The ADAMTS (A Disintegrin and Metalloproteinase with Thrombospondin motifs) family

The ADAMTS (A Disintegrin and Metalloproteinase with Thrombospondin motifs) enzymes are secreted, multi-domain matrix-associated zinc metalloendopeptidases that have diverse roles in tissue morphogenesis and patho-physiological remodeling, in inflammation and in vascular biology. The human family includes 19 members that can be sub-grouped on the basis of their known substrates, namely the aggrecanases or proteoglycanases (ADAMTS1, 4, 5, 8, 9, 15 and 20), the procollagen N-propeptidases (ADAMTS2, 3 and 14), the cartilage oligomeric matrix protein-cleaving enzymes (ADAMTS7 and 12), the von-Willebrand Factor proteinase (ADAMTS13) and a group of orphan enzymes (ADAMTS6, 10, 16, 17, 18 and 19). Control of the structure and function of the extracellular matrix (ECM) is a central theme of the biology of the ADAMTS, as exemplified by the actions of the procollagen-N-propeptidases in collagen fibril assembly and of the aggrecanases in the cleavage or modification of ECM proteoglycans. Defects in certain family members give rise to inherited genetic disorders, while the aberrant expression or function of others is associated with arthritis, cancer and cardiovascular disease. In particular, ADAMTS4 and 5 have emerged as therapeutic targets in arthritis. Multiple ADAMTSs from different sub-groupings exert either positive or negative effects on tumorigenesis and metastasis, with both metalloproteinase-dependent and -independent actions known to occur. The basic ADAMTS structure comprises a metalloproteinase catalytic domain and a carboxy-terminal ancillary domain, the latter determining substrate specificity and the localization of the protease and its interaction partners; ancillary domains probably also have independent biological functions. Focusing primarily on the aggrecanases and proteoglycanases, this review provides a perspective on the evolution of the ADAMTS family, their links with developmental and disease mechanisms, and key questions for the future

Structure-guided selection of specificity determining positions in the human kinome

Background: The human kinome contains many important drug targets. It is well-known that inhibitors of protein kinases bind with very different selectivity profiles. This is also the case for inhibitors of many other protein families. The increased availability of protein 3D structures has provided much information on the structural variation within a given protein family. However, the relationship between structural variations and binding specificity is complex and incompletely understood. We have developed a structural bioinformatics approach which provides an analysis of key determinants of binding selectivity as a tool to enhance the rational design of drugs with a specific selectivity profile. Results: We propose a greedy algorithm that computes a subset of residue positions in a multiple sequence alignment such that structural and chemical variation in those positions helps explain known binding affinities. By providing this information, the main purpose of the algorithm is to provide experimentalists with possible insights into how the selectivity profile of certain inhibitors is achieved, which is useful for lead optimization. In addition, the algorithm can also be used to predict binding affinities for structures whose affinity for a given inhibitor is unknown. The algorithm’s performance is demonstrated using an extensive dataset for the human kinome. Conclusion: We show that the binding affinity of 38 different kinase inhibitors can be explained with consistently high precision and accuracy using the variation of at most six residue positions in the kinome binding site. We show for several inhibitors that we are able to identify residues that are known to be functionally important

SPPS: A Sequence-Based Method for Predicting Probability of Protein-Protein Interaction Partners

Background: The molecular network sustained by different types of interactions among proteins is widely manifested as the fundamental driving force of cellular operations. Many biological functions are determined by the crosstalk between proteins rather than by the characteristics of their individual components. Thus, the searches for protein partners in global networks are imperative when attempting to address the principles of biology. Results: We have developed a web-based tool ‘‘Sequence-based Protein Partners Search’ ’ (SPPS) to explore interacting partners of proteins, by searching over a large repertoire of proteins across many species. SPPS provides a database containing more than 60,000 protein sequences with annotations and a protein-partner search engine in two modes (Single Query and Multiple Query). Two interacting proteins of human FBXO6 protein have been found using the service in the study. In addition, users can refine potential protein partner hits by using annotations and possible interactive network in the SPPS web server. Conclusions: SPPS provides a new type of tool to facilitate the identification of direct or indirect protein partners which may guide scientists on the investigation of new signaling pathways. The SPPS server is available to the public a

Genetic and Computational Identification of a Conserved Bacterial Metabolic Module

