scholarly journals PROTEINATOR: Web-UI exploring repurposing hypotheses of PROTEIN InhibiTORs based on protein interactions

2019 ◽  
Author(s):  
Santhosh Tangadu ◽  
Susmitha Shankara ◽  
Bhaskaram V. Varanasi ◽  
Prashanth Athri
Keyword(s):  
Drug Development ◽  
Search Engine ◽  
Protein Interactions ◽  
Web Application ◽  
Direct Interaction ◽  
Drug Repurposing ◽  
Protein S ◽  
Protein Protein Interactions ◽  
Integration Strategy ◽  
Data Analytic

AbstractPROTEINATOR is the first version of a staggered, multi-paradigm and extensible drug repurposing platform, focusing on a novel data analytic and integration strategy to find repurposing candidates that have potential to modulate targets through protein-protein interactions. The UI was created as an explorer to find ‘indirect’ drugs for a protein of interest. PROTEINATOR is developed as a web application that lets researchers search for alternate drugs for a protein of interest, based on the protein’s direct interaction with a another druggable protein. This unique tool provides researchers exploring specific implicated protein(s) (in the context of drug development), alternate, plausible routes to modulation by listing proteins that interact with the protein of interest that have reported inhibitors. It is a search engine to identify indirect drugs through connecting various databases, thus avoiding multiple steps and avoiding any manual errors. Using a representative set of databases, 112083 number of ‘indirect’ drug interactions are discovered that are potential modulators of proteins, detailed annotations of which are provided in the UI. PROTEINATOR is freely available at http://www.proteinator.in.

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 TRIM22. A Multitasking Antiviral Factor

Cells ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 1864
Author(s):  
Isabel Pagani ◽  
Guido Poli ◽  
Elisa Vicenzi
Keyword(s):  
Protein Interactions ◽  
Influenza A ◽  
Direct Interaction ◽  
Type I Interferons ◽  
Viral Gene ◽  
Target Cells ◽  
Type I ◽  
Protein Protein Interactions ◽  
Viral Genomes ◽  
Dna And Rna

Viral invasion of target cells triggers an immediate intracellular host defense system aimed at preventing further propagation of the virus. Viral genomes or early products of viral replication are sensed by a number of pattern recognition receptors, leading to the synthesis and production of type I interferons (IFNs) that, in turn, activate a cascade of IFN-stimulated genes (ISGs) with antiviral functions. Among these, several members of the tripartite motif (TRIM) family are antiviral executors. This article will focus, in particular, on TRIM22 as an example of a multitarget antiviral member of the TRIM family. The antiviral activities of TRIM22 against different DNA and RNA viruses, particularly human immunodeficiency virus type 1 (HIV-1) and influenza A virus (IAV), will be discussed. TRIM22 restriction of virus replication can involve either direct interaction of TRIM22 E3 ubiquitin ligase activity with viral proteins, or indirect protein–protein interactions resulting in control of viral gene transcription, but also epigenetic effects exerted at the chromatin level.

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

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.

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

2021 ◽  
Author(s):  
Aysam Guerler ◽  
Dannon Baker ◽  
Marius van den Beek ◽  
Dave Bouvier ◽  
Nate Coraor ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Drug Targets ◽  
Structural Models ◽  
Protein S ◽  
Structural Protein ◽  
Protein Protein Interactions ◽  
High Quality ◽  
Dipeptidyl Peptidase 4 ◽  
Genome Wide ◽  
Living Organisms

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.

scholarly journals MaXLinker: Proteome-wide Cross-link Identifications with High Specificity and Sensitivity

2019 ◽  
Vol 19 (3) ◽  
pp. 554-568 ◽  
Author(s):  
Kumar Yugandhar ◽  
Ting-Yi Wang ◽  
Alden King-Yung Leung ◽  
Michael Charles Lanz ◽  
Ievgen Motorykin ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Search Engine ◽  
Protein Interactions ◽  
Molecular Mechanisms ◽  
Cross Linking ◽  
Interaction Patterns ◽  
Protein Protein Interactions ◽  
Cross Link ◽  
Wide Cross ◽  
Cross Links

