scholarly journals Protein covariance networks reveal interactions important to the emergence of SARS coronaviruses as human pathogens

2020 ◽  
Author(s):  
William P. Robins ◽  
John J. Mekalanos
Keyword(s):  
Protein Interactions ◽  
Viral Evolution ◽  
Amino Acid Residues ◽  
Human Pathogen ◽  
Human Pathogens ◽  
Protein Protein Interactions ◽  
High Frequencies ◽  
Adaptive Mutations ◽  
Phylogeny Analysis ◽  
Animal Reservoirs

AbstractSARS-CoV-2 is one of three recognized coronaviruses (CoVs) that have caused epidemics or pandemics in the 21st century and that have likely emerged from animal reservoirs based on genomic similarities to bat and other animal viruses. Here we report the analysis of conserved interactions between amino acid residues in proteins encoded by SARS-CoV-related viruses. We identified pairs and networks of residue variants that exhibited statistically high frequencies of covariance with each other. While these interactions are likely key to both protein structure and other protein-protein interactions, we have also found that they can be used to provide a new computational approach (CoVariance-based Phylogeny Analysis) for understanding viral evolution and adaptation. Our data provide evidence that the evolutionary processes that converted a bat virus into human pathogen occurred through recombination with other viruses in combination with new adaptive mutations important for entry into human cells.

scholarly journals Covariance predicts conserved protein residue interactions important to the emergence and continued evolution of SARS-CoV-2 as a human pathogen

2022 ◽  
Author(s):  
William P Robins ◽  
John J Mekalanos
Keyword(s):  
Amino Acid ◽  
Amino Acid Residues ◽  
Human Pathogens ◽  
High Frequencies ◽  
Sequence Composition ◽  
Core Proteins ◽  
Lower Case ◽  
Animal Reservoirs ◽  
Independent Pair ◽  
Model Approach

SARS-CoV-2 is one of three recognized coronaviruses (CoVs) that have caused epidemics or pandemics in the 21st century and that likely emerged from animal reservoirs. Differences in nucleotide and protein sequence composition within related lower case Greek beta-coronaviruses are often used to better understand CoV evolution, host adaptation, and their emergence as human pathogens. Here we report the comprehensive analysis of amino acid residue changes that have occurred in lineage B lower case Greek betacoronaviruses (sarbecoviruses) that show covariance with each other. This analysis revealed patterns of covariance within conserved viral proteins that potentially define conserved interactions within and between core proteins encoded by SARS-CoV-2 related lower case Greek beta-coranaviruses. We identified not only individual pairs but also networks of amino acid residues that exhibited statistically high frequencies of covariance with each other using an independent pair model followed by a tandem model approach. Using 149 different CoV genomes that vary in their relatedness, we identified networks of unique combinations of alleles that can be incrementally traced genome by genome within different phylogenic lineages. Remarkably, covariant residues and their respective regions most abundantly represented are implicated in the emergence of SARS-CoV-2 and are also enriched in dominant SARS-CoV-2 variants.

scholarly journals Group I Metabotropic Glutamate Receptors and Interacting Partners: An Update

2022 ◽  
Vol 23 (2) ◽  
pp. 840
Author(s):  
Li-Min Mao ◽  
Alaya Bodepudi ◽  
Xiang-Ping Chu ◽  
John Q. Wang
Keyword(s):  
Synaptic Plasticity ◽  
Protein Interactions ◽  
Metabotropic Glutamate Receptors ◽  
Adaptor Proteins ◽  
Mammalian Brain ◽  
Amino Acid Residues ◽  
Protein Protein Interactions ◽  
Metabotropic Glutamate ◽  
Group I ◽  
Associated Proteins

Group I metabotropic glutamate (mGlu) receptors (mGlu1/5 subtypes) are G protein-coupled receptors and are broadly expressed in the mammalian brain. These receptors play key roles in the modulation of normal glutamatergic transmission and synaptic plasticity, and abnormal mGlu1/5 signaling is linked to the pathogenesis and symptomatology of various mental and neurological disorders. Group I mGlu receptors are noticeably regulated via a mechanism involving dynamic protein–protein interactions. Several synaptic protein kinases were recently found to directly bind to the intracellular domains of mGlu1/5 receptors and phosphorylate the receptors at distinct amino acid residues. A variety of scaffolding and adaptor proteins also interact with mGlu1/5. Constitutive or activity-dependent interactions between mGlu1/5 and their interacting partners modulate trafficking, anchoring, and expression of the receptors. The mGlu1/5-associated proteins also finetune the efficacy of mGlu1/5 postreceptor signaling and mGlu1/5-mediated synaptic plasticity. This review analyzes the data from recent studies and provides an update on the biochemical and physiological properties of a set of proteins or molecules that interact with and thus regulate mGlu1/5 receptors.

