Prediction of kinase-specific phosphorylation sites through an integrative model of protein context and sequence

Mapping Intimacies ◽

10.1101/043679 ◽

2016 ◽

Author(s):

Ralph Patrick ◽

Coralie Horin ◽

Bostjan Kobe ◽

Kim-Anh Lê Cao ◽

Mikael Bodén

Keyword(s):

Protein Interactions ◽

Binding Sites ◽

Protein Function ◽

Computational Prediction ◽

Alternative Methods ◽

Integrative Model ◽

Model Organisms ◽

Phosphorylation Sites ◽

Nuclear Localisation ◽

Cellular Context

AbstractThe identification of kinase substrates and the specific phosphorylation sites they regulate is an important factor in understanding protein function regulation and signalling pathways. Computational prediction of kinase targets – assigning kinases to putative substrates, and selecting from protein sequence the sites that kinases can phosphorylate – requires the consideration of both the cellular context that kinases operate in, as well as their binding affinity. This consideration enables investigation of how phosphorylation influences a range of biological processes.We report here a novel probabilistic model for the classification of kinase-specific phosphorylation sites from sequence across three model organisms: human, mouse and yeast. The model incorporates position-specific amino acid frequencies, and counts of co-occurring amino acids from kinase binding sites in a kinase‐ and family-specific manner. We show how this model can be seamlessly integrated with protein interactions and cell-cycle abundance profiles. When evaluating the prediction accuracy of our method, PhosphoPICK, on an independent hold-out set of kinase-specific phosphorylation sites, we found it achieved an average specificity of 97% while correctly predicting 32% of true positives. We also compared PhosphoPICK’s ability, through cross-validation, to predict kinase-specific phosphorylation sites with alternative methods, and found that at high levels of specificity PhosphoPICK outperforms alternative methods for most comparisons made.We investigated the relationship between experimentally confirmed phosphorylation sites and predicted nuclear localisation signals by predicting the most likely kinases to be regulating the phosphorylated residues immediately upstream or downstream from the localisation signal. We show that kinases PKA, Akt1 and AurB have an over-representation of predicted binding sites at particular positions downstream from predicted nuclear localisation signals, demonstrating an important role for these kinases in regulating the nuclear import of proteins.PhosphoPICK is freely available online as a web-service at http://bioinf.scmb.uq.edu.au/phosphopick.

The Phosphorylated Estrogen Receptor α (ER) Cistrome Identifies a Subset of Active Enhancers Enriched for Direct ER-DNA Binding and the Transcription Factor GRHL2

Molecular and Cellular Biology ◽

10.1128/mcb.00417-18 ◽

2018 ◽

Vol 39 (3) ◽

Cited By ~ 5

Author(s):

Kyle T. Helzer ◽

Mary Szatkowski Ozers ◽

Mark B. Meyer ◽

Nancy A. Benkusky ◽

Natalia Solodin ◽

...

Keyword(s):

Estrogen Receptor ◽

Transcription Factor ◽

Dna Binding ◽

Protein Interactions ◽

Posttranslational Modifications ◽

Binding Sites ◽

Protein Function ◽

Estrogen Receptor Α ◽

Binding Activity

ABSTRACT Posttranslational modifications are key regulators of protein function, providing cues that can alter protein interactions and cellular location. Phosphorylation of estrogen receptor α (ER) at serine 118 (pS118-ER) occurs in response to multiple stimuli and is involved in modulating ER-dependent gene transcription. While the cistrome of ER is well established, surprisingly little is understood about how phosphorylation impacts ER-DNA binding activity. To define the pS118-ER cistrome, chromatin immunoprecipitation sequencing was performed on pS118-ER and ER in MCF-7 cells treated with estrogen. pS118-ER occupied a subset of ER binding sites which were associated with an active enhancer mark, acetylated H3K27. Unlike ER, pS118-ER sites were enriched in GRHL2 DNA binding motifs, and estrogen treatment increased GRHL2 recruitment to sites occupied by pS118-ER. Additionally, pS118-ER occupancy sites showed greater enrichment of full-length estrogen response elements relative to ER sites. In an in vitro DNA binding array of genomic binding sites, pS118-ER was more commonly associated with direct DNA binding events than indirect binding events. These results indicate that phosphorylation of ER at serine 118 promotes direct DNA binding at active enhancers and is a distinguishing mark for associated transcription factor complexes on chromatin.

iProteinDB: an integrative database of Drosophila post-translational modifications

10.1101/386268 ◽

2018 ◽

Cited By ~ 2

Author(s):

Yanhui Hu ◽

Richelle Sopko ◽

Verena Chung ◽

Romain A. Studer ◽

Sean D. Landry ◽

...