Protein-protein interactions play a vital role in nearly all cellular functions. Hence, understanding their interaction patterns and three-dimensional structural conformations can provide crucial insights about various biological processes and underlying molecular mechanisms for many disease phenotypes. Cross-linking mass spectrometry (XL-MS) has the unique capability to detect protein-protein interactions at a large scale along with spatial constraints between interaction partners. The inception of MS-cleavable cross-linkers enabled the MS2-MS3 XL-MS acquisition strategy that provides cross-link information from both MS2 and MS3 level. However, the current cross-link search algorithm available for MS2-MS3 strategy follows a “MS2-centric” approach and suffers from a high rate of mis-identified cross-links. We demonstrate the problem using two new quality assessment metrics [“fraction of mis-identifications” (FMI) and “fraction of interprotein cross-links from known interactions” (FKI)]. We then address this problem, by designing a novel “MS3-centric” approach for cross-link identification and implementing it as a search engine named MaXLinker. MaXLinker outperforms the currently popular search engine with a lower mis-identification rate, and higher sensitivity and specificity. Moreover, we performed human proteome-wide cross-linking mass spectrometry using K562 cells. Employing MaXLinker, we identified a comprehensive set of 9319 unique cross-links at 1% false discovery rate, comprising 8051 intraprotein and 1268 interprotein cross-links. Finally, we experimentally validated the quality of a large number of novel interactions identified in our study, providing a conclusive evidence for MaXLinker's robust performance.

Multidimensional Integration Analysis of Autophagy-related Modules in Colorectal Cancer

2019 ◽  
Vol 16 (4) ◽  
pp. 340-346
Author(s):  
Yang Zhang ◽  
Zheng Zhang ◽  
Dong Wang ◽  
Jianzhen Xu ◽  
Yanhui Li ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Protein Interactions ◽  
Colon Adenocarcinoma ◽  
Undifferentiated Carcinoma ◽  
Protein Protein Interactions ◽  
Integration Strategy ◽  
Novel Approach ◽  
Multidimensional Integration ◽  
Regulation Network ◽  
Integration Analysis

Colorectal cancer (CRC) is a common malignant tumor of the digestive tract occurring in the colon, which mainly divided into adenocarcinoma, mucinous adenocarcinoma, and undifferentiated carcinoma. However, autophagy is related to the occurrence and development of various kinds of human diseases such as cancer. There is little research on the relationship between CRC and autophagy. Hence, we performed multidimensional integration analysis to systematically explore potential relationship between autophagy and CRC. Based on gene expression datasets of colon adenocarcinoma (COAD) and protein-protein interactions (PPIs), we first identified 12 autophagy-related modules in COAD using WGCNA. Then, 9 module pairs which with significantly crosstalk were deciphered, a total of 6 functional modules. Autophagy-related genes in these modules were closely related with CRC, emphasizing that the important role of autophagy-related genes in CRC, including PPP2CA and EIF4E, etc. In addition to, by integrating transcription factor (TF)-target and RNA-associated interactions, a regulation network was constructed, in which 42 TFs (including SMAD3 and TP53, etc.) and 20 miRNAs (including miR-20 and miR-30a, etc.) were identified as pivot regulators. Pivot TFs were mainly involved in cell cycle, cell proliferation and pathways in cancer. And pivot miRNAs were demonstrated associated with CRC. It suggests that these pivot regulators might be have an effect on the development of CRC by regulating autophagy. In a word, our results suggested that multidimensional integration strategy provides a novel approach to discover potential relationships between autophagy and CRC, and further improves our understanding of autophagy and tumor in human.

scholarly journals Mining peptides against SARS-CoV-2 entry from constructed RBMs-hACE2 isomer libraries using machine learning and molecular docking

2020 ◽  
Author(s):  
Xiaotong He
Keyword(s):  
Binding Affinity ◽  
Protein Interactions ◽  
Surface Protein ◽  
Protein S ◽  
Protein Protein Interactions ◽  
Angiotensin Converting Enzyme 2 ◽  
Transmembrane Potentials ◽  
Inhibitory Peptides ◽  
Feature Filters

Abstract Cellular entry of SARS-CoV-2 initiates from the protein-protein interactions (PPIs) between viral surface protein S and human angiotensin converting enzyme 2 (hACE2). Peptide-based drugs have the advantage of small molecule compounds to block such viral-host PPIs. Thus the viral targetregions on hACE2 have been believed as promising templates for designing specific inhibitory peptides against SARS-CoV-2 infection. However, starting from a few potential templates, in silico design and prediction between binding affinity and bioactivities in vivo are very challenging, herein a novel design strategy was implemented by mining constructed template isomer libraries using feature filters, supervised classifier and peptide protein docking.Applying these methods and the isomer libraries, 4 peptides were identified from 12 millions candidates owing to their distinct stability, interaction activity, inhibitory specificity, binding affinity, transmembrane potentials and effective conformation. These results have supplied a panel of specific anti-COVID19 leads for further drug development, supporting a new feasible antiviral strategy for targeting both intracellular and extracellular SARS-CoV-2 S proteins simultaneously. The methods have provided a useful tool for mining antiviral-peptides against viral diseases.

