scholarly journals Chemical toolbox for ‘live’ biochemistry to understand enzymatic functions in living systems

2019 ◽  
Author(s):  
Toru Komatsu ◽  
Yasuteru Urano
Keyword(s):  
Environmental Factors ◽  
Protein Interactions ◽  
Posttranslational Modifications ◽  
Live Cell ◽  
Living Systems ◽  
Protein Protein Interactions ◽  
Redox States ◽  
Recent Advances ◽  
Protein Functions ◽  
Research Tools

Abstract In this review, we present an overview of the recent advances in chemical toolboxes that are used to provide insights into ‘live’ protein functions in living systems. Protein functions are mediated by various factors inside of cells, such as protein−protein interactions, posttranslational modifications, and they are also subject to environmental factors such as pH, redox states and crowding conditions. Obtaining a true understanding of protein functions in living systems is therefore a considerably difficult task. Recent advances in research tools have allowed us to consider ‘live’ biochemistry as a valid approach to precisely understand how proteins function in a live cell context.

scholarly journals Deciphering and engineering chromodomain-methyllysine peptide recognition

2018 ◽  
Vol 4 (11) ◽  
pp. eaau1447 ◽  
Author(s):  
Ryan Hard ◽  
Nan Li ◽  
Wei He ◽  
Brian Ross ◽  
Gary C. H. Mo ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Posttranslational Modifications ◽  
Large Scale ◽  
Regulation Of Gene Expression ◽  
Live Cells ◽  
Lysine Methylation ◽  
Dynamic Regulation ◽  
Peptide Recognition ◽  
Protein Functions ◽  
Domain Peptide

Posttranslational modifications (PTMs) play critical roles in regulating protein functions and mediating protein-protein interactions. An important PTM is lysine methylation that orchestrates chromatin modifications and regulates functions of non-histone proteins. Methyllysine peptides are bound by modular domains, of which chromodomains are representative. Here, we conducted the first large-scale study of chromodomains in the human proteome interacting with both histone and non-histone methyllysine peptides. We observed significant degenerate binding between chromodomains and histone peptides, i.e., different histone sites can be recognized by the same set of chromodomains, and different chromodomains can share similar binding profiles to individual histone sites. Such degenerate binding is not dictated by amino acid sequence or PTM motif but rather rooted in the physiochemical properties defined by the PTMs on the histone peptides. This molecular mechanism is confirmed by the accurate prediction of the binding specificity using a computational model that captures the structural and energetic patterns of the domain-peptide interaction. To further illustrate the power and accuracy of our model, we used it to effectively engineer an exceptionally strong H3K9me3-binding chromodomain and to label H3K9me3 in live cells. This study presents a systematic approach to deciphering domain-peptide recognition and reveals a general principle by which histone modifications are interpreted by reader proteins, leading to dynamic regulation of gene expression and other biological processes.

scholarly journals The Role of Posttranslational Modifications in DNA Repair

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Miaomiao Bai ◽  
Dongdong Ti ◽  
Qian Mei ◽  
Jiejie Liu ◽  
Xin Yan ◽  
...  
Keyword(s):  
Dna Damage ◽  
Dna Repair ◽  
Protein Interactions ◽  
Posttranslational Modifications ◽  
Genome Stability ◽  
Protein Localization ◽  
Complex Structure ◽  
Protein Protein Interactions ◽  
Regulate Protein

The human body is a complex structure of cells, which are exposed to many types of stress. Cells must utilize various mechanisms to protect their DNA from damage caused by metabolic and external sources to maintain genomic integrity and homeostasis and to prevent the development of cancer. DNA damage inevitably occurs regardless of physiological or abnormal conditions. In response to DNA damage, signaling pathways are activated to repair the damaged DNA or to induce cell apoptosis. During the process, posttranslational modifications (PTMs) can be used to modulate enzymatic activities and regulate protein stability, protein localization, and protein-protein interactions. Thus, PTMs in DNA repair should be studied. In this review, we will focus on the current understanding of the phosphorylation, poly(ADP-ribosyl)ation, ubiquitination, SUMOylation, acetylation, and methylation of six typical PTMs and summarize PTMs of the key proteins in DNA repair, providing important insight into the role of PTMs in the maintenance of genome stability and contributing to reveal new and selective therapeutic approaches to target cancers.

scholarly journals Intrinsic Disorder in Tetratricopeptide Repeat Proteins

2020 ◽  
Vol 21 (10) ◽  
pp. 3709 ◽  
Author(s):  
Nathan W. Van Bibber ◽  
Cornelia Haerle ◽  
Roy Khalife ◽  
Bin Xue ◽  
Vladimir N. Uversky
Keyword(s):  
Protein Interactions ◽  
Posttranslational Modifications ◽  
Tandem Repeats ◽  
Intrinsically Disordered Protein ◽  
Intrinsic Disorder ◽  
Protein Protein Interactions ◽  
Systematic Analysis ◽  
Tetratricopeptide Repeats ◽  
Intrinsically Disordered ◽  
Tetratricopeptide Repeat Proteins