Keyword(s):

Protein Interactions ◽

Protein Function ◽

Large Scale ◽

Model Organisms ◽

General Strategy ◽

Post Translational Modification ◽

Post Translational Modifications ◽

Functional Sites ◽

Evolutionarily Conserved ◽

And Function

AbstractPost-translational modification (PTM) serves as a regulatory mechanism for protein function, influencing stability, protein interactions, activity and localization, and is critical in many signaling pathways. The best characterized PTM is phosphorylation, whereby a phosphate is added to an acceptor residue, commonly serine, threonine and tyrosine. As proteins are often phosphorylated at multiple sites, identifying those sites that are important for function is a challenging problem. Considering that many phosphorylation sites may be non-functional, prioritizing evolutionarily conserved phosphosites provides a general strategy to identify the putative functional sites with regards to regulation and function. To facilitate the identification of conserved phosphosites, we generated a large-scale phosphoproteomics dataset from Drosophila embryos collected from six closely-related species. We built iProteinDB (https://www.flyrnai.org/tools/iproteindb/), a resource integrating these data with other high-throughput PTM datasets, including vertebrates, and manually curated information for Drosophila. At iProteinDB, scientists can view the PTM landscape for any Drosophila protein and identify predicted functional phosphosites based on a comparative analysis of data from closely-related Drosophila species. Further, iProteinDB enables comparison of PTM data from Drosophila to that of orthologous proteins from other model organisms, including human, mouse, rat, Xenopus laevis, Danio rerio, and Caenorhabditis elegans.

Evolution of Sequence-based Bioinformatics Tools for Protein-protein Interaction Prediction

Current Genomics ◽

10.2174/1389202921999200625103936 ◽

2020 ◽

Vol 21 (6) ◽

pp. 454-463 ◽

Cited By ~ 1

Author(s):

Mst. Shamima Khatun ◽

Watshara Shoombuatong ◽

Md. Mehedi Hasan ◽

Hiroyuki Kurata

Keyword(s):

Protein Interactions ◽

Protein Function ◽

Disease Incidence ◽

Computational Prediction ◽

Future Perspective ◽

Protein Protein Interactions ◽

Protein Protein Interaction ◽

High Throughput Technology ◽

Protein Interaction Prediction ◽

Therapy Design

Protein-protein interactions (PPIs) are the physical connections between two or more proteins via electrostatic forces or hydrophobic effects. Identification of the PPIs is pivotal, which contributes to many biological processes including protein function, disease incidence, and therapy design. The experimental identification of PPIs via high-throughput technology is time-consuming and expensive. Bioinformatics approaches are expected to solve such restrictions. In this review, our main goal is to provide an inclusive view of the existing sequence-based computational prediction of PPIs. Initially, we briefly introduce the currently available PPI databases and then review the state-of-the-art bioinformatics approaches, working principles, and their performances. Finally, we discuss the caveats and future perspective of the next generation algorithms for the prediction of PPIs.

SUMO in the mammalian response to DNA damage

Biochemical Society Transactions ◽

10.1042/bst0380092 ◽

2010 ◽

Vol 38 (1) ◽

pp. 92-97 ◽

Cited By ~ 19

Author(s):

Joanna R. Morris

Keyword(s):

Dna Damage ◽

Protein Interactions ◽

Protein Function ◽

Mammalian Cells ◽

Cancer Susceptibility ◽

Susceptibility Gene ◽

Genotoxic Stress ◽

Breast Cancer Susceptibility ◽

Model Organisms ◽

Breast Cancer Susceptibility Gene

Modification by SUMOs (small ubiquitin-related modifiers) is largely transient and considered to alter protein function through altered protein–protein interactions. These modifications are significant regulators of the response to DNA damage in eukaryotic model organisms and SUMOylation affects a large number of proteins in mammalian cells, including several proteins involved in the response to genomic lesions [Golebiowski, Matic, Tatham, Cole, Yin, Nakamura, Cox, Barton, Mann and Hay (2009) Sci. Signaling 2, ra24]. Furthermore, recent work [Morris, Boutell, Keppler, Densham, Weekes, Alamshah, Butler, Galanty, Pangon, Kiuchi, Ng and Solomon (2009) Nature 462, 886–890; Galanty, Belotserkovskaya, Coates, Polo, Miller and Jackson (2009) Nature 462, 935–939] has revealed the involvement of the SUMO cascade in the BRCA1 (breast-cancer susceptibility gene 1) pathway response after DNA damage. The present review examines roles described for the SUMO pathway in the way mammalian cells respond to genotoxic stress.

