A unified approach to the important protein kinase inhibitor balanol and a proposed analogue.
Ontology highlight
ABSTRACT:
SUBMITTER: Saha T
PROVIDER: S-EPMC3896276 | biostudies-literature | 2013 Dec
REPOSITORIES: biostudies-literature
Publications
A unified approach to the important protein kinase inhibitor balanol and a proposed analogue.
Saha Tapan T Maitra Ratnava R Chattopadhyay Shital K SK
Beilstein journal of organic chemistry 20131219
A common approach to the important protein kinase inhibitor (-)-balanol and an azepine-ring-modified balanol derivative has been developed using an efficient fragment coupling protocol which proceeded in good overall yield. ...[more]
Similar Datasets
Project description:G protein-coupled receptor kinase 2 (GRK2) is a pharmaceutical target for the treatment of cardiovascular diseases such as congestive heart failure, myocardial infarction, and hypertension. To better understand how nanomolar inhibition and selectivity for GRK2 might be achieved, we have determined crystal structures of human GRK2 in complex with Gbetagamma in the presence and absence of the AGC kinase inhibitor balanol. The selectivity of balanol among human GRKs is assessed.
| S-EPMC3073382 | biostudies-literature
Project description:BACKGROUND:(-)-Balanol is an ATP-mimicking inhibitor that non-selectively targets protein kinase C (PKC) isozymes and cAMP-dependent protein kinase (PKA). While PKA constantly shows tumor promoting activities, PKC isozymes can ambiguously be tumor promoters or suppressors. In particular, PKCε is frequently implicated in tumorigenesis and a potential target for anticancer drugs. We recently reported that the C5(S)-fluorinated balanol analogue (balanoid 1c) had improved binding affinity and selectivity for PKCε but not to the other novel PKC isozymes, which share a highly similar ATP site. The underlying basis for this fluorine-based selectivity is not entirely comprehended and needs to be investigated further for the development of ATP mimic inhibitors specific for PKCε. RESULTS:Using molecular dynamics (MD) simulations assisted by homology modelling and sequence analysis, we have studied the fluorine-based selectivity in the highly similar ATP sites of novel PKC (nPKC) isozymes. The study suggests that every nPKC isozyme has different dynamics behaviour in both apo and 1c-bound forms. Interestingly, the apo form of PKCε, where 1c binds strongly, shows the highest degree of flexibility which dramatically decreases after binding 1c. CONCLUSIONS:For the first time to the best of our knowledge, we found that the origin of 1c selectivity for PKCε comes from the unique dynamics feature of each PKC isozyme. Fluorine conformational control in 1c can synergize with and lock down the dynamics of PKCε, which optimize binding interactions with the ATP site residues of the enzyme, particularly the invariant Lys437. This finding has implications for further rational design of balanol-based PKCε inhibitors for cancer drug development.
| S-EPMC7394325 | biostudies-literature
Project description:Cryoelectron tomography of the cell nucleus using scanning transmission electron microscopy and deconvolution processing technology has highlighted a large-scale, 100- to 300-nm interphase chromosome structure, which is present throughout the nucleus. This study further documents and analyzes these chromosome structures. The paper is divided into four parts: 1) evidence (preliminary) for a unified interphase chromosome structure; 2) a proposed unified interphase chromosome architecture; 3) organization as chromosome territories (e.g., fitting the 46 human chromosomes into a 10-μm-diameter nucleus); and 4) structure unification into a polytene chromosome architecture and lampbrush chromosomes. Finally, the paper concludes with a living light microscopy cell study showing that the G1 nucleus contains very similar structures throughout. The main finding is that this chromosome structure appears to coil the 11-nm nucleosome fiber into a defined hollow structure, analogous to a Slinky helical spring [https://en.wikipedia.org/wiki/Slinky; motif used in Bowerman et al., eLife 10, e65587 (2021)]. This Slinky architecture can be used to build chromosome territories, extended to the polytene chromosome structure, as well as to the structure of lampbrush chromosomes.
