scholarly journals Prediction of antiviral drugs against African swine fever viruses based on protein–protein interaction analysis

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8855
Author(s):  
Zhaozhong Zhu ◽  
Yunshi Fan ◽  
Yang Liu ◽  
Taijiao Jiang ◽  
Yang Cao ◽  
...  

The African swine fever virus (ASFV) has severely influenced the swine industry of the world. Unfortunately, there is currently no effective antiviral drug or vaccine against the virus. Identification of new anti-ASFV drugs is urgently needed. Here, an up-to-date set of protein–protein interactions between ASFV and swine were curated by integration of protein–protein interactions from multiple sources. Thirty-eight swine proteins were observed to interact with ASFVs and were defined as ASFV-interacting swine proteins. The ASFV-interacting swine proteins were found to play a central role in the swine protein–protein interaction network, with significant larger degree, betweenness and smaller shortest path length than other swine proteins. Some of ASFV-interacting swine proteins also interacted with several other viruses and could be taken as potential targets of drugs for broad-spectrum effect, such as HSP90AB1. Finally, the antiviral drugs which targeted ASFV-interacting swine proteins and ASFV proteins were predicted. Several drugs with either broad-spectrum effect or high specificity on ASFV-interacting swine proteins were identified, such as Polaprezinc and Geldanamycin. Structural modeling and molecular dynamics simulation showed that Geldanamycin could bind with swine HSP90AB1 stably. This work could not only deepen our understanding towards the ASFV-swine interactions, but also help for the development of effective antiviral drugs against the ASFVs.

2019 ◽  
Author(s):  
Zhaozhong Zhu ◽  
Yunshi Fan ◽  
Zena Cai ◽  
Zheng Zhang ◽  
Congyu Lu ◽  
...  

AbstractThe African swine fever virus (ASFV) has severely influenced the swine industry of the world. Unfortunately, there is no effective antiviral drug or vaccine against the virus until now. Identification of new anti-ASFV drugs is urgently needed. Here, an up-to-date set of protein-protein interactions (PPIs) between ASFV and swine were curated by integration of PPIs from multiple sources. Thirty-two swine proteins were observed to interact with ASFVs and were defined as AIPs. They were found to play a central role in the swine PPI network, with significant larger degree, betweenness and smaller shortest path length than other swine proteins. Some of AIPs also interacted with several other viruses and could be taken as potential targets of drugs for broad-spectrum effect, such as HSP90AB1. Finally, the antiviral drugs which targeted AIPs and ASFV proteins were predicted. Several drugs with either broad-spectrum effect or high specificity on AIPs were identified, such as Polaprezinc. This work could not only deepen our understanding towards the ASFV-swine interactions, but also help for the development of effective antiviral drugs against the ASFVs.


Author(s):  
Yu-Miao Zhang ◽  
Jun Wang ◽  
Tao Wu

In this study, the Agrobacterium infection medium, infection duration, detergent, and cell density were optimized. The sorghum-based infection medium (SbIM), 10-20 min infection time, addition of 0.01% Silwet L-77, and Agrobacterium optical density at 600 nm (OD600), improved the competence of onion epidermal cells to support Agrobacterium infection at >90% efficiency. Cyclin-dependent kinase D-2 (CDKD-2) and cytochrome c-type biogenesis protein (CYCH), protein-protein interactions were localized. The optimized procedure is a quick and efficient system for examining protein subcellular localization and protein-protein interaction.


2013 ◽  
Author(s):  
Austin G Meyer ◽  
Sara L Sawyer ◽  
Andrew D Ellington ◽  
Claus O Wilke

Existing computational methods to predict protein–protein interaction affinity often perform poorly in important test cases. In particular, the effects of multiple mutations, non-alanine substitutions, and flexible loops are difficult to predict with available tools and protocols. We present here a new method to interrogate affinity differences resulting from mutations in a host-virus protein–protein interface. Our method is based on extensive non-equilibrium all atom simulations: We computationally pull the machupo virus (MACV) spike glycoprotein (GP1) away from the human transferrin receptor (hTfR1) and estimate affinity using the max imum applied force during a pulling simulation and the area under the force-versus-distance curve. We find that these quantities can provide novel biophysical insight into the GP1/hTfR1 interaction. First, with no prior knowledge of the system we can differentiate among wild type and mutant complexes. Second, although the static co-crystal structure shows two large hydrogen-bonding networks in the GP1/hTfR1 interface, our simulations indicate that one of them may not be important for tight binding. Third, one viral site known to be critical for infection may mark an important evolutionary suppressor site for infection-resistant hTfR1 mutants. Finally, our method provides an elegant framework to compare the effects of multi ple mutations, individually and jointly, on protein–protein interactions.


