scholarly journals CAT, AGTR2, L-SIGN and DC-SIGN are potential receptors for the entry of SARS-CoV-2 into human cells

2021 ◽  
Author(s):  
Dongjie Guo ◽  
Ruifang Guo ◽  
Zhaoyang Li ◽  
Yuyang Zhang ◽  
Wei Zheng ◽  
...  
Keyword(s):  
Gastrointestinal Tract ◽  
Protein Interactions ◽  
Hot Spots ◽  
Human Tissues ◽  
Binding Affinities ◽  
Protein Protein Interactions ◽  
S Protein ◽  
Putative Protein ◽  
The World ◽  
Low Expression

Since December 2019, the COVID-19 caused by SARS-CoV-2 has been widely spread all over the world. It is reported that SARS-CoV-2 infection affects a series of human tissues, including lung, gastrointestinal tract, kidney, etc. ACE2 has been identified as the primary receptor of the SARS-CoV-2 Spike (S) protein. The relatively low expression level of this known receptor in the lungs, which is the predominantly infected organ in COVID-19, indicates that there may be some other co-receptors or alternative receptors of SARS-CoV-2 to work in coordination with ACE2. Here, we identified twenty-one candidate receptors of SARS-CoV-2, including ACE2-interactor proteins and SARS-CoV receptors. Then we investigated the protein expression levels of these twenty-one candidate receptors in different human tissues and found that five of which CAT, MME, L-SIGN, DC-SIGN, and AGTR2 were specifically expressed in SARS-CoV-2 affected tissues. Next, we performed molecular simulations of the above five candidate receptors with SARS-CoV-2 S protein, and found that the binding affinities of CAT, AGTR2, L-SIGN and DC-SIGN to S protein were even higher than ACE2. Interestingly, we also observed that CAT and AGTR2 bound to S protein in different regions with ACE2 conformationally, suggesting that these two proteins are likely capable of the co-receptors of ACE2. Conclusively, we considered that CAT, AGTR2, L-SIGN and DC-SIGN were the potential receptors of SARS-CoV-2. Moreover, AGTR2 and DC-SIGN tend to be highly expressed in the lungs of smokers, which is consistent with clinical phenomena of COVID-19, and further confirmed our conclusion. Besides, we also predicted the binding hot spots for these putative protein-protein interactions, which would help develop drugs against SARS-CoV-2.

scholarly journals Elucidating the druggable interface of protein−protein interactions using fragment docking and coevolutionary analysis

2016 ◽  
Vol 113 (50) ◽  
pp. E8051-E8058 ◽  
Author(s):  
Fang Bai ◽  
Faruck Morcos ◽  
Ryan R. Cheng ◽  
Hualiang Jiang ◽  
José N. Onuchic
Keyword(s):  
Drug Design ◽  
Protein Interactions ◽  
Binding Sites ◽  
Hot Spots ◽  
Therapeutic Agents ◽  
Molecular Probes ◽  
Therapeutic Drug ◽  
Protein Protein Interactions ◽  
Protein Surface ◽  
Fragment Docking

Protein−protein interactions play a central role in cellular function. Improving the understanding of complex formation has many practical applications, including the rational design of new therapeutic agents and the mechanisms governing signal transduction networks. The generally large, flat, and relatively featureless binding sites of protein complexes pose many challenges for drug design. Fragment docking and direct coupling analysis are used in an integrated computational method to estimate druggable protein−protein interfaces. (i) This method explores the binding of fragment-sized molecular probes on the protein surface using a molecular docking-based screen. (ii) The energetically favorable binding sites of the probes, called hot spots, are spatially clustered to map out candidate binding sites on the protein surface. (iii) A coevolution-based interface interaction score is used to discriminate between different candidate binding sites, yielding potential interfacial targets for therapeutic drug design. This approach is validated for important, well-studied disease-related proteins with known pharmaceutical targets, and also identifies targets that have yet to be studied. Moreover, therapeutic agents are proposed by chemically connecting the fragments that are strongly bound to the hot spots.

Functional nonsynonymous single nucleotide polymorphisms from the TGF-β protein interaction network

2007 ◽  
Vol 29 (2) ◽  
pp. 109-117 ◽  
Author(s):  
Sevtap Savas ◽  
Ian W. Taylor ◽  
Jeff L. Wrana ◽  
Hilmi Ozcelik
Keyword(s):  
Single Nucleotide Polymorphisms ◽  
Protein Interactions ◽  
Transforming Growth Factor ◽  
Conservation Status ◽  
Genetic Variations ◽  
Phosphorylation Sites ◽  
Nucleotide Polymorphisms ◽  
Protein Protein Interactions ◽  
Single Nucleotide ◽  
Putative Protein