| S-EPMC9245672 | biostudies-literature
Project description:Tyrosine and serine/threonine kinases are essential regulators of cell processes and are important targets for human therapies. Unfortunately, very little is known about specific kinase-substrate relationships, making it difficult to infer meaning from dysregulated phosphoproteomic datasets or for researchers to identify possible kinases that regulate specific or novel phosphorylation sites. The last two decades have seen an explosion in algorithms to extrapolate from what little is known into the larger unknown-predicting kinase relationships with site-specific substrates using a variety of approaches that include the sequence-specificity of kinase catalytic domains and various other factors, such as evolutionary relationships, co-expression, and protein-protein interaction networks. Unfortunately, a number of limitations prevent researchers from easily harnessing these resources, such as loss of resource accessibility, limited information in publishing that results in a poor mapping to a human reference, and not being updated to match the growth of the human phosphoproteome. Here, we propose a methodological framework for publishing predictions in a unified way, which entails ensuring predictions have been run on a current reference proteome, mapping the same substrates and kinases across resources to a common reference, filtering for the human phosphoproteome, and providing methods for updating the resource easily in the future. We applied this framework on three currently available resources, published in the last decade, which provide kinase-specific predictions in the human proteome. Using the unified datasets, we then explore the role of study bias, the emergent network properties of these predictive algorithms, and comparisons within and between predictive algorithms. The combination of the code for unification and analysis, as well as the unified predictions are available under the resource we named KinPred. We believe this resource will be useful for a wide range of applications and establishes best practices for long-term usability and sustainability for new and existing predictive algorithms.
| S-EPMC7895412 | biostudies-literature
Project description:G-protein-coupled-receptor (GPCR) signaling is exquisitely controlled to achieve spatial and temporal specificity. The endogenous protein kinase inhibitor peptide (PKI) confines the spatial and temporal spread of the activity of protein kinase A (PKA), which integrates inputs from three major types of GPCRs. Despite its wide usage as a pharmaceutical inhibitor of PKA, it was unclear whether PKI only inhibits PKA activity. Here, the effects of PKI on 55 mouse kinases were tested in in vitro assays. We found that in addition to inhibiting PKA activity, both PKI (6-22) amide and full-length PKIα facilitated the activation of multiple isoforms of protein kinase C (PKC), albeit at much higher concentrations than necessary to inhibit PKA. Thus, our results call for appropriate interpretation of experimental results using PKI as a pharmaceutical agent. Furthermore, our study lays the foundation to explore the potential functions of PKI in regulating PKC activity and in coordinating PKC and PKA activities.
| S-EPMC7878667 | biostudies-literature
Project description:Structure-based drug design of protein-kinase inhibitors has been facilitated by availability of an enormous number of structures in the Protein Databank (PDB), systematic analyses of which can provide insight into the factors that govern ligand-protein kinase interactions and into the conformational variability of the protein kinases. In this study, a nonredundant database containing 755 unique, curated, and annotated PDB protein kinase-inhibitor complexes (each consisting of a single protein kinase chain, a ligand, and water molecules around the ligand) was created. With this dataset, analyses were performed of protein conformational variability and interactions of ligands with 11 P-loop residues. Analysis of ligand-protein interactions included ligand atom preference, ligand-protein hydrogen bonds, and the number and position of crystallographic water molecules around important P-loop residues. Analysis of variability in the conformation of the P-loop considered backbone and side-chain dihedral angles, and solvent accessible surface area (SASA). A distorted conformation of the P-loop was observed for some of the protein kinase structures. Lower SASA was observed for the hydrophobic residue in beta1 of several members of the AGC family of protein kinases. Our systematic studies were performed amino acid-by-amino acid, which is unusual for analyses of protein kinase-inhibitor complexes.