A reference map of the human protein interactome

10.1101/605451 ◽

2019 ◽

Cited By ~ 10

Author(s):

Katja Luck ◽

Dae-Kyum Kim ◽

Luke Lambourne ◽

Kerstin Spirohn ◽

Bridget E. Begg ◽

...

Keyword(s):

Protein Interactions ◽

Protein Function ◽

Molecular Mechanisms ◽

Human Genetics ◽

Genomic Variation ◽

Small Scale ◽

Human Interactome ◽

Tissue Specific ◽

Cellular Context ◽

Reference Map

AbstractGlobal insights into cellular organization and function require comprehensive understanding of interactome networks. Similar to how a reference genome sequence revolutionized human genetics, a reference map of the human interactome network is critical to fully understand genotype-phenotype relationships. Here we present the first human “all-by-all” binary reference interactome map, or “HuRI”. With ~53,000 high-quality protein-protein interactions (PPIs), HuRI is approximately four times larger than the information curated from small-scale studies available in the literature. Integrating HuRI with genome, transcriptome and proteome data enables the study of cellular function within essentially any physiological or pathological cellular context. We demonstrate the use of HuRI in identifying specific subcellular roles of PPIs and protein function modulation via splicing during brain development. Inferred tissue-specific networks reveal general principles for the formation of cellular context-specific functions and elucidate potential molecular mechanisms underlying tissue-specific phenotypes of Mendelian diseases. HuRI thus represents an unprecedented, systematic reference linking genomic variation to phenotypic outcomes.

A Network of Phosphatidylinositol 4,5-bisphosphate Binding Sites Regulate Gating of the Ca2+-activated Cl− Channel ANO1 (TMEM16A)

10.1101/625897 ◽

2019 ◽

Cited By ~ 1

Author(s):

Kuai Yu ◽

Tao Jiang ◽

YuanYuan Cui ◽

Emad Tajkhorshid ◽

H. Criss Hartzell

Keyword(s):

Molecular Dynamics ◽

Protein Interactions ◽

Binding Sites ◽

Protein Function ◽

Computational Study ◽

Channel Gating ◽

Fluid Secretion ◽

Hydroxyl Groups ◽

Binding Modes ◽

Cytoplasmic Extension

AbstractANO1 (TMEM16A) is a Ca2+-activated Cl− channel that regulates diverse cellular functions including fluid secretion, neuronal excitability, and smooth muscle contraction. ANO1 is activated by elevation of cytosolic Ca2+ and modulated by phosphatidylinositol 4,5-bisphosphate (PI(4,5)P2). Here we describe a closely concerted experimental and computational study, including electrophysiology, mutagenesis, functional assays, and extended sampling of lipid-protein interactions with molecular dynamics (MD) to characterize PI(4,5)P2 binding modes and sites on ANO1. ANO1 currents in excised inside-out patches activated by 270 nM Ca2+ at +100 mV are increased by exogenous PI(4,5)P2 with an EC50 = 1.24 µM. The effect of PI(4,5)P2 is dependent on membrane voltage and Ca2+ and is explained by a stabilization of the ANO1 Ca2+-bound open state. Unbiased atomistic MD simulations with 1.4 mol% PI(4,5)P2 in a phosphatidylcholine bilayer identified 8 binding sites with significant probability of binding PI(4,5)P2. Three of these sites captured 85% of all ANO1 - PI(4,5)P2 interactions. Mutagenesis of basic amino acids near the membrane-cytosol interface found three regions of ANO1 critical for PI(4,5)P2 regulation that correspond to the same three sites identified by MD. PI(4,5)P2 is stabilized by hydrogen bonding between amino acid sidechains and phosphate/hydroxyl groups on PI(4,5)P2. Binding of PI(4,5)P2 alters the position of the cytoplasmic extension of TM6, which plays a crucial role in ANO1 channel gating, and increases the accessibility of the inner vestibule to Cl−ions. We propose a model consisting of a network of three PI(4,5)P2 binding sites at the cytoplasmic face of the membrane allosterically regulating ANO1 channel gating.Significance statementMembrane proteins dwell in a sea of phospholipids that not only structurally stabilize the proteins by providing a hydrophobic environment for their transmembrane segments, but also dynamically regulate protein function. While many cation channels are known to be regulated by phosphatidylinositol 4,5-bisphosphate (PI(4,5)P2), relatively little is known about anion channel regulation by phosphoinositides. Using a combination of patch clamp electrophysiology and atomistic molecular dynamics simulations, we have identified several PI(4,5)P2 binding sites in ANO1 (TMEM16A), a Cl− channel that performs myriad physiological functions from epithelial fluid secretion to regulation of electrical excitability. These binding sites form a band at the cytosolic interface of the membrane that we propose constitute a network to dynamically regulate this highly allosteric protein.

