An insight into molecular interaction of PGIP with PG for banana cultivar

Kumar, Sunil; Dehury, Budheswar; Tandon, Gitanjali; Jaiswal, Sarika; Iquebal, Mir Asif; Ahmad, Khurshid; Nagrale, Dipak T.; Singh, Udai B.; Jha, Yachana; Singh, Mahender Kumar; Singh, Arjun; Rai, Anil; Paital, Biswaranjan; Kumar, Dinesh

doi:10.2741/4809

Cited by 10 publications

(3 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…MD simulations of glucanase-GTP complex were done to explore the stability, conformational flexibility and dynamic behavior of all-atoms [ 24 , 25 ]. Ligand topology was deduced from CHARMM general force field ( https://cgenff.umaryland.edu/ ) [ 26 ] and force fields of protein building was done using GROMACSv2019.4 package [ 27 ].…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Delineation of molecular interactions of plant growth promoting bacteria induced β-1,3-glucanases and guanosine triphosphate ligand for antifungal response in rice: a molecular dynamics approach

Jha

Dehury

Kumar³

et al. 2021

Mol Biol Rep

Self Cite

View full text Add to dashboard Cite

Background The plant growth is influenced by multiple interactions with biotic (microbial) and abiotic components in their surroundings. These microbial interactions have both positive and negative effects on plant. Plant growth promoting bacterial (PGPR) interaction could result in positive growth under normal as well as in stress conditions. Methods Here, we have screened two PGPR’s and determined their potential in induction of specific gene in host plant to overcome the adverse effect of biotic stress caused by Magnaporthe grisea, a fungal pathogen that cause blast in rice. We demonstrated the glucanase protein mode of action by performing comparative modeling and molecular docking of guanosine triphosphate (GTP) ligand with the protein. Besides, molecular dynamic simulations have been performed to understand the behavior of the glucanase-GTP complex. Results The results clearly showed that selected PGPR was better able to induce modification in host plant at morphological, biochemical, physiological and molecular level by activating the expression of β-1,3-glucanases gene in infected host plant. The docking results indicated that Tyr75, Arg256, Gly258, and Ser223 of glucanase formed four crucial hydrogen bonds with the GTP, while, only Val220 found to form hydrophobic contact with ligand. Conclusions The PGPR able to induce β-1,3-glucanases gene in host plant upon pathogenic interaction and β-1,3-glucanases form complex with GTP by hydrophilic interaction for induction of defense cascade for acquiring resistance against Magnaporthe grisea. Graphical abstract

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Molecular Dynamics Simulation Of Glucanase-gtp Complexmentioning

confidence: 99%

Delineation of molecular interactions of plant growth promoting bacteria induced β-1,3-glucanases and guanosine triphosphate ligand for antifungal response in rice: a molecular dynamics approach

Jha

Dehury

Kumar³

et al. 2021

Mol Biol Rep

Self Cite

View full text Add to dashboard Cite

show abstract

“…For example, bio-medical pathway studies, not only provide new insights, but also vast data [13,23,24]. Although many in silico tools are used to study bio-phenomena in cells [28][29][30][31], tools for handling data, as well as techniques for identification of drugs and their targets by in silico methods have gained momentum only lately. Most of the computational methods for analyzing drug-target interactions are based on receptor or ligand models.…”

Section: Introductionmentioning

confidence: 99%

Approaches for network based drug discovery

Jayachandran

Ilango

Paital

et al. 2021

Front. Biosci. (Schol Ed)

View full text Add to dashboard Cite

Introduction 3. Interaction of drug with target 4. Methods to study drug interaction 4.1 Molecular docking-based method 4.2 Pharmacophore-based method 4.3 Similarity-based method 4.4 Machine learning-based 4.5 Network based methods 5. Drug repositioning 6. Data sources for network construction 7. Side effects nbdd analysis 8. Drug discovery from medicinal plants by nbdds 9. Elucidation of molecular mechanisms by nbdds 10. Protein-protein interaction (PPI) networks 10.1 Analyses of PPI network 10.2 PPI characterization by in silico approaches 11. Integrated network-based methods 12. Conclusions 13. Ethics approval and consent to participate 14. Author contributions 15. Acknowledgment 16. Funding 17. Conflict of interest 18. References

show abstract

Application of Bioinformatics in the Plant Pathology Research

Satpathy¹

2022

Advances in Agricultural and Industrial Microbiology

View full text Add to dashboard Cite

An insight into molecular interaction of PGIP with PG for banana cultivar

Abstract: Figure 12. Comparative analyses of electrostatic surface potential of (A) bPGIP-EcPG, (B) PvPGIP2-EcPG and (C) mutant PvPGIP2-EcPG complexes. The structures are representative obtained from the top ranked cluster after clustering analysis.

Cited by 10 publications

References 44 publications

Delineation of molecular interactions of plant growth promoting bacteria induced β-1,3-glucanases and guanosine triphosphate ligand for antifungal response in rice: a molecular dynamics approach

Delineation of molecular interactions of plant growth promoting bacteria induced β-1,3-glucanases and guanosine triphosphate ligand for antifungal response in rice: a molecular dynamics approach

Approaches for network based drug discovery

Application of Bioinformatics in the Plant Pathology Research

Contact Info

Product

Resources

About