Fast and accurate genome-wide predictions and structural modeling of protein-protein interactions using Galaxy

Protein-protein interactions play a crucial role in almost all cellular processes. Identifying interacting proteins reveals insight into living organisms and yields novel drug targets for disease treatment. Here, we present a publicly available, automated pipeline to predict genome-wide protein-protein interactions and produce high-quality multimeric structural models. Application of our method to the Human and Yeast genomes yield protein-protein interaction networks similar in quality to common experimental methods. We identified and modeled Human proteins likely to interact with the papain-like protease of SARS-CoV2's non-structural protein 3 (Nsp3). We also produced models of SARS-CoV2's spike protein (S) interacting with myelin-oligodendrocyte glycoprotein receptor (MOG) and dipeptidyl peptidase-4 (DPP4). The presented method is capable of confidently identifying interactions while providing high-quality multimeric structural models for experimental validation. The interactome modeling pipeline is available at usegalaxy.org.

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Roles of the 14-3-3 gene family in cotton flowering

BMC Plant Biology ◽

10.1186/s12870-021-02923-9 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Na Sang ◽

Hui Liu ◽

Bin Ma ◽

Xianzhong Huang ◽

Lu Zhuo ◽

...

Keyword(s):

Gene Family ◽

Protein Interactions ◽

Leucine Zipper ◽

Expression Patterns ◽

Bimolecular Fluorescence Complementation ◽

Structural Motif ◽

Virus Induced Gene Silencing ◽

Protein Protein Interactions ◽

Basic Leucine Zipper ◽

Genome Wide

Abstract Background In plants, 14-3-3 proteins, also called GENERAL REGULATORY FACTORs (GRFs), encoded by a large multigene family, are involved in protein–protein interactions and play crucial roles in various physiological processes. No genome-wide analysis of the GRF gene family has been performed in cotton, and their functions in flowering are largely unknown. Results In this study, 17, 17, 31, and 17 GRF genes were identified in Gossypium herbaceum, G. arboreum, G. hirsutum, and G. raimondii, respectively, by genome-wide analyses and were designated as GheGRFs, GaGRFs, GhGRFs, and GrGRFs, respectively. A phylogenetic analysis revealed that these proteins were divided into ε and non-ε groups. Gene structural, motif composition, synteny, and duplicated gene analyses of the identified GRF genes provided insights into the evolution of this family in cotton. GhGRF genes exhibited diverse expression patterns in different tissues. Yeast two-hybrid and bimolecular fluorescence complementation assays showed that the GhGRFs interacted with the cotton FLOWERING LOCUS T homologue GhFT in the cytoplasm and nucleus, while they interacted with the basic leucine zipper transcription factor GhFD only in the nucleus. Virus-induced gene silencing in G. hirsutum and transgenic studies in Arabidopsis demonstrated that GhGRF3/6/9/15 repressed flowering and that GhGRF14 promoted flowering. Conclusions Here, 82 GRF genes were identified in cotton, and their gene and protein features, classification, evolution, and expression patterns were comprehensively and systematically investigated. The GhGRF3/6/9/15 interacted with GhFT and GhFD to form florigen activation complexs that inhibited flowering. However, GhGRF14 interacted with GhFT and GhFD to form florigen activation complex that promoted flowering. The results provide a foundation for further studies on the regulatory mechanisms of flowering.

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Genome-wide analysis of vaccinia virus protein-protein interactions

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.080078197 ◽

2000 ◽

Vol 97 (9) ◽

pp. 4879-4884 ◽

Cited By ~ 193

Author(s):

S. McCraith ◽

T. Holtzman ◽

B. Moss ◽

S. Fields

Keyword(s):

Vaccinia Virus ◽

Protein Interactions ◽

Virus Protein ◽

Protein Protein Interactions ◽

Genome Wide Analysis ◽

Genome Wide

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Coiled-coil networking shapes cell molecular machinery

Molecular Biology of the Cell ◽

10.1091/mbc.e12-05-0396 ◽

2012 ◽

Vol 23 (19) ◽

pp. 3911-3922 ◽

Cited By ~ 44

Author(s):

Yongqiang Wang ◽

Xinlei Zhang ◽

Hong Zhang ◽

Yi Lu ◽

Haolong Huang ◽

...

Keyword(s):

Protein Interactions ◽

Critical Role ◽

Coiled Coil ◽

Coiled Coils ◽

Protein Protein Interactions ◽

Full Spectrum ◽

Kinetochore Assembly ◽

Genome Wide ◽

Molecular Machinery ◽

Systematic Understanding

The highly abundant α-helical coiled-coil motif not only mediates crucial protein–protein interactions in the cell but is also an attractive scaffold in synthetic biology and material science and a potential target for disease intervention. Therefore a systematic understanding of the coiled-coil interactions (CCIs) at the organismal level would help unravel the full spectrum of the biological function of this interaction motif and facilitate its application in therapeutics. We report the first identified genome-wide CCI network in Saccharomyces cerevisiae, which consists of 3495 pair-wise interactions among 598 predicted coiled-coil regions. Computational analysis revealed that the CCI network is specifically and functionally organized and extensively involved in the organization of cell machinery. We further show that CCIs play a critical role in the assembly of the kinetochore, and disruption of the CCI network leads to defects in kinetochore assembly and cell division. The CCI network identified in this study is a valuable resource for systematic characterization of coiled coils in the shaping and regulation of a host of cellular machineries and provides a basis for the utilization of coiled coils as domain-based probes for network perturbation and pharmacological applications.

