Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Recognition of ASF1 by Using Hydrocarbon-Constrained Peptides.

ABSTRACT: Inhibiting the histone H3-ASF1 (anti-silencing function?1) protein-protein interaction (PPI) represents a potential approach for treating numerous cancers. As an ?-helix-mediated PPI, constraining the key histone H3 helix (residues 118-135) is a strategy through which chemical probes might be elaborated to test this hypothesis. In this work, variant H3118-135 peptides bearing pentenylglycine residues at the i and i+4 positions were constrained by olefin metathesis. Biophysical analyses revealed that promotion of a bioactive helical conformation depends on the position at which the constraint is introduced, but that the potency of binding towards ASF1 is unaffected by the constraint and instead that enthalpy-entropy compensation occurs.

SUBMITTER: Bakail M

PROVIDER: S-EPMC6468270 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Recognition of ASF1 by Using Hydrocarbon-Constrained Peptides.

Bakail May M Rodriguez-Marin Silvia S Hegedüs Zsófia Z Perrin Marie E ME Ochsenbein Françoise F Wilson Andrew J AJ

Chembiochem : a European journal of chemical biology 20190213 7

Inhibiting the histone H3-ASF1 (anti-silencing function 1) protein-protein interaction (PPI) represents a potential approach for treating numerous cancers. As an α-helix-mediated PPI, constraining the key histone H3 helix (residues 118-135) is a strategy through which chemical probes might be elaborated to test this hypothesis. In this work, variant H3<sub>118-135</sub> peptides bearing pentenylglycine residues at the i and i+4 positions were constrained by olefin metathesis. Biophysical analyse ...[more]

PMID: 30512234

Similar Datasets

Hydrocarbon constrained peptides - understanding preorganisation and binding affinity.

Project description:The development of constrained peptides represents an emerging strategy to generate peptide based probes and hits for drug-discovery that address challenging protein-protein interactions (PPIs). In this manuscript we report on the use of a novel ?-alkenylglycine derived amino acid to synthesise hydrocarbon constrained BH3-family sequences (BIM and BID). Our biophysical and structural analyses illustrate that whilst the introduction of the constraint increases the population of the bioactive ?-helical conformation of the peptide in solution, it does not enhance the inhibitory potency against pro-apoptotic Bcl-xL and Mcl-1 PPIs. SPR analyses indicate binding occurs via an induced fit mechanism whilst X-ray analyses illustrate none of the key interactions between the helix and protein are disturbed. The behaviour derives from enthalpy-entropy compensation which may be considered in terms of the ground state energies of the unbound constrained and unconstrained peptides; this has implications for the design of preorganised peptides to target protein-protein interactions.

| S-EPMC5618334 | biostudies-literature

Constrained De Novo Sequencing of neo-Epitope Peptides using Tandem Mass Spectrometry.

Project description:Neoepitope peptides are newly formed antigens presented by major histocompatibility complex class I (MHC-I) on cell surfaces. The cells presenting neoepitope peptides are recognized and subsequently killed by cytotoxic T-cells. Immunopeptidomic approaches aim to characterize the peptide repertoire (including neoepitope) associated with the MHC-I molecules on the surface of tumor cells using proteomic technologies, providing critical information for designing effective immunotherapy strategies. We developed a novel constrained de novo sequencing algorithm to identify neo-epitope peptides from tandem mass spectra acquired in immunopeptidomic analyses. Our method incorporates prior probabilities to putative peptides according to position specific scoring matrices (PSSMs) representing the sequence preferences recognized by MHC-I molecules. We implemented a dynamic programming algorithm to determine the peptide sequences with an optimal posterior matching score for each given MS/MS spectrum. Similar to the de novo peptide sequencing, the dynamic programming algorithm allows an efficient searching in the entire peptide sequence space. On an LC-MS/MS dataset, we demonstrated the performance of our algorithm in detecting the neoepitope peptides bound by the HLA-C*0501 molecules that were superior to database search approaches and existing general purpose de novo peptide sequencing algorithms.

| S-EPMC6901291 | biostudies-literature

Isoform-selective disruption of AKAP-localized PKA using hydrocarbon stapled peptides.