Census of halide-binding sites in protein structures

Bioinformatics ◽

10.1093/bioinformatics/btaa079 ◽

2020 ◽

Vol 36 (10) ◽

pp. 3064-3071

Author(s):

Rostislav K Skitchenko ◽

Dmitrii Usoltsev ◽

Mayya Uspenskaya ◽

Andrey V Kajava ◽

Albert Guskov

Keyword(s):

Protein Interactions ◽

Binding Sites ◽

Protein Function ◽

Protein Structures ◽

Data Bank ◽

Supplementary Information ◽

Supplementary Data ◽

Coordination Numbers ◽

Charged Ions ◽

Ubiquitous Presence

Abstract Motivation Halides are negatively charged ions of halogens, forming fluorides (F−), chlorides (Cl−), bromides (Br−) and iodides (I−). These anions are quite reactive and interact both specifically and non-specifically with proteins. Despite their ubiquitous presence and important roles in protein function, little is known about the preferences of halides binding to proteins. To address this problem, we performed the analysis of halide–protein interactions, based on the entries in the Protein Data Bank. Results We have compiled a pipeline for the quick analysis of halide-binding sites in proteins using the available software. Our analysis revealed that all of halides are strongly attracted by the guanidinium moiety of arginine side chains, however, there are also certain preferences among halides for other partners. Furthermore, there is a certain preference for coordination numbers in the binding sites, with a correlation between coordination numbers and amino acid composition. This pipeline can be used as a tool for the analysis of specific halide–protein interactions and assist phasing experiments relying on halides as anomalous scatters. Availability and implementation All data described in this article can be reproduced via complied pipeline published at https://github.com/rostkick/Halide_sites/blob/master/README.md. Supplementary information Supplementary data are available at Bioinformatics online.

Covalent-Fragment Screening of Brd4 Identifies a Ligandable Site Orthogonal to the Acetyl-Lysine Binding Sites

10.26434/chemrxiv.8859098 ◽

2019 ◽

Author(s):

Michael Olp ◽

Daniel Sprague ◽

Stefan Kathman ◽

Ziyang Xu ◽

Alexandar Statsyuk ◽

...

Keyword(s):

Mass Spectrometry ◽

Binding Site ◽

Binding Sites ◽

Computational Prediction ◽

Chemical Probes ◽

Computational Docking ◽

Fragment Screening ◽

Covalent Inhibitors ◽

Bet Protein ◽

Proof Of Principle

<p>Brd4, a member of the bromodomain and extraterminal domain (BET) family, has emerged as a promising epigenetic target in cancer and inflammatory disorders. All reported BET family ligands bind within the bromodomain acetyl-lysine binding sites and competitively inhibit BET protein interaction with acetylated chromatin. Alternative chemical probes that act orthogonally to the highly-conserved acetyl-lysine binding sites may exhibit selectivity within the BET family and avoid recently reported toxicity in clinical trials of BET bromodomain inhibitors. Here, we report the first identification of a ligandable site on a bromodomain outside the acetyl-lysine binding site. Inspired by our computational prediction of hotspots adjacent to non-homologous cysteine residues within the <i>C</i>-terminal Brd4 bromodomain (Brd4-BD2), we performed a mid-throughput mass spectrometry screen to identify cysteine-reactive fragments that covalently and selectively modify Brd4. Subsequent mass spectrometry, NMR and computational docking analyses of electrophilic fragment hits revealed a novel ligandable site near Cys356 that is unique to Brd4 among all human bromodomains. This site is orthogonal to the Brd4-BD2 acetyl-lysine binding site as Cys356 modification did not impact binding of the pan-BET bromodomain inhibitor JQ1 in fluorescence polarization assays. Finally, we tethered covalent fragments to JQ1 and performed NanoBRET assays to provide proof of principle that this orthogonal site can be covalently targeted in intact human cells. Overall, we demonstrate the potential of targeting sites orthogonal to bromodomain acetyl-lysine binding sites to develop bivalent and covalent inhibitors that displace Brd4 from chromatin.</p>