2021 ◽  
Author(s):  
Laia Miret Casals ◽  
Willem Vannecke ◽  
Kurt Hoogewijs ◽  
Gianluca Arauz ◽  
Marina Gay ◽  
...  

We describe furan as a triggerable ‘warhead’ for site-specific cross-linking using the actin and thymosin β4 (Tβ4)-complex as model of a weak and dynamic protein-protein interaction with known 3D structure...


2019 ◽  
Vol 13 (S1) ◽  
Author(s):  
Qingqing Li ◽  
Zhihao Yang ◽  
Zhehuan Zhao ◽  
Ling Luo ◽  
Zhiheng Li ◽  
...  

Abstract Background Protein–protein interaction (PPI) information extraction from biomedical literature helps unveil the molecular mechanisms of biological processes. Especially, the PPIs associated with human malignant neoplasms can unveil the biology behind these neoplasms. However, such PPI database is not currently available. Results In this work, a database of protein–protein interactions associated with 171 kinds of human malignant neoplasms named HMNPPID is constructed. In addition, a visualization program, named VisualPPI, is provided to facilitate the analysis of the PPI network for a specific neoplasm. Conclusions HMNPPID can hopefully become an important resource for the research on PPIs of human malignant neoplasms since it provides readily available data for healthcare professionals. Thus, they do not need to dig into a large amount of biomedical literatures any more, which may accelerate the researches on the PPIs of malignant neoplasms.


2017 ◽  
Vol 114 (40) ◽  
pp. E8333-E8342 ◽  
Author(s):  
Maximilian G. Plach ◽  
Florian Semmelmann ◽  
Florian Busch ◽  
Markus Busch ◽  
Leonhard Heizinger ◽  
...  

Cells contain a multitude of protein complexes whose subunits interact with high specificity. However, the number of different protein folds and interface geometries found in nature is limited. This raises the question of how protein–protein interaction specificity is achieved on the structural level and how the formation of nonphysiological complexes is avoided. Here, we describe structural elements called interface add-ons that fulfill this function and elucidate their role for the diversification of protein–protein interactions during evolution. We identified interface add-ons in 10% of a representative set of bacterial, heteromeric protein complexes. The importance of interface add-ons for protein–protein interaction specificity is demonstrated by an exemplary experimental characterization of over 30 cognate and hybrid glutamine amidotransferase complexes in combination with comprehensive genetic profiling and protein design. Moreover, growth experiments showed that the lack of interface add-ons can lead to physiologically harmful cross-talk between essential biosynthetic pathways. In sum, our complementary in silico, in vitro, and in vivo analysis argues that interface add-ons are a practical and widespread evolutionary strategy to prevent the formation of nonphysiological complexes by specializing protein–protein interactions.


2019 ◽  
Author(s):  
Akhilesh Kumar Bajpai ◽  
Sravanthi Davuluri ◽  
Kriti Tiwary ◽  
Sithalechumi Narayanan ◽  
Sailaja Oguru ◽  
...  

AbstractProtein-protein interactions (PPIs) are critical, and so are the databases and tools (resources) concerning PPIs. But in absence of systematic comparisons, biologists/bioinformaticians may be forced to make a subjective selection among such protein interaction databases and tools. In fact, a comprehensive list of such bioinformatics resources has not been reported so far. For the first time, we compiled 375 PPI resources, short-listed and performed preliminary comparison of 125 important ones (both lists available publicly at startbioinfo.com), and then systematically compared human PPIs from 16 carefully-selected databases. General features have been first compared in detail. The coverage of ‘experimentally verified’ vs. all PPIs, as well as those significant in case of disease-associated and other types of genes among the chosen databases has been compared quantitatively. This has been done in two ways: outputs manually obtained using web-interfaces, and all interactions downloaded from the databases. For the first approach, PPIs obtained in response to gene queries using the web interfaces were compared. As a query set, 108 genes associated with different tissues (specific to kidney, testis, and uterus, and ubiquitous) or diseases (breast cancer, lung cancer, Alzheimer’s, cystic fibrosis, diabetes, and cardiomyopathy) were chosen. PPI-coverage for well-studied genes was also compared with that of less-studied ones. For the second approach, the back-end-data from the databases was downloaded and compared. Based on the results, we recommend the use of STRING and UniHI for retrieving the majority of ‘experimentally verified’ protein interactions, and hPRINT and STRING for obtaining maximum number of ‘total’ (experimentally verified as well as predicted) PPIs. The analysis of experimentally verified PPIs found exclusively in each database revealed that STRING contributed about 71% of exclusive hits. Overall, hPRINT, STRING and IID together retrieved ~94% of ‘total’ protein interactions available in the databases. The coverage of certain databases was skewed for some gene-types. The results also indicate that the database usage frequency may not correlate with their advantages, thereby justifying the need for more frequent studies of this nature.