Among the realm of repeat containing proteins that commonly serve as “scaffolds” promoting protein-protein interactions, there is a family of proteins containing between 2 and 20 tetratricopeptide repeats (TPRs), which are functional motifs consisting of 34 amino acids. The most distinguishing feature of TPR domains is their ability to stack continuously one upon the other, with these stacked repeats being able to affect interaction with binding partners either sequentially or in combination. It is known that many repeat-containing proteins are characterized by high levels of intrinsic disorder, and that many protein tandem repeats can be intrinsically disordered. Furthermore, it seems that TPR-containing proteins share many characteristics with hybrid proteins containing ordered domains and intrinsically disordered protein regions. However, there has not been a systematic analysis of the intrinsic disorder status of TPR proteins. To fill this gap, we analyzed 166 human TPR proteins to determine the degree to which proteins containing TPR motifs are affected by intrinsic disorder. Our analysis revealed that these proteins are characterized by different levels of intrinsic disorder and contain functional disordered regions that are utilized for protein-protein interactions and often serve as targets of various posttranslational modifications.

In Silico Recognition of Protein-Protein Interaction

2011 ◽  
pp. 248-268
Author(s):  
Byung-Hoon Park ◽  
Phuongan Dam ◽  
Chongle Pan ◽  
Ying Xu ◽  
Al Geist ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Regulatory Networks ◽  
Machine Learning Techniques ◽  
Translation Regulation ◽  
Future Research ◽  
Protein Protein Interactions ◽  
Protein Protein Interaction ◽  
Protein Levels ◽  
Protein Functions ◽  
Model Protein

Protein-protein interactions are fundamental to cellular processes. They are responsible for phenomena like DNA replication, gene transcription, protein translation, regulation of metabolic pathways, immunologic recognition, signal transduction, etc. The identification of interacting proteins is therefore an important prerequisite step in understanding their physiological functions. Due to the invaluable importance to various biophysical activities, reliable computational methods to infer protein-protein interactions from either structural or genome sequences are in heavy demand lately. Successful predictions, for instance, will facilitate a drug design process and the reconstruction of metabolic or regulatory networks. In this chapter, we review: (a) high-throughput experimental methods for identification of protein-protein interactions, (b) existing databases of protein-protein interactions, (c) computational approaches to predicting protein-protein interactions at both residue and protein levels, (d) various statistical and machine learning techniques to model protein-protein interactions, and (e) applications of protein-protein interactions in predicting protein functions. We also discuss intrinsic drawbacks of the existing approaches and future research directions.

scholarly journals PathwayMatcher: proteoform-centric network construction enables fine-granularity multiomics pathway mapping

GigaScience ◽  
2019 ◽  
Vol 8 (8) ◽  
Author(s):  
Luis Francisco Hernández Sánchez ◽  
Bram Burger ◽  
Carlos Horro ◽  
Antonio Fabregat ◽  
Stefan Johansson ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Posttranslational Modifications ◽  
Knowledge Bases ◽  
Protein Isoforms ◽  
Biomedical Data ◽  
Protein Protein Interactions ◽  
Gene Sets ◽  
Functional Knowledge ◽  
Pathway Analyses ◽  
Different Levels

Abstract Background Mapping biomedical data to functional knowledge is an essential task in bioinformatics and can be achieved by querying identifiers (e.g., gene sets) in pathway knowledge bases. However, the isoform and posttranslational modification states of proteins are lost when converting input and pathways into gene-centric lists. Findings Based on the Reactome knowledge base, we built a network of protein-protein interactions accounting for the documented isoform and modification statuses of proteins. We then implemented a command line application called PathwayMatcher (github.com/PathwayAnalysisPlatform/PathwayMatcher) to query this network. PathwayMatcher supports multiple types of omics data as input and outputs the possibly affected biochemical reactions, subnetworks, and pathways. Conclusions PathwayMatcher enables refining the network representation of pathways by including proteoforms defined as protein isoforms with posttranslational modifications. The specificity of pathway analyses is hence adapted to different levels of granularity, and it becomes possible to distinguish interactions between different forms of the same protein.

scholarly journals Distinct p53 acetylation cassettes differentially influence gene-expression patterns and cell fate

2006 ◽  
Vol 173 (4) ◽  
pp. 533-544 ◽  
Author(s):  
Chad D. Knights ◽  
Jason Catania ◽  
Simone Di Giovanni ◽  
Selen Muratoglu ◽  
Ricardo Perez ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Fate ◽  
Protein Interactions ◽  
Posttranslational Modifications ◽  
Biological Activities ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
P53 Gene ◽  
Protein Protein Interactions

The activity of the p53 gene product is regulated by a plethora of posttranslational modifications. An open question is whether such posttranslational changes act redundantly or dependently upon one another. We show that a functional interference between specific acetylated and phosphorylated residues of p53 influences cell fate. Acetylation of lysine 320 (K320) prevents phosphorylation of crucial serines in the NH2-terminal region of p53; only allows activation of genes containing high-affinity p53 binding sites, such as p21/WAF; and promotes cell survival after DNA damage. In contrast, acetylation of K373 leads to hyperphosphorylation of p53 NH2-terminal residues and enhances the interaction with promoters for which p53 possesses low DNA binding affinity, such as those contained in proapoptotic genes, leading to cell death. Further, acetylation of each of these two lysine clusters differentially regulates the interaction of p53 with coactivators and corepressors and produces distinct gene-expression profiles. By analogy with the “histone code” hypothesis, we propose that the multiple biological activities of p53 are orchestrated and deciphered by different “p53 cassettes,” each containing combination patterns of posttranslational modifications and protein–protein interactions.