scholarly journals Characterization of COMMD protein–protein interactions in NF-κB signalling

2006 ◽  
Vol 398 (1) ◽  
pp. 63-71 ◽  
Author(s):  
Prim de Bie ◽  
Bart van de Sluis ◽  
Ezra Burstein ◽  
Karen J. Duran ◽  
Ruud Berger ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Copper Metabolism ◽  
Nuclear Factor Κb ◽  
Inhibitory Effect ◽  
Protein Family ◽  
Amino Acid Residues ◽  
Protein Protein Interactions ◽  
Necrosis Factor

COMMD [copper metabolism gene MURR1 (mouse U2af1-rs1 region 1) domain] proteins constitute a recently identified family of NF-κB (nuclear factor κB)-inhibiting proteins, characterized by the presence of the COMM domain. In the present paper, we report detailed investigation of the role of this protein family, and specifically the role of the COMM domain, in NF-κB signalling through characterization of protein–protein interactions involving COMMD proteins. The small ubiquitously expressed COMMD6 consists primarily of the COMM domain. Therefore COMMD1 and COMMD6 were analysed further as prototype members of the COMMD protein family. Using specific antisera, interaction between endogenous COMMD1 and COMMD6 is described. This interaction was verified by independent techniques, appeared to be direct and could be detected throughout the whole cell, including the nucleus. Both proteins inhibit TNF (tumour necrosis factor)-induced NF-κB activation in a non-synergistic manner. Mutation of the amino acid residues Trp24 and Pro41 in the COMM domain of COMMD6 completely abolished the inhibitory effect of COMMD6 on TNF-induced NF-κB activation, but this was not accompanied by loss of interaction with COMMD1, COMMD6 or the NF-κB subunit RelA. In contrast with COMMD1, COMMD6 does not bind to IκBα (inhibitory κBα), indicating that both proteins inhibit NF-κB in an overlapping, but not completely similar, manner. Taken together, these data support the significance of COMMD protein–protein interactions and provide new mechanistic insight into the function of this protein family in NF-κB signalling.

Prediction of Protein-Protein Interactions Between Human Host and Two Mycobacterial Organisms

2013 ◽  
pp. 175-187
Author(s):  
Oruganty Krishnadev ◽  
Shveta Bisht ◽  
Narayanaswamy Srinivasan
Keyword(s):  
Protein Interactions ◽  
Serine Proteases ◽  
Cellular Membrane ◽  
Human Pathogens ◽  
Protein Protein Interactions ◽  
Human Host ◽  
Interaction Partners ◽  
Human Proteins ◽  
Mycobacterial Antigens ◽  
Ras Signalling

The genomes of many human pathogens have been sequenced but the protein-protein interactions across a pathogen and human are still poorly understood. The authors apply a simple homology-based method to predict protein-protein interactions between human host and two mycobacterial organisms viz., M.tuberculosis and M.leprae. They focused on secreted proteins of pathogens and cellular membrane proteins to restrict to uncovering biologically significant and feasible interactions. Predicted interactions include five mycobacterial proteins of yet unknown function, thus suggesting a role for these proteins in pathogenesis. The authors predict interaction partners for secreted mycobacterial antigens such as MPT70, serine proteases and other proteins interacting with human proteins, such as toll-like receptors, ras signalling proteins and immune maintenance proteins, that are implicated in pathogenesis. These results suggest that the list of predicted interactions is suitable for further analysis and forms a useful step in the understanding of pathogenesis of these mycobacterial organisms.

scholarly journals A distinct class of plant and animal viral proteins that disrupt mitosis by directly interrupting the mitotic entry switch Wee1-Cdc25-Cdk1

2020 ◽  
Vol 6 (20) ◽  
pp. eaba3418
Author(s):  
Huaibing Jin ◽  
Zhiqiang Du ◽  
Yanjing Zhang ◽  
Judit Antal ◽  
Zongliang Xia ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Viral Proteins ◽  
Plant Viruses ◽  
Amino Acid Residues ◽  
Protein Protein Interactions ◽  
Common Amino Acid ◽  
Mitotic Entry ◽  
Distinct Class ◽  
Barley Yellow Dwarf ◽  
Hiv 1