We have experimentally and computationally defined a set of genes that form a conserved metabolic module in the α-proteobacterium Caulobacter crescentus and used this module to illustrate a schema for the propagation of pathway-level annotation across bacterial genera. Applying comprehensive forward and reverse genetic methods and genome-wide transcriptional analysis, we (1) confirmed the presence of genes involved in catabolism of the abundant environmental sugar myo-inositol, (2) defined an operon encoding an ABC-family myo-inositol transmembrane transporter, and (3) identified a novel myo-inositol regulator protein and cis-acting regulatory motif that control expression of genes in this metabolic module. Despite being encoded from non-contiguous loci on the C. crescentus chromosome, these myo-inositol catabolic enzymes and transporter proteins form a tightly linked functional group in a computationally inferred network of protein associations. Primary sequence comparison was not sufficient to confidently extend annotation of all components of this novel metabolic module to related bacterial genera. Consequently, we implemented the Graemlin multiple-network alignment algorithm to generate cross-species predictions of genes involved in myo-inositol transport and catabolism in other α-proteobacteria. Although the chromosomal organization of genes in this functional module varied between species, the upstream regions of genes in this aligned network were enriched for the same palindromic cis-regulatory motif identified experimentally in C. crescentus. Transposon disruption of the operon encoding the computationally predicted ABC myo-inositol transporter of Sinorhizobium meliloti abolished growth on myo-inositol as the sole carbon source, confirming our cross-genera functional prediction. Thus, we have defined regulatory, transport, and catabolic genes and a cis-acting regulatory sequence that form a conserved module required for myo-inositol metabolism in select α-proteobacteria. Moreover, this study describes a forward validation of gene-network alignment, and illustrates a strategy for reliably transferring pathway-level annotation across bacterial species

A short history of the 5-HT2C receptor: from the choroid plexus to depression, obesity and addiction treatment

This paper is a personal account on the discovery and characterization of the 5-HT2C receptor (first known as the 5- HT1C receptor) over 30 years ago and how it translated into a number of unsuspected features for a G protein-coupled receptor (GPCR) and a diversity of clinical applications. The 5-HT2C receptor is one of the most intriguing members of the GPCR superfamily. Initially referred to as 5-HT1CR, the 5-HT2CR was discovered while studying the pharmacological features and the distribution of [3H]mesulergine-labelled sites, primarily in the brain using radioligand binding and slice autoradiography. Mesulergine (SDZ CU-085), was, at the time, best defined as a ligand with serotonergic and dopaminergic properties. Autoradiographic studies showed remarkably strong [3H]mesulergine-labelling to the rat choroid plexus. [3H]mesulergine-labelled sites had pharmacological properties different from, at the time, known or purported 5-HT receptors. In spite of similarities with 5-HT2 binding, the new binding site was called 5-HT1C because of its very high affinity for 5-HT itself. Within the following 10 years, the 5-HT1CR (later named 5- HT2C) was extensively characterised pharmacologically, anatomically and functionally: it was one of the first 5-HT receptors to be sequenced and cloned. The 5-HT2CR is a GPCR, with a very complex gene structure. It constitutes a rarity in theGPCR family: many 5-HT2CR variants exist, especially in humans, due to RNA editing, in addition to a few 5-HT2CR splice variants. Intense research led to therapeutically active 5-HT2C receptor ligands, both antagonists (or inverse agonists) and agonists: keeping in mind that a number of antidepressants and antipsychotics are 5- HT2CR antagonists/inverse agonists. Agomelatine, a 5-HT2CR antagonist is registered for the treatment of major depression. The agonist Lorcaserin is registered for the treatment of aspects of obesity and has further potential in addiction, especially nicotine/ smoking. There is good evidence that the 5-HT2CR is involved in spinal cord injury-induced spasms of the lower limbs, which can be treated with 5-HT2CR antagonists/inverse agonists such as cyproheptadine or SB206553. The 5-HT2CR may play a role in schizophrenia and epilepsy. Vabicaserin, a 5-HT2CR agonist has been in development for the treatment of schizophrenia and obesity, but was stopped. As is common, there is potential for further indications for 5-HT2CR ligands, as suggested by a number of preclinical and/or genome-wide association studies (GWAS) on depression, suicide, sexual dysfunction, addictions and obesity. The 5-HT2CR is clearly affected by a number of established antidepressants/antipsychotics and may be one of the culprits in antipsychotic-induced weight gain

Combination of searches for heavy spin-1 resonances using 139 fb−1 of proton-proton collision data at s = 13 TeV with the ATLAS detector

A combination of searches for new heavy spin-1 resonances decaying into different pairings of W, Z, or Higgs bosons, as well as directly into leptons or quarks, is presented. The data sample used corresponds to 139 fb−1 of proton-proton collisions at = 13 TeV collected during 2015–2018 with the ATLAS detector at the CERN Large Hadron Collider. Analyses selecting quark pairs (qq, bb, , and tb) or third-generation leptons (τν and ττ) are included in this kind of combination for the first time. A simplified model predicting a spin-1 heavy vector-boson triplet is used. Cross-section limits are set at the 95% confidence level and are compared with predictions for the benchmark model. These limits are also expressed in terms of constraints on couplings of the heavy vector-boson triplet to quarks, leptons, and the Higgs boson. The complementarity of the various analyses increases the sensitivity to new physics, and the resulting constraints are stronger than those from any individual analysis considered. The data exclude a heavy vector-boson triplet with mass below 5.8 TeV in a weakly coupled scenario, below 4.4 TeV in a strongly coupled scenario, and up to 1.5 TeV in the case of production via vector-boson fusion