Project description:A-kinase anchoring proteins (AKAPs) play an important role in the spatial and temporal regulation of protein kinase A (PKA) by scaffolding critical intracellular signaling complexes. Here we report the design of conformationally constrained peptides that disrupt interactions between PKA and AKAPs in an isoform-selective manner. Peptides derived from the A Kinase Binding (AKB) domain of several AKAPs were chemically modified to contain an all-hydrocarbon staple and target the docking/dimerization domain of PKA-R, thereby occluding AKAP interactions. The peptides are cell-permeable against diverse human cell lines, are highly isoform-selective for PKA-RII, and can effectively inhibit interactions between AKAPs and PKA-RII in intact cells. These peptides can be applied as useful reagents in cell-based studies to selectively disrupt AKAP-localized PKA-RII activity and block AKAP signaling complexes. In summary, the novel hydrocarbon-stapled peptides developed in this study represent a new class of AKAP disruptors to study compartmentalized RII-regulated PKA signaling in cells.

| S-EPMC3985448 | biostudies-literature

ChemPix: automated recognition of hand-drawn hydrocarbon structures using deep learning.

Project description:Inputting molecules into chemistry software, such as quantum chemistry packages, currently requires domain expertise, expensive software and/or cumbersome procedures. Leveraging recent breakthroughs in machine learning, we develop ChemPix: an offline, hand-drawn hydrocarbon structure recognition tool designed to remove these barriers. A neural image captioning approach consisting of a convolutional neural network (CNN) encoder and a long short-term memory (LSTM) decoder learned a mapping from photographs of hand-drawn hydrocarbon structures to machine-readable SMILES representations. We generated a large auxiliary training dataset, based on RDKit molecular images, by combining image augmentation, image degradation and background addition. Additionally, a small dataset of ∼600 hand-drawn hydrocarbon chemical structures was crowd-sourced using a phone web application. These datasets were used to train the image-to-SMILES neural network with the goal of maximizing the hand-drawn hydrocarbon recognition accuracy. By forming a committee of the trained neural networks where each network casts one vote for the predicted molecule, we achieved a nearly 10 percentage point improvement of the molecule recognition accuracy and were able to assign a confidence value for the prediction based on the number of agreeing votes. The ensemble model achieved an accuracy of 76% on hand-drawn hydrocarbons, increasing to 86% if the top 3 predictions were considered.

| S-EPMC8365825 | biostudies-literature

Using Peptidomimetics and Constrained Peptides as Valuable Tools for Inhibiting Protein⁻Protein Interactions.

Project description:Protein⁻protein interactions (PPIs) are tremendously important for the function of many biological processes. However, because of the structure of many protein⁻protein interfaces (flat, featureless and relatively large), they have largely been overlooked as potential drug targets. In this review, we highlight the current tools used to study the molecular recognition of PPIs through the use of different peptidomimetics, from small molecules and scaffolds to peptides. Then, we focus on constrained peptides, and in particular, ways to constrain α-helices through stapling using both one- and two-component techniques.

| S-EPMC6017787 | biostudies-literature

Solid-phase synthesis of tetrahydropyridazinedione-constrained peptides.

Project description:The design and solid-phase synthesis of tetrahydropyridazine-3,6-dione (Tpd) peptidomimetics derived from backbone-aminated peptides is reported. The described protocol features the synthesis of chiral ?-hydrazino acids suitable for chemoselective incorporation into growing peptide chains. Acid-catalyzed cyclization to form the Tpd ring during cleavage affords the target peptidomimetics in good yield and purity. The scope of Tpd incorporation is demonstrated through the synthesis of constrained peptides featuring nucleophilic/electrophilic side chains and sterically encumbered ?-substituted hydrazino acid residues.

| S-EPMC4201324 | biostudies-literature

Hydrocarbon-stapled peptides: principles, practice, and progress.

