scholarly journals A systems-based method to repurpose marketed therapeutics for antiviral use: a SARS-CoV-2 case study

2021 ◽  
Vol 4 (5) ◽  
pp. e202000904
Author(s):  
Mengran Wang ◽  
Johanna B Withers ◽  
Piero Ricchiuto ◽  
Ivan Voitalov ◽  
Michael McAnally ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Sequence Similarity ◽  
Interaction Network ◽  
Drug Repurposing ◽  
Viral Proteins ◽  
Antiviral Drugs ◽  
Host Protein ◽  
Physical Interaction ◽  
Protein Protein Interactions ◽  
Emerging Viruses

This study describes two complementary methods that use network-based and sequence similarity tools to identify drug repurposing opportunities predicted to modulate viral proteins. This approach could be rapidly adapted to new and emerging viruses. The first method built and studied a virus–host–physical interaction network; a three-layer multimodal network of drug target proteins, human protein–protein interactions, and viral–host protein–protein interactions. The second method evaluated sequence similarity between viral proteins and other proteins, visualized by constructing a virus–host–similarity interaction network. Methods were validated on the human immunodeficiency virus, hepatitis B, hepatitis C, and human papillomavirus, then deployed on SARS-CoV-2. Comparison of virus–host–physical interaction predictions to known antiviral drugs had AUCs of 0.69, 0.59, 0.78, and 0.67, respectively, reflecting that the scores are predictive of effective drugs. For SARS-CoV-2, 569 candidate drugs were predicted, of which 37 had been included in clinical trials for SARS-CoV-2 (AUC = 0.75, P-value 3.21 × 10−3). As further validation, top-ranked candidate antiviral drugs were analyzed for binding to protein targets in silico; binding scores generated by BindScope indicated a 70% success rate.

scholarly journals A SARS-CoV-2 – host proximity interactome

2020 ◽  
Author(s):  
Payman Samavarchi-Tehrani ◽  
Hala Abdouni ◽  
James D.R. Knight ◽  
Audrey Astori ◽  
Reuben Samson ◽  
...  
Keyword(s):  
Host Cell ◽  
Protein Interactions ◽  
Affinity Purification ◽  
Drug Repurposing ◽  
Viral Proteins ◽  
Host Protein ◽  
Virus Protein ◽  
Host Proteins ◽  
Biochemical Purification ◽  
Cell Functions

AbstractViral replication is dependent on interactions between viral polypeptides and host proteins. Identifying virus-host protein interactions can thus uncover unique opportunities for interfering with the virus life cycle via novel drug compounds or drug repurposing. Importantly, many viral-host protein interactions take place at intracellular membranes and poorly soluble organelles, which are difficult to profile using classical biochemical purification approaches. Applying proximity-dependent biotinylation (BioID) with the fast-acting miniTurbo enzyme to 27 SARS-CoV-2 proteins in a lung adenocarcinoma cell line (A549), we detected 7810 proximity interactions (7382 of which are new for SARS-CoV-2) with 2242 host proteins (results available at covid19interactome.org). These results complement and dramatically expand upon recent affinity purification-based studies identifying stable host-virus protein complexes, and offer an unparalleled view of membrane-associated processes critical for viral production. Host cell organellar markers were also subjected to BioID in parallel, allowing us to propose modes of action for several viral proteins in the context of host proteome remodelling. In summary, our dataset identifies numerous high confidence proximity partners for SARS-CoV-2 viral proteins, and describes potential mechanisms for their effects on specific host cell functions.

scholarly journals Different Subtypes of Influenza Viruses Target Different Human Proteins and Pathways Leading to Different Pathogenic Phenotypes

2019 ◽  
Vol 2019 ◽  
pp. 1-7
Author(s):  
Yujie Wang ◽  
Ting Song ◽  
Kaiwu Li ◽  
Yuan Jin ◽  
Junjie Yue ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Influenza A ◽  
Viral Proteins ◽  
Influenza Viruses ◽  
Host Protein ◽  
Protein Protein Interactions ◽  
Influenza A Viruses ◽  
Host Proteins ◽  
Pathogenic Mechanisms ◽  
Human Proteins

