Structure of the phosphoinositide 3-kinase (PI3K) p110γ-p101 complex reveals molecular mechanism of GPCR activation.
TL;DR: In this paper, the authors report the structure of a heterodimeric PI3Kγ complex, p110γ-p101, which is a unique assembly of catalytic and regulatory subunits.
Abstract: The class IB phosphoinositide 3-kinase (PI3K), PI3Kγ, is a master regulator of immune cell function and a promising drug target for both cancer and inflammatory diseases. Critical to PI3Kγ function is the association of the p110γ catalytic subunit to either a p101 or p84 regulatory subunit, which mediates activation by G protein-coupled receptors. Here, we report the cryo-electron microscopy structure of a heterodimeric PI3Kγ complex, p110γ-p101. This structure reveals a unique assembly of catalytic and regulatory subunits that is distinct from other class I PI3K complexes. p101 mediates activation through its Gβγ-binding domain, recruiting the heterodimer to the membrane and allowing for engagement of a secondary Gβγ-binding site in p110γ. Mutations at the p110γ-p101 and p110γ-adaptor binding domain interfaces enhanced Gβγ activation. A nanobody that specifically binds to the p101-Gβγ interface blocks activation, providing a novel tool to study and target p110γ-p101-specific signaling events in vivo.
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TL;DR: In this paper , a review summarizes the molecular basis for the involvement of phosphoinositide kinases in disease and assesses the preclinical and clinical development of PI3K inhibitors.
Abstract: Lipid phosphoinositides are master regulators of almost all aspects of a cell's life and death and are generated by the tightly regulated activity of phosphoinositide kinases. Although extensive efforts have focused on drugging class I phosphoinositide 3-kinases (PI3Ks), recent years have revealed opportunities for targeting almost all phosphoinositide kinases in human diseases, including cancer, immunodeficiencies, viral infection and neurodegenerative disease. This has led to widespread efforts in the clinical development of potent and selective inhibitors of phosphoinositide kinases. This Review summarizes our current understanding of the molecular basis for the involvement of phosphoinositide kinases in disease and assesses the preclinical and clinical development of phosphoinositide kinase inhibitors.
12 citations
TL;DR: In this article, the authors used single-particle cryoelectron microscopy (cryo-EM) to determine three distinct conformations of full-length PI3Kα (p110α-p85α): the unliganded heterodimer PI3kα, PI3 kα bound to the p110α specific inhibitor BYL-719, and PI3 Kα exposed to an activating phosphopeptide.
Abstract: Phosphoinositide 3-kinases (PI3Ks) are lipid kinases essential for growth and metabolism. Their aberrant activation is associated with many types of cancers. Here we used single-particle cryoelectron microscopy (cryo-EM) to determine three distinct conformations of full-length PI3Kα (p110α-p85α): the unliganded heterodimer PI3Kα, PI3Kα bound to the p110α-specific inhibitor BYL-719, and PI3Kα exposed to an activating phosphopeptide. The cryo-EM structures of unbound and of BYL-719-bound PI3Kα are in general accord with published crystal structures. Local deviations are presented and discussed. BYL-719 stabilizes the structure of PI3Kα, but three regions of low-resolution extra density remain and are provisionally assigned to the cSH2, BH, and SH3 domains of p85. One of the extra density regions is in contact with the kinase domain blocking access to the catalytic site. This conformational change indicates that the effects of BYL-719 on PI3Kα activity extend beyond competition with adenosine triphosphate (ATP). In unliganded PI3Kα, the DFG motif occurs in the "in" and "out" positions. In BYL-719-bound PI3Kα, only the DFG-in position, corresponding to the active conformation of the kinase, was observed. The phosphopeptide-bound structure of PI3Kα is composed of a stable core resolved at 3.8 A. It contains all p110α domains except the adaptor-binding domain (ABD). The p85α domains, linked to the core through the ABD, are no longer resolved, implying that the phosphopeptide activates PI3Kα by fully releasing the niSH2 domain from binding to p110α. The structures presented here show the basal form of the full-length PI3Kα dimer and document conformational changes related to the activated and inhibited states.
12 citations
TL;DR: Using a combination of X-ray crystallography, hydrogen deuterium exchange mass spectrometry (HDX-MS), electron microscopy, molecular modeling, single-molecule imaging, and activity assays, the authors identify molecular differences between PI3Kγ-p84 and p110γp101 that explain their differential membrane recruitment and activation by Ras and GPCRs.
7 citations
TL;DR: In this article , a synergy of biochemical assays and hydrogen deuterium exchange mass spectrometry (HDX-MS) was used to reveal unique regulatory mechanisms underlying PI3K activation.