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Exploring Protein-Protein Interactions as Drug Targets for Anti-cancer Therapy with In Silico Workflows

Methods in Molecular Biology - Proteomics for Drug Discovery ◽

10.1007/978-1-4939-7201-2_15 ◽

2017 ◽

pp. 221-236 ◽

Cited By ~ 11

Author(s):

Alexander Goncearenco ◽

Minghui Li ◽

Franco L. Simonetti ◽

Benjamin A. Shoemaker ◽

Anna R. Panchenko

Keyword(s):

Cancer Therapy ◽

Protein Interactions ◽

In Silico ◽

Drug Targets ◽

Protein Protein Interactions ◽

Anti Cancer

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Significance of thiol-disulfide balance in SARS-CoV-2 infection

Medicinski podmladak ◽

10.5937/mp72-32874 ◽

2021 ◽

Vol 72 (3) ◽

pp. 30-36

Author(s):

Tatjana Simić

Keyword(s):

Cell Surface ◽

Host Cell ◽

Protein Interactions ◽

Viral Entry ◽

Molecular Mechanisms ◽

Alkylating Agents ◽

Protein S ◽

Protein Protein Interactions ◽

Virus Surface ◽

Host Cell Surface

Studies of the molecular mechanisms regarding interaction of different viruses with receptors on the host cell surface have shown that the viral entry depends on the specific relationship between free thiol (SH) groups and disulfides on the virus surface, as well as the thiol disulfide balance on the host cell surface. The presence of oxidizing compounds or alkylating agents, which disturb the thiol-disulfide balance on the surface of the virus, can also affect its infectious potential. Disturbed thiol-disulfide balance may also influence protein-protein interactions between SARS-CoV-2 protein S and ACE2 receptors of the host cell. This review presents the basic mechanisms of maintaining intracellular and extracellular thiol disulfide balance and previous experimental and clinical evidence in favor of impaired balance in SARS-CoV-2 infection. Besides, the results of the clinical application or experimental analysis of compounds that induce changes in the thiol disulfide balance towards reduction of disulfide bridges in proteins of interest in COVID-19 infection are presented.

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Prioritization of genes associated with the pathogenesis of leukosis in cattle

Vavilov Journal of Genetics and Breeding ◽

10.18699/vj18.451 ◽

2019 ◽

Vol 22 (8) ◽

pp. 1063-1069 ◽

Cited By ~ 1

Author(s):

N. S. Yudin ◽

N. L. Podkolodnyy ◽

T. A. Agarkova ◽

E. V. Ignatieva

Keyword(s):

Protein Interactions ◽

Genome Wide Association Study ◽

Association Studies ◽

Mammalian Species ◽

Genome Wide Association ◽

Farm Animals ◽

Genome Wide Association Studies ◽

Protein Protein Interactions ◽

Genome Wide ◽

A Genome

Selection by means of genetic markers is a promising approach to the eradication of infectious diseases in farm animals, especially in the absence of eﬀective methods of treatment and prevention. Bovine leukemia virus (BLV) is spread throughout the world and represents one of the biggest problems for the livestock production and food security in Russia. However, recent genome-wide association studies have shown that sensitivity/resistance to BLV is polygenic. The aim of this study was to create a catalog of cattle genes and genes of other mammalian species involved in the pathogenesis of BLV-induced infection and to perform gene prioritization using bioinformatics methods. Based on manually collected information from a range of open sources, a total of 446 genes were included in the catalog of cattle genes and genes of other mammals involved in the pathogenesis of BLV-induced infection. The following criteria were used to prioritize 446 genes from the catalog: (1) the gene is associated with leukemia according to a genome-wide association study; (2) the gene is associated with leukemia according to a case-control study; (3) the role of the gene in leukemia development has been studied using knockout mice; (4) protein-protein interactions exist between the gene-encoded protein and either viral particles or individual viral proteins; (5) the gene is annotated with Gene Ontology terms that are overrepresented for a given list of genes; (6) the gene participates in biological pathways from the KEGG or REACTOME databases, which are over-represented for a given list of genes; (7) the protein encoded by the gene has a high number of protein-protein interactions with proteins encoded by other genes from the catalog. Based on each criterion, a rank was assigned to each gene. Then the ranks were summarized and an overall rank was determined. Prioritization of 446 candidate genes allowed us to identify 5 genes of interest (TNF,LTB,BOLA-DQA1,BOLA-DRB3,ATF2), which can aﬀect the sensitivity/resistance of cattle to leukemia.

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