Different subtypes of influenza A viruses (IAVs) cause different pathogenic phenotypes after infecting human bodies. Analysis of the interactions between viral proteins and the host proteins may provide insights into the pathogenic mechanisms of the virus. In this paper, we found that the same proteins (nucleoprotein and neuraminidase) of H1N1 and H5N1 have different impacts on the NF-κB activation. By further examining the virus–host protein–protein interactions, we found that both NP and NA proteins of the H1N1 and H5N1 viruses target different host proteins. These results indicate that different subtypes of influenza viruses target different human proteins and pathways leading to different pathogenic phenotypes.

scholarly journals Role of Viral Protein-Protein Interactions and Possible Targets for New Therapeutics

2021 ◽  
Vol 2 (2) ◽  
pp. 1-15
Author(s):  
Rehan Zafar Paracha ◽  
Fahed Parvaiz ◽  
Babar Aslam ◽  
Ayesha Obaid ◽  
Sidra Qureshi ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Viral Protein ◽  
Influenza A ◽  
Viral Infections ◽  
Treatment Options ◽  
Interaction Network ◽  
Viral Proteins ◽  
Protein Protein Interactions ◽  
Virus Influenza

Viral infections are the cause of serious infirmities in humans and kill millions of people every year. Management of viral diseases is one of the challenges faced by the whole world which needs improvement in prevention and treatment options. Complete understanding of the consequences of viral proteins interaction network on host physiology is essential. Towards this goal, deciphering viral protein-protein interactions is one of the perspective which can help in our understanding about the basis of viral pathogenesis and the development of new antivirals. Indeed, viral infection network based on viral-viral proteins will provide an elusive and investigative framework to articulate rationalize drug discovery based on proteomics scale of viruses. In this study, proteomics a collection of viral-viral protein interactions reporting different studies of Hepatitis C virus, Influenza A virus, Dengue virus and SARS Coronavirus. Our effort of protein-interactions was focused on different studies reporting interactions between viral proteins encoded by the viruses under study. The study is integrated with a broad and original literature-curated data of viral-viral protein (197 non-redundant) interactions.

scholarly journals Poxvirus Proteomics and Virus-Host Protein Interactions

2009 ◽  
Vol 73 (4) ◽  
pp. 730-749 ◽  
Author(s):  
Kim Van Vliet ◽  
Mohamed R. Mohamed ◽  
Leiliang Zhang ◽  
Nancy Yaneth Villa ◽  
Steven J. Werden ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Viral Proteins ◽  
Specific Protein ◽  
Host Protein ◽  
Virus Protein ◽  
Protein Protein Interactions ◽  
Host Interaction ◽  
Chip Technology ◽  
Poxvirus Genome ◽  
Protein Components

SUMMARY Studies of the functional proteins encoded by the poxvirus genome provide information about the composition of the virus as well as individual virus-virus protein and virus-host protein interactions, which provides insight into viral pathogenesis and drug discovery. Widely used proteomic techniques to identify and characterize specific protein-protein interactions include yeast two-hybrid studies and coimmunoprecipitations. Recently, various mass spectrometry techniques have been employed to identify viral protein components of larger complexes. These methods, combined with structural studies, can provide new information about the putative functions of viral proteins as well as insights into virus-host interaction dynamics. For viral proteins of unknown function, identification of either viral or host binding partners provides clues about their putative function. In this review, we discuss poxvirus proteomics, including the use of proteomic methodologies to identify viral components and virus-host protein interactions. High-throughput global protein expression studies using protein chip technology as well as new methods for validating putative protein-protein interactions are also discussed.

scholarly journals A comprehensive physical interaction map between the Turnip mosaic potyvirus and Arabidopsis thaliana proteomes