| S-EPMC3235399 | biostudies-literature
Project description:MotivationIt is fundamental to cut multi-domain proteins into individual domains, for precise domain-based structural and functional studies. In the past, sequence-based and structure-based domain parsing was carried out independently with different methodologies. The recent progress in deep learning-based protein structure prediction provides the opportunity to unify sequence-based and structure-based domain parsing.ResultsBased on the inter-residue distance matrix, which can be either derived from the input structure or predicted by trRosettaX, we can decode the domain boundaries under a unified framework. We name the proposed method UniDoc. The principle of UniDoc is based on the well-accepted physical concept of maximizing intra-domain interaction while minimizing inter-domain interaction. Comprehensive tests on five benchmark datasets indicate that UniDoc outperforms other state-of-the-art methods in terms of both accuracy and speed, for both sequence-based and structure-based domain parsing. The major contribution of UniDoc is providing a unified framework for structure-based and sequence-based domain parsing. We hope that UniDoc would be a convenient tool for protein domain analysis.Availability and implementationhttps://yanglab.nankai.edu.cn/UniDoc/.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC9919455 | biostudies-literature
Project description:Protein-peptide interactions are vital for the cell. They mediate, inhibit or serve as structural components in nearly 40% of all macromolecular interactions, and are often associated with diseases, making them interesting leads for protein drug design. In recent years, large-scale technologies have enabled exhaustive studies on the peptide recognition preferences for a number of peptide-binding domain families. Yet, the paucity of data regarding their molecular binding mechanisms together with their inherent flexibility makes the structural prediction of protein-peptide interactions very challenging. This leaves flexible docking as one of the few amenable computational techniques to model these complexes. We present here an ensemble, flexible protein-peptide docking protocol that combines conformational selection and induced fit mechanisms. Starting from an ensemble of three peptide conformations (extended, a-helix, polyproline-II), flexible docking with HADDOCK generates 79.4% of high quality models for bound/unbound and 69.4% for unbound/unbound docking when tested against the largest protein-peptide complexes benchmark dataset available to date. Conformational selection at the rigid-body docking stage successfully recovers the most relevant conformation for a given protein-peptide complex and the subsequent flexible refinement further improves the interface by up to 4.5 Å interface RMSD. Cluster-based scoring of the models results in a selection of near-native solutions in the top three for ∼75% of the successfully predicted cases. This unified conformational selection and induced fit approach to protein-peptide docking should open the route to the modeling of challenging systems such as disorder-order transitions taking place upon binding, significantly expanding the applicability limit of biomolecular interaction modeling by docking.
| S-EPMC3596317 | biostudies-literature
Project description:Protein kinase A (PKA), the main effector of cAMP in eukaryotes, is a paradigm for the mechanisms of ligand-dependent and allosteric regulation in signalling. Here we report the orthologous but cAMP-independent PKA of the protozoan Trypanosoma and identify 7-deaza-nucleosides as potent activators (EC50 ≥ 6.5 nM) and high affinity ligands (KD ≥ 8 nM). A co-crystal structure of trypanosome PKA with 7-cyano-7-deazainosine and molecular docking show how substitution of key amino acids in both CNB domains of the regulatory subunit and its unique C-terminal αD helix account for this ligand swap between trypanosome PKA and canonical cAMP-dependent PKAs. We propose nucleoside-related endogenous activators of Trypanosoma brucei PKA (TbPKA). The existence of eukaryotic CNB domains not associated with binding of cyclic nucleotides suggests that orphan CNB domains in other eukaryotes may bind undiscovered signalling molecules. Phosphoproteome analysis validates 7-cyano-7-deazainosine as powerful cell-permeable inducer to explore cAMP-independent PKA signalling in medically important neglected pathogens.
| S-EPMC6440977 | biostudies-literature
Project description:Although Fischer's extraordinary career came to focus mostly on the protein phosphatases, after his co-discovery of Phosphorylase Kinase with Ed Krebs he was clearly intrigued not only by cAMP-dependent protein kinase (PKA), but also by the heat-stable, high-affinity protein kinase inhibitor (PKI). PKI is an intrinsically disordered protein that contains at its N-terminus a pseudo-substrate motif that binds synergistically and with high-affinity to the PKA catalytic (C) subunit. The sequencing and characterization of this inhibitor peptide (IP20) were validated by the structure of the PKA C-subunit solved first as a binary complex with IP20 and then as a ternary complex with ATP and two magnesium ions. A second motif, nuclear export signal (NES), was later discovered in PKI. Both motifs correspond to amphipathic helices that convey high-affinity binding. The dynamic features of full-length PKI, recently captured by NMR, confirmed that the IP20 motif becomes dynamically and sequentially ordered only in the presence of the C-subunit. The type I PKA regulatory (R) subunits also contain a pseudo-substrate ATPMg2-dependent high-affinity inhibitor sequence. PKI and PKA, especially the Cβ subunit, are highly expressed in the brain, and PKI expression is also cell cycle-dependent. In addition, PKI is now linked to several cancers. The full biological importance of PKI and PKA signaling in the brain, and their importance in cancer thus remains to be elucidated.
| S-EPMC10050139 | biostudies-literature