Maximizing and stabilizing luminescence from halide perovskites with potassium passivation

Metal halide perovskites are of great interest for various high-performance optoelectronic applications. The ability to tune the perovskite bandgap continuously by modifying the chemical composition opens up applications for perovskites as coloured emitters, in building-integrated photovoltaics, and as components of tandem photovoltaics to increase the power conversion efficiency. Nevertheless, performance is limited by non-radiative losses, with luminescence yields in state-of-the-art perovskite solar cells still far from 100 per cent under standard solar illumination conditions. Furthermore, in mixed halide perovskite systems designed for continuous bandgap tunability2 (bandgaps of approximately 1.7 to 1.9 electronvolts), photoinduced ion segregation leads to bandgap instabilities. Here we demonstrate substantial mitigation of both non-radiative losses and photoinduced ion migration in perovskite films and interfaces by decorating the surfaces and grain boundaries with passivating potassium halide layers. We demonstrate external photoluminescence quantum yields of 66 per cent, which translate to internal yields that exceed 95 per cent. The high luminescence yields are achieved while maintaining high mobilities of more than 40 square centimetres per volt per second, providing the elusive combination of both high luminescence and excellent charge transport. When interfaced with electrodes in a solar cell device stack, the external luminescence yield—a quantity that must be maximized to obtain high efficiency—remains as high as 15 per cent, indicating very clean interfaces. We also demonstrate the inhibition of transient photoinduced ion-migration processes across a wide range of mixed halide perovskite bandgaps in materials that exhibit bandgap instabilities when unpassivated. We validate these results in fully operating solar cells. Our work represents an important advance in the construction of tunable metal halide perovskite films and interfaces that can approach the efficiency limits in tandem solar cells, coloured-light-emitting diodes and other optoelectronic applications.M.A.-J. thanks Nava Technology Limited and Nyak Technology Limited for their funding and technical support. Z.A.-G. acknowledges funding from a Winton Studentship, and ICON Studentship from the Lloyd’s Register Foundation. This project has received funding from the European Union’s Seventh Framework Programme (FP7/2007-2013) under REA grant agreement number PIOF-GA-2013-622630, the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement number 756962), and the Royal Society and Tata Group (UF150033). We thank the Engineering and Physical Sciences Research Council (EPSRC) for support. XMaS is a mid-range facility at the European Synchrotron Radiation Facility supported by the EPSRC and we are grateful to the XMaS beamline team staff for their support. We thank Diamond Light Source for access to beamline I09 and staff member T.-L. Lee as well as U. Cappel for assistance during the HAXPES measurements. S.C., C.D. and G.D. acknowledge funding from the ERC under grant number 25961976 PHOTO EM and financial support from the European Union under grant number 77 312483 ESTEEM2. M.A. thanks the president of the UAE’s Distinguished Student Scholarship Program, granted by the Ministry of Presidential Affairs. H.R. and B.P. acknowledge support from the Swedish research council (2014-6019) and the Swedish foundation for strategic research. E.M.H. and T.J.S. were supported by the Netherlands Organization for Scientific Research under the Echo grant number 712.014.007

A Novel Method to Detect Proteins Evolving at Correlated Rates: Identifying New Functional Relationships between Coevolving Proteins

Interacting proteins evolve at correlated rates, possibly as the result of evolutionary pressures shared by functional groups and/or coevolution between interacting proteins. This evolutionary signature can be exploited to learn more about protein networks and to infer functional relationships between proteins on a genome-wide scale. Multiple methods have been introduced that detect correlated evolution using amino acid distances. One assumption made by these methods is that the neutral rate of nucleotide substitution is uniform over time; however, this is unlikely and such rate heterogeneity would adversely affect amino acid distance methods. We explored alternative methods that detect correlated rates using protein-coding nucleotide sequences in order to better estimate the rate of nonsynonymous substitution at each branch (dN) normalized by the underlying synonymous substitution rate (dS). Our novel likelihood method, which was robust to realistic simulation parameters, was tested on Drosophila nuclear pore proteins, which form a complex with well-documented physical interactions. The method revealed significantly correlated evolution between nuclear pore proteins, where members of a stable subcomplex showed stronger correlations compared with those proteins that interact transiently. Furthermore, our likelihood approach was better able to detect correlated evolution among closely related species than previous methods. Hence, these sequence-based methods are a complementary approach for detecting correlated evolution and could be applied genome-wide to provide candidate protein–protein interactions and functional group assignments using just coding sequences