Protein complexes mediated by protein-protein interactions are essential for many cellular functions. Transforming growth factor (TGF)-β signaling involves a cascade of protein-protein interactions and malfunctioning of this pathway has been implicated in human diseases. Using an in silico approach, we analyzed the naturally occurring human genetic variations from the proteins involved in the TGF-β signaling (10 TGF-β proteins and 242 other proteins interacting with them) to identify the ones that have potential biological consequences. All proteins were searched in the dbSNP database for the presence of nonsynonymous single nucleotide polymorphisms (nsSNPs). A total of 118 validated nsSNPs from 63 proteins were retrieved and analyzed in terms of 1) evolutionary conservation status, 2) being located in a functional protein domain or motif, and 3) altering putative protein motif or phosphorylation sites. Our results indicated the presence of 31 nsSNPs that occurred at evolutionarily conserved residues, 37 nsSNPs were located in protein domains, motifs, or repeats, and 46 nsSNPs were predicted to either create or abolish putative protein motifs or phosphorylation sites. We undertook this study to analyze the human genetic variations that can affect the protein function and the TGF-β signaling. The nsSNPs reported in here can be characterized by experimental approaches to elucidate their exact biological roles and whether they are related to human disease.

scholarly journals The structural evolution of host-pathogen protein interactions: an integrative approach

2019 ◽  
Author(s):  
Anderson F. Brito ◽  
John W. Pinney
Keyword(s):  
Protein Interactions ◽  
Homology Modelling ◽  
Structural Evolution ◽  
Integrative Approach ◽  
Binding Affinities ◽  
Protein Protein Interactions ◽  
Host Pathogen ◽  
Cell Membrane Proteins ◽  
Pathogen Protein ◽  
History Of

ABSTRACTThe evolution of protein-protein interactions (PPIs) is directly influenced by the evolutionary histories of the genes and the species encoding the interacting proteins. When it comes to PPIs of host-pathogen systems, the complexity of their evolution is much higher, as two independent, but biologically associated entities, are involved. In this work, an integrative approach combining phylogenetics, tree reconciliations, ancestral sequence reconstructions, and homology modelling is proposed for studying the evolution of host-pathogen PPIs. As a case study, we analysed the evolution of interactions between herpesviral glycoproteins gD/gG and the cell membrane proteins nectins. By modelling the structures of more than 12,000 ancestral states of these virus-host complexes it was found that in early times of their evolution, these proteins were unable to interact, most probably due to electrostatic incompatibilities between their interfaces. After the event of gene duplication that gave rise to a paralog of gD (known as gG), both protein lineages evolved following distinct functional constraints, with most gD reaching high binding affinities towards nectins, while gG lost such ability, most probably due to a process of neofunctionalization. Based on their favourable interaction energies (negative ΔG), it is possible to hypothesize that apart from nectins 1 and 2, some alphaherpesviruses might also use nectins 3 and 4 as cell receptors. These findings show that the proposed integrative method is suitable for modelling the evolution of host-pathogen protein interactions, and useful for raising new hypotheses that broaden our understanding about the evolutionary history of PPIs, and their molecular functioning.

scholarly journals Quantitative yeast-yeast two hybrid for discovery and binding affinity estimation of protein-protein interactions

2020 ◽  
Author(s):  
Kaitlyn Bacon ◽  
Abigail Blain ◽  
John Bowen ◽  
Matthew Burroughs ◽  
Nikki McArthur ◽  
...  
Keyword(s):  
Binding Affinity ◽  
Protein Interactions ◽  
Quantitative Estimation ◽  
Surface Display ◽  
Combinatorial Libraries ◽  
Yeast Surface Display ◽  
Binding Affinities ◽  
Protein Protein Interactions ◽  
Yeast Two Hybrid ◽  
Two Hybrid

AbstractQuantifying the binding affinity of protein-protein interactions is important for elucidating connections within biochemical signaling pathways, as well as characterization of binding proteins isolated from combinatorial libraries. We describe a quantitative yeast-yeast two hybrid (qYY2H) system that not only enables discovery of specific protein-protein interactions, but also efficient, quantitative estimation of their binding affinities (KD). In qYY2H, the bait and prey proteins are expressed as yeast cell surface fusions using yeast surface display. We developed a semi-empirical framework for estimating the KD of monovalent bait-prey interactions, using measurements of the apparent KD of yeast-yeast binding, which is mediated by multivalent interactions between yeast-displayed bait and prey. Using qYY2H, we identified interaction partners of SMAD3 and the tandem WW domains of YAP from a cDNA library and characterized their binding affinities. Finally, we showed that qYY2H could also quantitatively evaluate binding interactions mediated by post-translational modifications on the bait protein.

scholarly journals The TissueNet v.2 database: A quantitative view of protein-protein interactions across human tissues

2016 ◽  
Vol 45 (D1) ◽  
pp. D427-D431 ◽  
Author(s):  
Omer Basha ◽  
Ruth Barshir ◽  
Moran Sharon ◽  
Eugene Lerman ◽  
Binyamin F. Kirson ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Human Tissues ◽  
Protein Protein Interactions

scholarly journals Modeling of Protein–Protein Interactions in Cytokinin Signal Transduction

