Protein-protein interaction and molecular dynamics of Iturin A gene on effector proteins Phytophthora infestans

2020 ◽  
Vol 23 ◽  
Author(s):  
Bhimanagoud Kumbar ◽  
Shivananda Kandagalla ◽  
Bharath B R ◽  
Sharath B S ◽  
Riaz Mahmood
Keyword(s):  
Molecular Dynamics ◽  
Antifungal Activity ◽  
Phytophthora Infestans ◽  
Protein Interaction ◽  
In Silico ◽  
Plant Pathogens ◽  
Effector Proteins ◽  
P Value ◽  
Iturin A ◽  
Protein Protein Interaction

Aim And Objectives: Phytophthora infestans (Mont.) de Bary, fungal pathogen it causes late blight, which results in devastating economic loss among the Solanaceae. The bacillus lipopeptides shows the antagonistic activity against the many plant pathogens, among bacillus lipopeptides Iturin A reported as the antifungal gene. Hence, to understand the in silico antifungal activity, we have selected gene iturin A (AXN89987) produced by Bacillus spp to check the molecular dynamics study with the effector proteins of the P. infestanse. In this concern known effectors proteins of P. infestans were subjected to the protein-protein interaction and followed by simulation. Material and Method: Iturin A gene was amplified using the soil bacterium Bacillus subtilis with gene specific primers. Cloned into pTZ 57R/T vector and confirmed by sequencing. To get better insight the protein model was developed for Iturin A using Modeller 9.17, also for the effector proteins by using PDB structure of ID 4MRT (Phosphopantetheine Transferase Sfp) and 1QR0 (4'-phosphopantetheinyl moiety of coenzyme A) as template it shares the identity 72% and expected P-value: 3e-121 respectively. The model quality was assessed using ProSA and PROCHECK programs. Results: The potency of modelled protein against effector proteins of P. infestans were evaluated in silico using the HADDOCK server and the results showed the high affinity of Iturin A toward the effector protein Host ATG8 (PDB-5L83). Finally, the simulation was performed to the docked conformation of Iturin A with Host ATG8 to further understand the stability of the complex using Desmond program. Conclusion: Altogether the protein-protein interaction and simulation study propose a new methodology and intern it also attempted to uncover possible antifungal activity of iturin A against effector proteins of P. infestans.

scholarly journals Phytophthora infestans RXLR-WY effector AVR3a associates with a Dynamin-Related Protein involved in endocytosis of a plant pattern recognition receptor

2014 ◽  
Author(s):  
Angela Chaparro-Garcia ◽  
Simon Schwizer ◽  
Jan Sklenar ◽  
Kentaro Yoshida ◽  
Jorunn I. B. Bos ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Cell Death ◽  
Phytophthora Infestans ◽  
Plant Pathogens ◽  
Defense Responses ◽  
Effector Proteins ◽  
Related Protein ◽  
Receptor Mediated Endocytosis ◽  
Molecular Patterns ◽  
Basal Immunity

Perception of pathogen associated molecular patterns (PAMPs) by cell surface localized pattern recognition receptors (PPRs), activates plant basal defense responses in a process known as PAMP/PRR–triggered immunity (PTI). In turn, pathogens deploy effector proteins that interfere with different steps in PTI signaling. However, our knowledge of PTI suppression by filamentous plant pathogens, i.e. fungi and oomycetes, remains fragmentary. Previous work revealed that BAK1/SERK3, a regulatory receptor of several PRRs, contributes to basal immunity against the Irish potato famine pathogen Phytophthora infestans. Moreover BAK1/SERK3 is required for the cell death induced by P. infestans elicitin INF1, a protein with characteristics of PAMPs. The P. infestans host-translocated RXLR-WY effector AVR3a is known to supress INF1-mediated defense by binding the E3 ligase CMPG1. In contrast, AVR3aKI-Y147del, a deletion mutant of the C-terminal tyrosine of AVR3a, fails to bind CMPG1 and suppress INF1 cell death. Here we studied the extent to which AVR3a and its variants perturb additional BAK1/SERK3 dependent PTI responses using the plant PRR FLAGELLIN SENSING 2 (FLS2). We found that all tested variants of AVR3a, including AVR3aKI-Y147del, suppress early defense responses triggered by the bacterial flagellin-derived peptide flg22 and reduce internalization of activated FLS2 from the plasma membrane without disturbing its nonactivated localization. Consistent with this effect of AVR3a on FLS2 endocytosis, we discovered that AVR3a associates with the Dynamin-Related Protein DRP2, a plant GTPase implicated in receptor-mediated endocytosis. Interestingly, DRP2 is required for ligand-induced FLS2 internalization but does not affect internalization of the growth receptor BRASSINOSTEROID INSENSITIVE 1 (BRI1). Furthermore, overexpression of DRP2 suppressed accumulation of reactive oxygen species triggered by PAMP treatment. We conclude that AVR3a associates with a key cellular trafficking and membrane-remodeling complex involved in immune receptor-mediated endocytosis and signaling. AVR3a is a multifunctional effector that can suppress BAK1/SERK3 mediated immunity through at least two different pathways.

scholarly journals Protein-protein interaction networks and protein-ligand docking: Contemporary insights and future perspectives

2021 ◽  
Vol 38 (1) ◽  
pp. 5-17
Author(s):  
Aleksandar Velesinović ◽  
Goran Nikolić
Keyword(s):  
Modeling And Simulation ◽  
Protein Interaction ◽  
In Silico ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Ligand Docking ◽  
In Vivo Models ◽  
Protein Protein Interaction ◽  
Protein Protein Interaction Networks ◽  
In Silico Methods

Traditional research means, such as in vitro and in vivo models, have consistently been used by scientists to test hypotheses in biochemistry. Computational (in silico) methods have been increasingly devised and applied to testing and hypothesis development in biochemistry over the last decade. The aim of in silico methods is to analyze the quantitative aspects of scientific (big) data, whether these are stored in databases for large data or generated with the use of sophisticated modeling and simulation tools; to gain a fundamental understanding of numerous biochemical processes related, in particular, to large biological macromolecules by applying computational means to big biological data sets, and by computing biological system behavior. Computational methods used in biochemistry studies include proteomics-based bioinformatics, genome-wide mapping of protein-DNA interaction, as well as high-throughput mapping of the protein-protein interaction networks. Some of the vastly used molecular modeling and simulation techniques are Monte Carlo and Langevin (stochastic, Brownian) dynamics, statistical thermodynamics, molecular dynamics, continuum electrostatics, protein-ligand docking, protein-ligand affinity calculations, protein modeling techniques, and the protein folding process and enzyme action computer simulation. This paper presents a short review of two important methods used in the studies of biochemistry - protein-ligand docking and the prediction of protein-protein interaction networks.

scholarly journals Correction: Identification of selective protein–protein interaction inhibitors using efficient in silico peptide-directed ligand design

2019 ◽  
Vol 10 (22) ◽  
pp. 5849-5850
Author(s):  
Andrew M. Beekman ◽  
Marco M. D. Cominetti ◽  
Samuel J. Walpole ◽  
Saurabh Prabhu ◽  
Maria A. O’Connell ◽  
...  
Keyword(s):  
Protein Interaction ◽  
In Silico ◽  
Ligand Design ◽  
Protein Protein Interaction

Correction for ‘Identification of selective protein–protein interaction inhibitors using efficient in silico peptide-directed ligand design’ by Andrew M. Beekman et al., Chem. Sci., 2019, DOI: 10.1039/c9sc00059c.

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