The C29–C34 parts of antitumor macrolide aplyronine A serve as versatile actin-affinity tags

2021 ◽  
Author(s):  
Didik Huswo Utomo ◽  
Akari Fujieda ◽  
Kentaro Tanaka ◽  
Momoko Takahashi ◽  
Kentaro Futaki ◽  
...  
Keyword(s):  
Natural Products ◽  
Drug Development ◽  
Anticancer Drug ◽  
Protein Interactions ◽  
Side Chain ◽  
Protein Protein Interactions ◽  
Affinity Tags ◽  
Promising Strategy ◽  
Anticancer Drug Development ◽  
Aplyronine A

Anticancer drug development inspired by natural products based on protein–protein interactions (PPI) is a promising strategy. We developed structurally-simplified C29–C34 side-chain analogs of aplyronine A (ApA), an antitumor marine macrolide....

scholarly journals Inhibition of APC anticoagulant activity on oxidized phospholipid by anti–β2-glycoprotein I monoclonal antibodies

Blood ◽  
2005 ◽  
Vol 106 (5) ◽  
pp. 1629-1635 ◽  
Author(s):  
Omid Safa ◽  
Charles T. Esmon ◽  
Naomi L. Esmon
Keyword(s):  
Monoclonal Antibodies ◽  
Protein Interactions ◽  
Anticoagulant Activity ◽  
Activated Protein C ◽  
Membrane Vesicles ◽  
Protein S ◽  
Specific Protein ◽  
Protein Protein Interactions ◽  
Glycoprotein I ◽  
Antibody Complex

Abstract Activated protein C (APC) anticoagulant activity and the ability to be inhibited by auto-antibodies associated with thrombosis are strongly augmented by the presence of phosphatidylethanolamine (PE) and phospholipid oxidation. β2-glycoprotein I (β2-GPI) is a major antigen for antiphospholipid antibodies present in patients with the antiphospholipid syndrome. We therefore investigated whether anti–β2-GPI monoclonal antibodies (mAbs) could inhibit APC with similar membrane specificity. Five mouse mAbs that reacted with different epitopes on β2-GPI were examined. Each inhibited the PE-, phospholipid oxidation–dependent enhancement of APC anticoagulant activity and required antibody divalency. A chimeric APC that retains anticoagulant activity but is relatively unaffected by protein S, PE, or oxidation was not inhibited by the antibodies. In purified systems, anti–β2-GPI mAb inhibition of factor Va inactivation was greater in the presence of protein S and required β2-GPI. Surprisingly, although the mAbs did increase β2-GPI affinity for membranes, PE and oxidation had little influence on the affinity of the β2-GPI antibody complex for the membrane vesicles. We conclude that antibodies to β2-GPI inhibit APC function specifically and contribute to a hypercoaguable state by disrupting specific protein-protein interactions induced by oxidation of PE-containing membranes.

PsfR, a factor that stimulates psbAI expression in the cyanobacterium Synechococcus elongatus PCC 7942

Microbiology ◽  
2004 ◽  
Vol 150 (4) ◽  
pp. 1031-1040 ◽  
Author(s):  
Colleen Thomas ◽  
Carol R. Andersson ◽  
Shannon R. Canales ◽  
Susan S. Golden
Keyword(s):  
Protein Interactions ◽  
Regulation Of Gene Expression ◽  
D1 Protein ◽  
Direct Interaction ◽  
Synechococcus Elongatus ◽  
Phosphoryl Transfer ◽  
Reaction Centre ◽  
Protein Protein Interactions ◽  
Circadian Expression ◽  
Synechococcus Elongatus Pcc 7942

In this paper a gene (psfR) is reported that regulates psbAI activity in Synechococcus elongatus, a unicellular photoautotrophic cyanobacterium that carries out oxygenic (plant-type) photosynthesis and exhibits global circadian regulation of gene expression. In S. elongatus, a family of three psbA genes encodes the D1 protein of the photosystem II reaction centre. Overexpression of psfR results in increased expression of psbAI, but does not affect the circadian timing of psbAI expression. psfR overexpression affected some, but not all of the genes routinely surveyed for circadian expression. PsfR acts (directly or indirectly) on the psbAI basal promoter region. psfR knockout mutants exhibit wild-type psbAI expression, suggesting that other factors can regulate psbAI expression in the absence of functional PsfR. PsfR contains two receiver-like domains (found in bacterial two-component signal transduction systems), one of which lacks the conserved aspartyl residue required for phosphoryl transfer. PsfR also contains a GGDEF domain. The presence of these domains and the absence of a detectable conserved DNA-binding domain suggest that PsfR may regulate psbAI expression via protein–protein interactions or GGDEF activity (the production of cyclic dinucleotides) rather than direct interaction with the psbAI promoter.

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