2019 ◽  
Vol 20 (9) ◽  
pp. 2096 ◽  
Author(s):  
Dmitry V. Arkhipov ◽  
Sergey N. Lomin ◽  
Yulia A. Myakushina ◽  
Ekaterina M. Savelieva ◽  
Dmitry I. Osolodkin ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Hot Spots ◽  
Protein Complexes ◽  
Structural Features ◽  
Signaling Proteins ◽  
In Planta ◽  
Protein Protein Interactions ◽  
Response Regulators ◽  
Protein Surfaces

The signaling of cytokinins (CKs), classical plant hormones, is based on the interaction of proteins that constitute the multistep phosphorelay system (MSP): catalytic receptors—sensor histidine kinases (HKs), phosphotransmitters (HPts), and transcription factors—response regulators (RRs). Any CK receptor was shown to interact in vivo with any of the studied HPts and vice versa. In addition, both of these proteins tend to form a homodimer or a heterodimeric complex with protein-paralog. Our study was aimed at explaining by molecular modeling the observed features of in planta protein–protein interactions, accompanying CK signaling. For this purpose, models of CK-signaling proteins’ structure from Arabidopsis and potato were built. The modeled interaction interfaces were formed by rather conserved areas of protein surfaces, complementary in hydrophobicity and electrostatic potential. Hot spots amino acids, determining specificity and strength of the interaction, were identified. Virtual phosphorylation of conserved Asp or His residues affected this complementation, increasing (Asp-P in HK) or decreasing (His-P in HPt) the affinity of interacting proteins. The HK–HPt and HPt–HPt interfaces overlapped, sharing some of the hot spots. MSP proteins from Arabidopsis and potato exhibited similar properties. The structural features of the modeled protein complexes were consistent with the experimental data.

Druggable protein–protein interactions – from hot spots to hot segments

2013 ◽  
Vol 17 (6) ◽  
pp. 952-959 ◽  
Author(s):  
Nir London ◽  
Barak Raveh ◽  
Ora Schueler-Furman
Keyword(s):  
Protein Interactions ◽  
Hot Spots ◽  
Protein Protein Interactions

scholarly journals Quantifying protein-protein interactions by molecular counting with mass photometry

2020 ◽  
Author(s):  
Fabian Soltermann ◽  
Eric D.B. Foley ◽  
Veronica Pagnoni ◽  
Martin R. Galpin ◽  
Justin L.P. Benesch ◽  
...  
Keyword(s):  
Molecular Mass ◽  
Single Molecule ◽  
Protein Interactions ◽  
Analytical Techniques ◽  
Binding Affinities ◽  
Label Free ◽  
Protein Protein Interactions ◽  
Single Molecule Level ◽  
Minimal Invasiveness ◽  
Universal Approach

AbstractInteractions between biomolecules control the processes of life in health, and their malfunction in disease, making their characterization and quantification essential. Immobilization- and label-free analytical techniques are particular desirable because of their simplicity and minimal invasiveness, but struggle to quantify tight interactions. Here, we show that we can accurately count, distinguish by molecular mass, and thereby reveal the relative abundances of different un-labelled biomolecules and their complexes in mixtures at the single-molecule level by mass photometry. These measurements enable us to quantify binding affinities over four orders of magnitude at equilibrium for both simple and complex stoichiometries within minutes, as well as to determine the associated kinetics. Our results introduce mass photometry as a rapid, simple and label-free method for studying sub-μM binding affinities, with potential to be extended towards a universal approach for characterising complex biomolecular interactions.

scholarly journals Systematic discovery of Short Linear Motifs decodes calcineurin phosphatase signaling

2019 ◽  
Author(s):  
Callie P. Wigington ◽  
Jagoree Roy ◽  
Nikhil P. Damle ◽  
Vikash K. Yadav ◽  
Cecilia Blikstad ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Nuclear Pore ◽  
Binding Affinities ◽  
Protein Protein Interactions ◽  
Short Linear Motifs ◽  
Binding Peptides ◽  
Linear Motifs ◽  
Calcineurin Phosphatase

SummaryShort linear motifs (SLiMs) drive dynamic protein-protein interactions essential for signaling, but sequence degeneracy and low binding affinities make them difficult to identify. We harnessed unbiased systematic approaches for SLiM discovery to elucidate the regulatory network of calcineurin (CN)/PP2B, the Ca2+-activated phosphatase that recognizes LxVP and PxIxIT motifs. In vitro proteome-wide detection of CN-binding peptides, in vivo SLiM-dependent proximity labeling, and in silico modeling of motif determinants uncovered unanticipated CN interactors, including NOTCH1, which we establish as a CN substrate. Unexpectedly, CN shows SLiM-dependent proximity to centrosomal and nuclear pore complex (NPC) proteins – structures where Ca2+ signaling is largely uncharacterized. CN dephosphorylates human and yeast NPC proteins and promotes accumulation of a nuclear transport reporter, suggesting conserved NPC regulation by CN. The CN network assembled here provides a resource to investigate Ca2+ and CN signaling and demonstrates synergy between experimental and computational methods, establishing a blueprint for examining SLiM-based networks.

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