Abstract: Abstract PIK3CA encoding the phosphoinositide 3-kinase (PI3K) p110α catalytic subunit is frequently mutated in cancer, with mutations occurring widely throughout the primary sequence. The full set of mechanisms underlying how PI3Ks are activated by all oncogenic mutations on membranes are unclear. Using a synergy of biochemical assays and hydrogen deuterium exchange mass spectrometry (HDX-MS), we reveal unique regulatory mechanisms underlying PI3K activation. Engagement of p110α on membranes leads to disengagement of the ABD of p110α from the catalytic core, and the C2 domain from the iSH2 domain of the p85 regulatory subunit. PI3K activation also requires reorientation of the p110α C-terminus, with mutations that alter the inhibited conformation of the C-terminus increasing membrane binding. Mutations at the C-terminus (M1043I/L, H1047R, G1049R, and N1068KLKR) activate p110α through distinct mechanisms, with this having important implications for mutant selective inhibitor development. This work reveals unique mechanisms underlying how PI3K is activated by oncogenic mutations, and explains how double mutants can synergistically increase PI3K activity.
6 citations
TL;DR: The application of chemical cross-linking mass spectrometry (CXMS) facilitated the identification of the p85 domains BH, cSH2, and SH3 as well as their docking positions on the PI3Kα catalytic core.
Abstract: Significance PI3Kα is a dimeric lipid kinase consisting of a catalytic subunit p110α and a regulatory subunit p85α. It controls cell proliferation and survival and is an important therapeutic target for cancer. However, the development of effective drugs against PI3Kα requires a level of structural information that is currently unavailable, because the extreme flexibility of PI3Kα interferes with structural analysis. Nanobodies were used in conjunction with chemical cross-linking to generate insights into the identity and the positions of the most flexible domains of PI3Kα and into mechanistic aspects of positional flexibility. The studies also reveal the existence of a previously unreported structural conformation of PI3Kα.
5 citations
References
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TL;DR: Coot is a molecular-graphics program designed to assist in the building of protein and other macromolecular models and the current state of development and available features are presented.
Abstract: Coot is a molecular-graphics application for model building and validation of biological macromolecules. The program displays electron-density maps and atomic models and allows model manipulations such as idealization, real-space refinement, manual rotation/translation, rigid-body fitting, ligand search, solvation, mutations, rotamers and Ramachandran idealization. Furthermore, tools are provided for model validation as well as interfaces to external programs for refinement, validation and graphics. The software is designed to be easy to learn for novice users, which is achieved by ensuring that tools for common tasks are `discoverable' through familiar user-interface elements (menus and toolbars) or by intuitive behaviour (mouse controls). Recent developments have focused on providing tools for expert users, with customisable key bindings, extensions and an extensive scripting interface. The software is under rapid development, but has already achieved very widespread use within the crystallographic community. The current state of the software is presented, with a description of the facilities available and of some of the underlying methods employed.
22,053 citations
TL;DR: Key statistics on the current data contents and volume of downloads are outlined, and how PRIDE data are starting to be disseminated to added-value resources including Ensembl, UniProt and Expression Atlas are outlined.
Abstract: The PRoteomics IDEntifications (PRIDE) database (https://www.ebi.ac.uk/pride/) is the world’s largest data repository of mass spectrometry-based proteomics data, and is one of the founding members of the global ProteomeXchange (PX) consortium. In this manuscript, we summarize the developments in PRIDE resources and related tools since the previous update manuscript was published in Nucleic Acids Research in 2016. In the last 3 years, public data sharing through PRIDE (as part of PX) has definitely become the norm in the field. In parallel, data re-use of public proteomics data has increased enormously, with multiple applications. We first describe the new architecture of PRIDE Archive, the archival component of PRIDE. PRIDE Archive and the related data submission framework have been further developed to support the increase in submitted data volumes and additional data types. A new scalable and fault tolerant storage backend, Application Programming Interface and web interface have been implemented, as a part of an ongoing process. Additionally, we emphasize the improved support for quantitative proteomics data through the mzTab format. At last, we outline key statistics on the current data contents and volume of downloads, and how PRIDE data are starting to be disseminated to added-value resources including Ensembl, UniProt and Expression Atlas.
5,735 citations
01 Oct 2019
TL;DR: Recent developments in the Phenix software package are described in the context of macromolecular structure determination using X-rays, neutrons and electrons.
Abstract: Diffraction (X-ray, neutron and electron) and electron cryo-microscopy are powerful methods to determine three-dimensional macromolecular structures, which are required to understand biological processes and to develop new therapeutics against diseases. The overall structure-solution workflow is similar for these techniques, but nuances exist because the properties of the reduced experimental data are different. Software tools for structure determination should therefore be tailored for each method. Phenix is a comprehensive software package for macromolecular structure determination that handles data from any of these techniques. Tasks performed with Phenix include data-quality assessment, map improvement, model building, the validation/rebuilding/refinement cycle and deposition. Each tool caters to the type of experimental data. The design of Phenix emphasizes the automation of procedures, where possible, to minimize repetitive and time-consuming manual tasks, while default parameters are chosen to encourage best practice. A graphical user interface provides access to many command-line features of Phenix and streamlines the transition between programs, project tracking and re-running of previous tasks.