New advances in extracting and learning from protein–protein interactions within unstructured biomedical text data

2019 ◽  
Vol 3 (4) ◽  
pp. 357-369
Author(s):  
J. Harry Caufield ◽  
Peipei Ping
Keyword(s):  
Protein Interactions ◽  
Protein Function ◽  
Historical Context ◽  
Specific Protein ◽  
Basic Unit ◽  
Biomedical Text ◽  
Protein Protein Interactions ◽  
Text Data ◽  
Ppi Networks ◽  
Protein Functions

Abstract Protein–protein interactions, or PPIs, constitute a basic unit of our understanding of protein function. Though substantial effort has been made to organize PPI knowledge into structured databases, maintenance of these resources requires careful manual curation. Even then, many PPIs remain uncurated within unstructured text data. Extracting PPIs from experimental research supports assembly of PPI networks and highlights relationships crucial to elucidating protein functions. Isolating specific protein–protein relationships from numerous documents is technically demanding by both manual and automated means. Recent advances in the design of these methods have leveraged emerging computational developments and have demonstrated impressive results on test datasets. In this review, we discuss recent developments in PPI extraction from unstructured biomedical text. We explore the historical context of these developments, recent strategies for integrating and comparing PPI data, and their application to advancing the understanding of protein function. Finally, we describe the challenges facing the application of PPI mining to the text concerning protein families, using the multifunctional 14-3-3 protein family as an example.

Quantitative Imaging of FRET-Based Biosensors for Cell- and Organelle-Specific Analyses in Plants

2016 ◽  
Vol 22 (2) ◽  
pp. 300-310 ◽  
Author(s):  
Swayoma Banerjee ◽  
Luis Rene Garcia ◽  
Wayne K. Versaw
Keyword(s):  
High Precision ◽  
Protein Interactions ◽  
Posttranslational Modifications ◽  
Dynamic Range ◽  
Quantitative Imaging ◽  
Resonance Energy Transfer ◽  
Resonance Energy ◽  
High Dynamic Range ◽  
Imaging Data ◽  
Protein Protein Interactions

AbstractGenetically encoded Förster resonance energy transfer (FRET)-based biosensors have been used to report relative concentrations of ions and small molecules, as well as changes in protein conformation, posttranslational modifications, and protein–protein interactions. Changes in FRET are typically quantified through ratiometric analysis of fluorescence intensities. Here we describe methods to evaluate ratiometric imaging data acquired through confocal microscopy of a FRET-based inorganic phosphate biosensor in different cells and subcellular compartments of Arabidopsis thaliana. Linear regression was applied to donor, acceptor, and FRET-derived acceptor fluorescence intensities obtained from images of multiple plants to estimate FRET ratios and associated location-specific spectral correction factors with high precision. FRET/donor ratios provided a combination of high dynamic range and precision for this biosensor when applied to the cytosol of both root and leaf cells, but lower precision when this ratiometric method was applied to chloroplasts. We attribute this effect to quenching of donor fluorescence because high precision was achieved with FRET/acceptor ratios and thus is the preferred ratiometric method for this organelle. A ligand-insensitive biosensor was also used to distinguish nonspecific changes in FRET ratios. These studies provide a useful guide for conducting quantitative ratiometric studies in live plants that is applicable to any FRET-based biosensor.

Applications of Mass Spectrometry in Proteomics

2013 ◽  
Vol 66 (7) ◽  
pp. 721 ◽  
Author(s):  
Izabela Sokolowska ◽  
Armand G. Ngounou Wetie ◽  
Alisa G. Woods ◽  
Costel C. Darie
Keyword(s):  
Mass Spectrometry ◽  
Protein Interactions ◽  
Protein Identification ◽  
Protein Protein Interactions ◽  
Post Translational Modification ◽  
Cellular Processes ◽  
Physiological Processes ◽  
Protein Functions ◽  
Instruments And Techniques ◽  
Accurate Mass Spectrometry

Characterisation of proteins and whole proteomes can provide a foundation to our understanding of physiological and pathological states and biological diseases or disorders. Constant development of more reliable and accurate mass spectrometry (MS) instruments and techniques has allowed for better identification and quantification of the thousands of proteins involved in basic physiological processes. Therefore, MS-based proteomics has been widely applied to the analysis of biological samples and has greatly contributed to our understanding of protein functions, interactions, and dynamics, advancing our knowledge of cellular processes as well as the physiology and pathology of the human body. This review will discuss current proteomic approaches for protein identification and characterisation, including post-translational modification (PTM) analysis and quantitative proteomics as well as investigation of protein–protein interactions (PPIs).

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