2021 ◽  
Author(s):  
Fernando Martínez ◽  
Christina Toft ◽  
Julia Hillung ◽  
Silvia Giménez-Santamarina ◽  
Lynne Yenush ◽  
...  
Keyword(s):  
Arabidopsis Thaliana ◽  
Protein Interactions ◽  
Mode Of Action ◽  
Plant Viruses ◽  
Host Protein ◽  
Bimolecular Fluorescence Complementation ◽  
Virus Protein ◽  
Physical Interaction ◽  
Protein Protein Interactions ◽  
Disease Etiology

Abstract Viruses are obligate intracellular parasites that have co-evolved with their hosts to establish an intricate network of protein-protein interactions. Yet, the systems-level mode of action of plant viruses remains poorly understood. Here, we followed a high-throughput yeast two-hybrid screening to identify 378 novel virus-host protein-protein interactions between Turnip mosaic virus (TuMV), a representative plant RNA virus, and Arabidopsis thaliana, one of its natural hosts. We found the RNA-dependent RNA polymerase NIb as the virus protein with the largest number of contacts. We verified a subset of 25 selected interactions in planta by bimolecular fluorescence complementation assays. We then constructed a comprehensive network comprising 399 TuMV-A. thaliana interactions to perform, together with intravirus and intrahost connections, detailed computational analyses. In particular, we found that the host proteins targeted by the virus participate in a higher number of infection-related functions, are more connected and have an increased capacity to spread information throughout the cell proteome, display higher expression levels, and have been subject to stronger purifying selection than expected by chance. Overall, our results provide a comprehensive mechanistic description of a plant virus-host interplay, with potential impact on disease etiology, and reveal that plant and animal viruses share fundamental features in their mode of action.

Decoding Protein-protein Interactions: An Overview

2020 ◽  
Vol 20 (10) ◽  
pp. 855-882
Author(s):  
Olivia Slater ◽  
Bethany Miller ◽  
Maria Kontoyianni
Keyword(s):  
Drug Discovery ◽  
Protein Interactions ◽  
Drug Repurposing ◽  
Protein Docking ◽  
Target Space ◽  
Protein Protein Interactions ◽  
X Ray Crystallography ◽  
Protein Protein Interaction ◽  
Interaction Sites ◽  
Long Time

Drug discovery has focused on the paradigm “one drug, one target” for a long time. However, small molecules can act at multiple macromolecular targets, which serves as the basis for drug repurposing. In an effort to expand the target space, and given advances in X-ray crystallography, protein-protein interactions have become an emerging focus area of drug discovery enterprises. Proteins interact with other biomolecules and it is this intricate network of interactions that determines the behavior of the system and its biological processes. In this review, we briefly discuss networks in disease, followed by computational methods for protein-protein complex prediction. Computational methodologies and techniques employed towards objectives such as protein-protein docking, protein-protein interactions, and interface predictions are described extensively. Docking aims at producing a complex between proteins, while interface predictions identify a subset of residues on one protein that could interact with a partner, and protein-protein interaction sites address whether two proteins interact. In addition, approaches to predict hot spots and binding sites are presented along with a representative example of our internal project on the chemokine CXC receptor 3 B-isoform and predictive modeling with IP10 and PF4.

scholarly journals Short loop functional commonality identified in leukaemia proteome highlights crucial protein sub-networks

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Sun Sook Chung ◽  
Joseph C F Ng ◽  
Anna Laddach ◽  
N Shaun B Thomas ◽  
Franca Fraternali
Keyword(s):  
Protein Interactions ◽  
Large Scale ◽  
Interaction Network ◽  
Protein Protein Interactions ◽  
Protein Protein Interaction ◽  
Ppi Networks ◽  
Short Loop ◽  
New Strategy ◽  
Loop Network ◽  
Protein Protein Interaction Network