3,268 citations
TL;DR: Improvements to the public website and data-download systems and new functionality in COSMIC-3D allows exploration of mutations within three-dimensional protein structures, their protein structural and functional impacts, and implications for druggability.
Abstract: COSMIC, the Catalogue Of Somatic Mutations In Cancer (https://cancer.sanger.ac.uk) is the most detailed and comprehensive resource for exploring the effect of somatic mutations in human cancer. The latest release, COSMIC v86 (August 2018), includes almost 6 million coding mutations across 1.4 million tumour samples, curated from over 26 000 publications. In addition to coding mutations, COSMIC covers all the genetic mechanisms by which somatic mutations promote cancer, including non-coding mutations, gene fusions, copy-number variants and drug-resistance mutations. COSMIC is primarily hand-curated, ensuring quality, accuracy and descriptive data capture. Building on our manual curation processes, we are introducing new initiatives that allow us to prioritize key genes and diseases, and to react more quickly and comprehensively to new findings in the literature. Alongside improvements to the public website and data-download systems, new functionality in COSMIC-3D allows exploration of mutations within three-dimensional protein structures, their protein structural and functional impacts, and implications for druggability. In parallel with COSMIC's deep and broad variant coverage, the Cancer Gene Census (CGC) describes a curated catalogue of genes driving every form of human cancer. Currently describing 719 genes, the CGC has recently introduced functional descriptions of how each gene drives disease, summarized into the 10 cancer Hallmarks.
2,626 citations
TL;DR: It is found that large-scale genomic analysis can identify nearly all known cancer genes in these cancer types and 33 genes that were not previously known to be significantly mutated in cancer, including genes related to proliferation, apoptosis, genome stability, chromatin regulation, immune evasion, RNA processing and protein homeostasis.
Abstract: Although a few cancer genes are mutated in a high proportion of tumours of a given type (.20%), most are mutated at intermediate frequencies (2–20%). To explore the feasibility of creating a comprehensive catalogue of cancer genes, we analysed somatic point mutations in exome sequences from 4,742 human cancers and their matched normal-tissue samples across 21 cancer types. We found that large-scale genomic analysis can identify nearly all known cancer genes in these tumour types. Our analysis also identified 33 genes that were not previously known to be significantly mutated in cancer, including genes related to proliferation, apoptosis, genome stability, chromatin regulation, immune evasion, RNA processing and protein homeostasis. Down-sampling analysis indicates that larger sample sizes will reveal many more genes mutated at clinically important frequencies. We estimate that near-saturation may be achieved with 600– 5,000 samples per tumour type, depending on background mutation frequency. The results may help to guide the next stage of cancer genomics. Comprehensive knowledge of the genes underlying human cancers is a critical foundation for cancer diagnostics, therapeutics, clinical-trial design and selection of rational combination therapies. It is now possible to use genomic analysis to identify cancer genes in an unbiased fashion, based on the presence of somatic mutations at a rate significantly higher than the expected background level. Systematic studies have revealed many new cancer genes, as well as new classes of cancer genes 1,2 . They have also made clear that, although some cancer genes are mutated at high frequencies, most cancer genes in most patients occur at intermediate frequencies (2–20%) or lower. Accordingly, a complete catalogue of mutations in this frequency class will be essential for recognizing dysregulated pathways and optimal targets for therapeutic intervention. However, recent work suggests major gaps in our knowledge of cancer genes of intermediate frequency. For example, a study of 183 lung adenocarcinomas 3 found that 15% of patients lacked even a single mutation affecting any of the 10 known hallmarks of cancer, and 38% had 3 or fewer such mutations. In this paper, we analysed somatic point mutations (substitutions and small insertion and deletions) in nearly 5,000 human cancers and their matched normal-tissue samples (‘tumour–normal pairs’) across 21 tumour types. The questions that we examine here are: first, whether large-scale genomic analysis across tumour types can reliably identify all known cancer genes; second, whether it will reveal many new candidate cancer genes; and third, how far we are from having a complete catalogue of cancer genes (at least those of intermediate frequency). We used rigorous statistical methods to enumerate candidate cancer genes and then carefully inspected each gene to identify those with strong biological connections to cancer and mutational patterns consistent with the expected function. The analysis reveals nearly all known cancer genes and revealed 33 novel candidates, including genes related to proliferation, apoptosis, genome stability, chromatin regulation, immune evasion, RNA processing and protein homeostasis. Importantly, the data show that the
2,565 citations