptor is linked to a broad variety of disorders, including anxiety, depression, alcohol addiction, memory and cancer. Despite extensive efforts, few compounds are known to target the receptor, and only the agonist baclofen is approved for clinical use. The receptor is a mandatory heterodimer of the GABAB1 and GABAB2 subunits, and each subunit is composed of an extracellular Venus Flytrap domain (VFT) and a transmembrane domain of seven α-helices (7TM domain). In this review, we briefly present the existing knowledge about the receptor structure, activation and compounds targeting the receptor, emphasizing the role of the receptor in previous and future drug design and discovery efforts.
Calmodulin (CaM) is a ubiquitous, highly conserved, eukaryotic protein that binds to and regulates a number of diverse target proteins involved in different functions such as metabolism, muscle ...contraction, apoptosis, memory, inflammation and the immune response. In this minireview, we analyze the large number of CaM‐complex structures deposited in the Protein Data Bank (i.e. crystal and nuclear magnetic resonance structures) to gain insight into the structural diversity of CaM‐binding sites and mechanisms, such as those for CaM‐activated protein kinases and phosphatases, voltage‐gated Ca²⁺‐channels and the plasma membrane Ca²⁺‐ATPase.
While predicting a ligand that binds to a protein is feasible with current methods, the opposite, i.e., the prediction of a receptor for a ligand remains challenging. We present an approach for ...predicting receptors of a given ligand that uses de novo design and structural bioinformatics. We have developed the algorithm CRD, comprising multiple modules combining fragment-based sub-site finding, a machine learning function to estimate the size of the site, a genetic algorithm that encodes knowledge on protein structures and a physics-based fitness scoring scheme. CRD includes a pseudo-receptor design component followed by a mapping component to identify proteins that might contain these sites. CRD recovers the sites and receptors of several natural ligands. It designs similar sites for similar ligands, yet to some extent can distinguish between closely related ligands. CRD correctly predicts receptor classes for several drugs and might become a valuable tool for drug discovery.
Display omitted
•CRD is an algorithm that allows the prediction of a receptor for a given small molecule•CRD uses a fragment-based design approach to design putative binding sites for a ligand•CRD accurately recovers the sites and receptors for several natural ligands and drugs•CRD helps to bridge the gap between structure-guided and ligand-guided drug design
Sankar et al. present an algorithm, CRD, for predicting receptors for small molecule natural ligands and drugs, making it a valuable tool in fundamental biology research as well as for drug discovery.
MicroRNA targets are often recognized through pairing between the miRNA seed region and complementary sites within target mRNAs, but not all of these canonical sites are equally effective, and both ...computational and in vivo UV-crosslinking approaches suggest that many mRNAs are targeted through non-canonical interactions. Here, we show that recently reported non-canonical sites do not mediate repression despite binding the miRNA, which indicates that the vast majority of functional sites are canonical. Accordingly, we developed an improved quantitative model of canonical targeting, using a compendium of experimental datasets that we pre-processed to minimize confounding biases. This model, which considers site type and another 14 features to predict the most effectively targeted mRNAs, performed significantly better than existing models and was as informative as the best high-throughput in vivo crosslinking approaches. It drives the latest version of TargetScan (v7.0; targetscan.org), thereby providing a valuable resource for placing miRNAs into gene-regulatory networks.
Background
Ligand binding site prediction from protein structure has many applications related to elucidation of protein function and structure based drug discovery. It often represents only one step ...of many in complex computational drug design efforts. Although many methods have been published to date, only few of them are suitable for use in automated pipelines or for processing large datasets. These use cases require stability and speed, which disqualifies many of the recently introduced tools that are either template based or available only as web servers.
Results
We present P2Rank, a stand-alone template-free tool for prediction of ligand binding sites based on machine learning. It is based on prediction of ligandability of local chemical neighbourhoods that are centered on points placed on the solvent accessible surface of a protein. We show that P2Rank outperforms several existing tools, which include two widely used stand-alone tools (Fpocket, SiteHound), a comprehensive consensus based tool (MetaPocket 2.0), and a recent deep learning based method (DeepSite). P2Rank belongs to the fastest available tools (requires under 1 s for prediction on one protein), with additional advantage of multi-threaded implementation.
Conclusions
P2Rank is a new open source software package for ligand binding site prediction from protein structure. It is available as a user-friendly stand-alone command line program and a Java library. P2Rank has a lightweight installation and does not depend on other bioinformatics tools or large structural or sequence databases. Thanks to its speed and ability to make fully automated predictions, it is particularly well suited for processing large datasets or as a component of scalable structural bioinformatics pipelines.
Mutual information and entropy transfer analysis employed on two inactive states of human beta‐2 adrenergic receptor (β2‐AR) unraveled distinct communication pathways. Previously, a so‐called ...“highly” inactive state of the receptor was observed during 1.5 microsecond long molecular dynamics simulation where the largest intracellular loop (ICL3) was swiftly packed onto the G‐protein binding cavity, becoming entirely inaccessible. Mutual information quantifying the degree of correspondence between backbone‐Cα fluctuations was mostly shared between intra‐ and extra‐cellular loop regions in the original inactive state, but shifted to entirely different regions in this latest inactive state. Interestingly, the largest amount of mutual information was always shared among the mobile regions. Irrespective of the conformational state, polar residues always contributed more to mutual information than hydrophobic residues, and also the number of polar‐polar residue pairs shared the highest degree of mutual information compared to those incorporating hydrophobic residues. Entropy transfer, quantifying the correspondence between backbone‐Cα fluctuations at different timesteps, revealed a distinctive pathway directed from the extracellular site toward intracellular portions in this recently exposed inactive state for which the direction of information flow was the reverse of that observed in the original inactive state where the mobile ICL3 and its intracellular surroundings drove the future fluctuations of extracellular regions.
PDF