2019 ◽  
Author(s):  
Franziska Seeger ◽  
Anna Little ◽  
Yang Chen ◽  
Tina Woolf ◽  
Haiyan Cheng ◽  
...  

AbstractProtein-protein interactions regulate many essential biological processes and play an important role in health and disease. The process of experimentally charac-terizing protein residues that contribute the most to protein-protein interaction affin-ity and specificity is laborious. Thus, developing models that accurately characterize hotspots at protein-protein interfaces provides important information about how to inhibit therapeutically relevant protein-protein interactions. During the course of the ICERM WiSDM workshop 2017, we combined the KFC2a protein-protein interaction hotspot prediction features with Rosetta scoring function terms and interface filter metrics. A 2-way and 3-way forward selection strategy was employed to train support vector machine classifiers, as was a reverse feature elimination strategy. From these results, we identified subsets of KFC2a and Rosetta combined features that show improved performance over KFC2a features alone.


2021 ◽  
Author(s):  
Tatiana de Souza Moraes ◽  
Sam W. van Es ◽  
Inmaculada Hernández-Pinzón ◽  
Gwendolyn K. Kirschner ◽  
Froukje van der Wal ◽  
...  

AbstractBarley is the fourth largest cereal crop grown worldwide, and essential for food and feed production. Phenotypically, the barley spike, which is unbranched, occurs in two main architectural shapes: two-rowed or six-rowed. In the 6-rowed cultivars, all three florets of the triple floret meristem develop into seeds while in 2-rowed lines only the central floret forms a seed. VRS5(HvTB1), act as inhibitor of lateral seed outgrowth and vrs5(hvtb1) mutants display a six-rowed spike architecture. VRS5(HvTB1) is a member of the TCP transcription factor (TF) family, which often form protein-protein interactions with other transcriptional regulators to modulate the expression of their target genes.Despite the key role of VRS5(HvTB1) in regulating barley plant architecture, there is hardly any knowledge on its molecular mode-of-action. We performed an extensive phylogenetic analysis of the TCP transcription factor family, followed by an in-vitro protein-protein interaction study using yeast-two-hybrid. Our analysis shows that VRS5(HvTB1) has a diverse interaction capacity, interacting with class II TCP’s, NF-Y TF, but also chromatin modellers. Further analysis of the interaction capacity of VRS5(HvTB1) with other TCP TFs shows that VRS5(HvTB1) preferably interacts with other class II TCP TFs within the TB1 clade. One of these interactors, encoded by HvTB2, shows a similar expression pattern when compared to VRS5(HvTB1). Haplotype analysis of HvTB2 suggest that this gene is highly conserved and shows hardly any variation in cultivars or wild barley. Induced mutations in HvTB2 trough CRISPR-CAS9 mutagenesis in cv. Golden Promise resulted in barley plants that lost their characteristic unbranched spike architecture. hvtb2 mutants exhibited branches arising at the main spike, suggesting that, similar to VRS5(HvTB1), HvTB2 act as inhibitor of branching. Taken together, our protein-protein interaction studies of VRS5(HvTB1) resulted in the identification of HvTB2, another key regulator of spike architecture in barley. Understanding the molecular network, including protein-protein interactions, of key regulators of plant architecture such as VRS5(HvTB1) provide new routes towards the identification of other key regulators of plant architecture in barley.Author summaryTranscriptional regulation is one of the basic molecular processes that drives plant growth and development. The key TCP transcriptional regulator TEOSINTE BRANCHED 1 (TB1) is one of these key regulators that has been targeted during domestication of several crops for its role as modulator of branching. Also in barley, a key cereal crop, HvTB1 (also referred to as VRS5), inhibits the outgrowth or side shoots, or tillers, and seeds. Despite its key role in barley development, there is hardly any knowledge on the molecular network that is utilized by VRS5(HvTB1). Transcriptional regulators form homo- and heterodimers to regulate the expression of their downstream targets. Here, we performed an extensive phylogenetic analysis of TCP transcription factors (TFs) in barley, followed by protein-protein interaction studies of VRS5(HvTB1). Our analysis indicates, that VRS5(HvTB1) has a diverse capacity of interacting with class II TCPs, NF-Y TF, but also chromatin modellers. Induced mutagenesis trough CRISPR-CAS mutagenesis of one of the putative VRS5(HvTB1) interactors, HvTB2, resulted in barley plants with branched spikes. This shows that insight into the VRS5(HvTB1) interactome, followed by detailed functional analysis of potential interactors is essential to truly understand how TCPs modulate plant architecture. The study presented here provides a first step to underpin the protein-protein interactome of VRS5(HvTB1) and identify other, yet unknown, key regulators of barley plant architecture.


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