Many animal viral proteins, e.g., Vpr of HIV-1, disrupt host mitosis by directly interrupting the mitotic entry switch Wee1-Cdc25-Cdk1. However, it is unknown whether plant viruses may use this mechanism in their pathogenesis. Here, we report that the 17K protein, encoded by barley yellow dwarf viruses and related poleroviruses, delays G2/M transition and disrupts mitosis in both host (barley) and nonhost (fission yeast, Arabidopsis thaliana, and tobacco) cells through interrupting the function of Wee1-Cdc25-CDKA/Cdc2 via direct protein-protein interactions and alteration of CDKA/Cdc2 phosphorylation. When ectopically expressed, 17K disrupts the mitosis of cultured human cells, and HIV-1 Vpr inhibits plant cell growth. Furthermore, 17K and Vpr share similar secondary structural feature and common amino acid residues required for interacting with plant CDKA. Thus, our work reveals a distinct class of mitosis regulators that are conserved between plant and animal viruses and play active roles in viral pathogenesis.

Analysis of an engineered plasma kallikrein inhibitor and its effect on contact activation

2010 ◽  
Vol 391 (4) ◽  
Author(s):  
A. Allart Stoop ◽  
Ravi V. Joshi ◽  
Christopher T. Eggers ◽  
Charles S. Craik
Keyword(s):  
Serine Protease ◽  
Protein Interactions ◽  
Phage Library ◽  
Plasma Kallikrein ◽  
Amino Acid Residues ◽  
Protein Protein Interactions ◽  
Contact Activation ◽  
Kallikrein Inhibitor ◽  
Membrane Type ◽  
Opposing Effects

AbstractEngineering of protein-protein interactions is used to enhance the affinity or specificity of proteins, such as antibodies or protease inhibitors, for their targets. However, fully diversifying all residues in a protein-protein interface is often unfeasible. Therefore, we limited our phage library for the serine protease inhibitor ecotin by restricting it to only tetranomial diversity and then targeted all 20 amino acid residues involved in protein recognition. This resulted in a high-affinity and highly specific plasma kallikrein inhibitor, ecotin-Pkal. To validate this approach we dissected the energetic contributions of each wild type (wt) or mutated surface loop to the binding of either plasma kallikrein (PKal) or membrane-type serine protease 1. The analysis demonstrated that a mutation in one loop has opposing effects depending on the sequence of surrounding loops. This finding stresses the cooperative nature of loop-loop interactions and justifies targeting multiple loops with a limited diversity. In contrast to ecotin wt, the specific loop combination of ecotin-Pkal discriminates the subtle structural differences between the active enzymes, PKal and Factor XIIa, and their respective zymogen forms. We used ecotin-Pkal to specifically inhibit contact activation of human plasma at the level mediated by plasma kallikrein.

Cardiac hypertrophy and altered β-adrenergic signaling in transgenic mice that express the amino terminus of β-ARK1

2003 ◽  
Vol 285 (5) ◽  
pp. H2201-H2211 ◽  
Author(s):  
Janelle R. Keys ◽  
Emily A. Greene ◽  
Chris J. Cooper ◽  
Sathyamangla V. Naga Prasad ◽  
Howard A. Rockman ◽  
...  
Keyword(s):  
Transgenic Mice ◽  
Cardiac Hypertrophy ◽  
Protein Interactions ◽  
Amino Terminus ◽  
Amino Acid Residues ◽  
Protein Protein Interactions ◽  
Gpcr Signaling ◽  
Amino Terminal ◽  
G Protein Coupled

The G protein-coupled receptor (GPCR) kinase β-adrenergic receptor (β-AR) kinase-1 (β-ARK1) is elevated during heart failure; however, its role is not fully understood. β-ARK1 contains several domains that are capable of protein-protein interactions that may play critical roles in the regulation of GPCR signaling. In this study, we developed a novel line of transgenic mice that express an amino-terminal peptide of β-ARK1 that is comprised of amino acid residues 50–145 (β-ARKnt) in the heart to determine whether this domain has any functional significance in vivo. Surprisingly, the β-ARKnt transgenic mice presented with cardiac hypertrophy. Our data suggest that the phenotype was driven via an enhanced β-AR system, as β-ARKnt mice had elevated cardiac β-AR density. Moreover, administration of a β-AR antagonist reversed hypertrophy in these mice. Interestingly, signaling through the β-AR in response to agonist stimulation was not enhanced in these mice. Thus the amino terminus of β-ARK1 appears to be critical for normal β-AR regulation in vivo, which further supports the hypothesis that β-ARK1 plays a key role in normal and compromised cardiac GPCR signaling.

scholarly journals Inferring interaction partners from protein sequences using mutual information