Recent Advances on the Semi-Supervised Learning for Long Non-Coding RNA-Protein Interactions Prediction: A Review

Protein and Peptide Letters ◽

10.2174/0929866526666191025104043 ◽

2020 ◽

Vol 27 (5) ◽

pp. 385-391

Author(s):

Lin Zhong ◽

Zhong Ming ◽

Guobo Xie ◽

Chunlong Fan ◽

Xue Piao

Keyword(s):

Supervised Learning ◽

Protein Interactions ◽

Computational Models ◽

Prediction Models ◽

Chromatin Modification ◽

Computational Prediction ◽

Human Diseases ◽

Future Research ◽

Non Coding Rna ◽

Long Non Coding Rna

: In recent years, more and more evidence indicates that long non-coding RNA (lncRNA) plays a significant role in the development of complex biological processes, especially in RNA progressing, chromatin modification, and cell differentiation, as well as many other processes. Surprisingly, lncRNA has an inseparable relationship with human diseases such as cancer. Therefore, only by knowing more about the function of lncRNA can we better solve the problems of human diseases. However, lncRNAs need to bind to proteins to perform their biomedical functions. So we can reveal the lncRNA function by studying the relationship between lncRNA and protein. But due to the limitations of traditional experiments, researchers often use computational prediction models to predict lncRNA protein interactions. In this review, we summarize several computational models of the lncRNA protein interactions prediction base on semi-supervised learning during the past two years, and introduce their advantages and shortcomings briefly. Finally, the future research directions of lncRNA protein interaction prediction are pointed out.

The SNPs within 3'UTR of miRNA Target Genes Related to Multiple Sclerosis: A Computational Prediction

Current Pharmacogenomics and Personalized Medicine ◽

10.2174/1875692118666200316130727 ◽

2020 ◽

Vol 17 (2) ◽

pp. 133-147

Author(s):

Mina Zafarpiran ◽

Roya Sharifi ◽

Zeinab Shirvani-Farsani

Keyword(s):

Multiple Sclerosis ◽

Gene Regulation ◽

Binding Sites ◽

Target Genes ◽

Demyelinating Disease ◽

Target Prediction ◽

Computational Prediction ◽

Functional Verification ◽

Candidate Snps ◽

Inflammatory Genes

Background: Multiple Sclerosis (MS) is an inflammatory and demyelinating disease of the central nervous system, and genetic factors play an important role in its susceptibility. The expressions of many inflammatory genes implicated in MS are regulated by microRNA (miRNAs), whose function is to suppress the translation by pairing with miRNA Recognition Elements (MREs) present in the 3' untranslated region (3'UTR) of target mRNA. Recently, it has been shown that the Single Nucleotide Polymorphism (SNPs) present within the 3'UTR of mRNAs can affect the miRNA-mediated gene regulation and susceptibility to a variety of human diseases. Objective: The aim of this study was to analyze the SNPs within the 3'UTR of miRNA inflammatory target genes related to multiple sclerosis. Methods: By DisGeNET, dbGaP, Ovid, DAVID, Web of knowledge, and SNPs databases, 3'UTR genetic variants were identified in all inflammatory genes associated with MS. Also, miRNA's target prediction databases were used for predicting the miRNA binding sites. Results: We identified 125 SNPs with MAF>0.05 located in the binding site of the miRNA of 35 genes among 59 inflammatory genes related to MS. Bioinformatics analysis predicted 62 MRE-modulating SNPs and 59 MRE-creating SNPs in the 3'UTR of MSimplicated inflammatory genes. These candidate SNPs within miRNA binding sites of inflammatory genes can alter the miRNAs binding, and consequently lead to the mRNA gene regulation. Conclusion: Therefore, these miRNA and MRE-SNPs may play important roles in personalized medicine of MS, and hence, they would be valuable for further functional verification investigations.