Project description:Protein structure underlies essential biological processes and provides a blueprint for molecular mimicry that drives drug discovery. Although small molecules represent the lion's share of agents that target proteins for therapeutic benefit, there remains no substitute for the natural properties of proteins and their peptide subunits in the majority of biological contexts. The peptide α-helix represents a common structural motif that mediates communication between signaling proteins. Because peptides can lose their shape when taken out of context, developing chemical interventions to stabilize their bioactive structure remains an active area of research. The all-hydrocarbon staple has emerged as one such solution, conferring α-helical structure, protease resistance, cellular penetrance, and biological activity upon successful incorporation of a series of design and application principles. Here, we describe our more than decade-long experience in developing stapled peptides as biomedical research tools and prototype therapeutics, highlighting lessons learned, pitfalls to avoid, and keys to success.

| S-EPMC4136684 | biostudies-other

Multisite Substrate Recognition in Asf1-Dependent Acetylation of Histone H3 K56 by Rtt109.

Project description:Rtt109 is a unique histone acetyltransferase acetylating histone H3 lysine 56 (H3K56), a modification critical for DNA replication-coupled nucleosome assembly and genome stability. In cells, histone chaperone Asf1 is essential for H3K56 acetylation, yet the mechanisms for H3K56 specificity and Asf1 requirement remain unknown. We have determined the crystal structure of the Rtt109-Asf1-H3-H4 complex and found that unwinding of histone H3 αN, where K56 is normally located, and stabilization of the very C-terminal β strand of histone H4 by Asf1 are prerequisites for H3K56 acetylation. Unexpectedly, an interaction between Rtt109 and the central helix of histone H3 is also required. The observed multiprotein, multisite substrate recognition mechanism among histone modification enzymes provides mechanistic understandings of Rtt109 and Asf1 in H3K56 acetylation, as well as valuable insights into substrate recognition by histone modification enzymes in general.

| S-EPMC6103222 | biostudies-literature

Structural insights reveal a recognition feature for tailoring hydrocarbon stapled-peptides against the eukaryotic translation initiation factor 4E protein.

Project description:Stapled-peptides have emerged as an exciting class of molecules which can modulate protein-protein interactions. We have used a structure-guided approach to rationally develop a set of hydrocarbon stapled-peptides with high binding affinities and residence times against the oncogenic eukaryotic translation initiation factor 4E (eIF4E) protein. Crystal structures of these peptides in complex with eIF4E show that they form specific interactions with a region on the protein-binding interface of eIF4E which is distinct from the other well-established canonical interactions. This recognition element is a major molecular determinant underlying the improved binding kinetics of these peptides with eIF4E. The interactions were further exploited by designing features in the peptides to attenuate disorder and increase helicity which collectively resulted in the generation of a distinct class of hydrocarbon stapled-peptides targeting eIF4E. This study details new insights into the molecular basis of stapled-peptide: eIF4E interactions and their exploitation to enhance promising lead molecules for the development of stapled-peptide compounds for oncology.

| S-EPMC6385854 | biostudies-literature

β-Ginkgotides: Hyperdisulfide-constrained peptides from Ginkgo biloba.

Project description:Hyperdisulfide-constrained peptides are distinguished by their high stability and diverse functions. Thus far, these peptides have been reported from animals only but their occurrence in plants are rare. Here, we report the discovery, synthesis and characterization of a hyperdisulfide-constrained peptides family of approximately 2 kDa, β-ginkgotides (β-gB1 and β-gB2) from Ginkgo biloba. Proteomic analysis showed β-ginkgotides contain 18‒20 amino acids, of which 16 residues form a conserved six-cysteine core with a highly clustered cysteine spacing of C‒CC‒C‒CC, an arrangement that has not been reported in cysteine-rich peptides. Disulfide mapping revealed a novel disulfide connectivity of CysI‒IV, CysII‒VI and CysIII‒V. Oxidative folding of synthetic β-gB1 to the native form was obtained in 70% yield. The synthetic β-gB1 displays a compact structure with no regular secondary structural elements, as determined by NMR spectroscopy. Transcriptomic analysis showed precursor βgb1 has a four-domain architecture and revealed an additional 76 β-ginkgotide-like peptides in 59 different gymnosperms, but none in angiosperms. Phylogenetic clustering analysis demonstrated β-ginkgotides belong to a new cysteine-rich peptide family. β-Ginkgotide is resistant to thermal, chemical and proteolytic degradation. Together, β-ginkgotides represent the first-in-class hyperdisulfide-constrained peptide family from plants with a novel scaffold that could be useful for engineering metabolically stable peptidyl therapeutics.

| S-EPMC5522442 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data