2018 ◽  
Author(s):  
Anne-Florence Bitbol
Keyword(s):  
Mutual Information ◽  
Protein Interactions ◽  
Sequence Data ◽  
Protein Complexes ◽  
Three Dimensional ◽  
Specific Protein ◽  
Amino Acid Residues ◽  
Protein Protein Interactions ◽  
Cellular Processes ◽  
Interaction Partners

AbstractSpecific protein-protein interactions are crucial in most cellular processes. They enable multiprotein complexes to assemble and to remain stable, and they allow signal transduction in various pathways. Functional interactions between proteins result in coevolution between the interacting partners, and thus in correlations between their sequences. Pairwise maximum-entropy based models have enabled successful inference of pairs of amino-acid residues that are in contact in the three-dimensional structure of multi-protein complexes, starting from the correlations in the sequence data of known interaction partners. Recently, algorithms inspired by these methods have been developed to identify which proteins are specific interaction partners among the paralogous proteins of two families, starting from sequence data alone. Here, we demonstrate that a slightly higher performance for partner identification can be reached by an approximate maximization of the mutual information between the sequence alignments of the two protein families. This stands in contrast with structure prediction of proteins and of multiprotein complexes from sequence data, where pairwise maximum-entropy based global statistical models substantially improve performance compared to mutual information. Our findings entail that the statistical dependences allowing interaction partner prediction from sequence data are not restricted to the residue pairs that are in direct contact at the interface between the partner proteins.Author summarySpecific protein-protein interactions are at the heart of most intra-cellular processes. Mapping these interactions is thus crucial to a systems-level understanding of cells, and has broad applications to areas such as drug targeting. Systematic experimental identification of protein interaction partners is still challenging. However, a large and rapidly growing amount of sequence data is now available. Recently, algorithms have been proposed to identify which proteins interact from their sequences alone, thanks to the co-variation of the sequences of interacting proteins. These algorithms build upon inference methods that have been used with success to predict the three-dimensional structures of proteins and multi-protein complexes, and their focus is on the amino-acid residues that are in direct contact. Here, we propose a simpler method to identify which proteins interact among the paralogous proteins of two families, starting from their sequences alone. Our method relies on an approximate maximization of mutual information between the sequences of the two families, without specifically emphasizing the contacting residue pairs. We demonstrate that this method slightly outperforms the earlier one. This result highlights that partner prediction does not only rely on the identities and interactions of directly contacting amino-acids.

scholarly journals Sequence conservation, domain architectures, and phylogenetic distribution of the HD-GYP type c-di-GMP phosphodiesterases

2021 ◽  
Author(s):  
Michael Y. Galperin ◽  
Shan-Ho Chou
Keyword(s):  
Protein Interactions ◽  
Regulatory Protein ◽  
Second Messenger ◽  
Distribution Patterns ◽  
Distribution Functions ◽  
Amino Acid Residues ◽  
Sequence Motifs ◽  
Protein Protein Interactions ◽  
Conserved Sequence ◽  
Common Domain

The HD-GYP domain, named after two of its conserved sequence motifs, was first described in 1999 as a specialized version of the widespread HD phosphohydrolase domain that had additional highly conserved amino acid residues. Domain associations of HD-GYP indicated its involvement in bacterial signal transduction and distribution patterns of this domain suggested that it could serve as a hydrolase of the bacterial second messenger c-di-GMP, in addition to or instead of the EAL domain. Subsequent studies confirmed the ability of various HD-GYP domains to hydrolyze c-di-GMP to linear pGpG and/or GMP. Certain HD-GYP-containing proteins hydrolyze another second messenger, cGAMP, and some HD-GYP domains participate in regulatory protein-protein interactions. The recently solved structures of HD-GYP domains from four distinct organisms clarified the mechanisms of c-di-GMP binding and metal-assisted hydrolysis. However, the HD-GYP domain is poorly represented in public domain databases, which causes certain confusion about its phylogenic distribution, functions, and domain architectures. Here, we present a refined sequence model for the HD-GYP domain and describe the roles of its most conserved residues in metal and/or substrate binding. We also calculate the numbers of HD-GYPs encoded in various genomes and list the most common domain combinations involving HD-GYP, such as the RpfG (REC-HD-GYP), Bd1817 (DUF3391-HD-GYP), and PmGH (GAF-HD-GYP) protein families. We also provide the descriptions of six HD-GYP-associated domains, including four novel integral membrane sensor domains. This work is expected to stimulate studies of diverse HD-GYP-containing proteins, their N-terminal sensor domains, and the signals to which they respond.

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