Abstract Direct drug targeting of mutated proteins in cancer is not always possible and efficacy can be nullified by compensating protein–protein interactions (PPIs). Here, we establish an in silico pipeline to identify specific PPI sub-networks containing mutated proteins as potential targets, which we apply to mutation data of four different leukaemias. Our method is based on extracting cyclic interactions of a small number of proteins topologically and functionally linked in the Protein–Protein Interaction Network (PPIN), which we call short loop network motifs (SLM). We uncover a new property of PPINs named ‘short loop commonality’ to measure indirect PPIs occurring via common SLM interactions. This detects ‘modules’ of PPI networks enriched with annotated biological functions of proteins containing mutation hotspots, exemplified by FLT3 and other receptor tyrosine kinase proteins. We further identify functional dependency or mutual exclusivity of short loop commonality pairs in large-scale cellular CRISPR–Cas9 knockout screening data. Our pipeline provides a new strategy for identifying new therapeutic targets for drug discovery.

scholarly journals Frequent assembly of chimeric complexes in the protein interaction network of an interspecies yeast hybrid

2020 ◽  
Author(s):  
Rohan Dandage ◽  
Caroline M Berger ◽  
Isabelle Gagnon-Arsenault ◽  
Kyung-Mee Moon ◽  
Richard Greg Stacey ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Molecular Level ◽  
Yeast Species ◽  
Protein Complexes ◽  
Mitochondrial Protein ◽  
Chimeric Protein ◽  
Interaction Network ◽  
Protein Protein Interactions ◽  
Extreme Phenotypes ◽  
Yeast Hybrid

Abstract Hybrids between species often show extreme phenotypes, including some that take place at the molecular level. In this study, we investigated the phenotypes of an interspecies diploid hybrid in terms of protein-protein interactions inferred from protein correlation profiling. We used two yeast species, Saccharomyces cerevisiae and Saccharomyces uvarum, which are interfertile, but yet have proteins diverged enough to be differentiated using mass spectrometry. Most of the protein-protein interactions are similar between hybrid and parents, and are consistent with the assembly of chimeric complexes, which we validated using an orthogonal approach for the prefoldin complex. We also identified instances of altered protein-protein interactions in the hybrid, for instance in complexes related to proteostasis and in mitochondrial protein complexes. Overall, this study uncovers the likely frequent occurrence of chimeric protein complexes with few exceptions, which may result from incompatibilities or imbalances between the parental proteins.

scholarly journals PIPINO: A Software Package to Facilitate the Identification of Protein-Protein Interactions from Affinity Purification Mass Spectrometry Data

2016 ◽  
Vol 2016 ◽  
pp. 1-13
Author(s):  
Stefan Kalkhof ◽  
Stefan Schildbach ◽  
Conny Blumert ◽  
Friedemann Horn ◽  
Martin von Bergen ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Protein Interactions ◽  
Isotope Labeling ◽  
Affinity Purification ◽  
Interaction Network ◽  
Mass Spectrometry Data ◽  
Protein Protein Interactions ◽  
Protein Protein Interaction ◽  
Binding Behavior ◽  
Bona Fide

The functionality of most proteins is regulated by protein-protein interactions. Hence, the comprehensive characterization of the interactome is the next milestone on the path to understand the biochemistry of the cell. A powerful method to detect protein-protein interactions is a combination of coimmunoprecipitation or affinity purification with quantitative mass spectrometry. Nevertheless, both methods tend to precipitate a high number of background proteins due to nonspecific interactions. To address this challenge the software Protein-Protein-Interaction-Optimizer (PIPINO) was developed to perform an automated data analysis, to facilitate the selection of bona fide binding partners, and to compare the dynamic of interaction networks. In this study we investigated the STAT1 interaction network and its activation dependent dynamics. Stable isotope labeling by amino acids in cell culture (SILAC) was applied to analyze the STAT1 interactome after streptavidin pull-down of biotagged STAT1 from human embryonic kidney 293T cells with and without activation. Starting from more than 2,000 captured proteins 30 potential STAT1 interaction partners were extracted. Interestingly, more than 50% of these were already reported or predicted to bind STAT1. Furthermore, 16 proteins were found to affect the binding behavior depending on STAT1 phosphorylation such as STAT3 or the importin subunits alpha 1 and alpha 6.

Sign in / Sign up

Export Citation Format

Share Document