Application of SSIR Method for the Design of Fungicides
Source abstract
Abstract
The design of fungicides is a central topic in agricultural chemistry. In this manuscript, it is shown how the Superposition of Significant Interaction Rules (SSIR) method can serve the generation of new potentially active molecules. By using SSIR, it is shown how the process becomes a simple symbolic procedure without the intervention of sophisticated statistical methods, although the results obtained are comparable.
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Research context
OpenAlex topics: Pesticide Residue Analysis and Safety · Fungal Plant Pathogen Control · Agricultural Practices and Plant Genetics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Departamento de Química Física, Unidad de Investigación de Diseño de Fármacos y Conectividad Molecular, Facultad de Farmacia, Universitat de València, 46100 Burjassot, Spain
Institut de Química Computacional i Catàlisi (IQCC) and Departament de Química, Universitat de Girona, 17071 Girona, Spain
References (26)
Show source-provided references
1. Besalú, E., Prat, C., and Anticó, E. (2020). Investigation of volatiles in cork samples using chromatographic data and the superposing significant interaction rules (SSIR) chemometric tool. Biomolecules, 10.10.3390/biom10060896 ↗
2. Modeling binary fingerprint descriptors with the superposing significant interaction rules (SSIR) method
3. Besalú, E., and De Julián-Ortiz, J.V. (2020). Ranking series of cancer-related gene expression data by means of the Superposing Significant Interaction Rules method. Biomolecules, 10.10.3390/biom10091293 ↗
4. Molecular topology and QSAR multi-target analysis to boost the in silico research for fungicides in agricultural chemistry10.1007/s11030-018-9879-3 ↗
5. Molecular analysis of new sources of resistance to Pseudoperonospora cubensis (Berk. et Curt.) Rostovzev in cucumber10.1134/S1022795415090112 ↗
6. Coexistence of multiple endemic and pandemic lineages of the rice blast pathogen10.1128/mBio.01806-17 ↗
7. Biocontrol activity of recombinant aspartic protease from Trichoderma harzianum against pathogenic fungi10.1016/j.enzmictec.2018.02.002 ↗
8. Is the Emergence of Fungal Resistance to Medical Triazoles Related to Their Use in the Agroecosystems? A Mini Review10.1016/j.bjm.2016.06.006 ↗
9. Modeling Pesticides Toxicity to Sheepshead Minnow Using QSAR10.1016/j.ecoenv.2020.110352 ↗
10. QSAR Modeling the Toxicity of Pesticides against Americamysis Bahia10.1016/j.chemosphere.2020.127217 ↗
11. QSAR and Molecular Docking Studies of Novel 2,5-Distributed-1,3,4-Thiadiazole Derivatives Containing 5-Phenyl-2-Furan as Fungicides against Phythophthora Infestans10.1186/s43088-020-0037-5 ↗
12. Changing Trends in Discovery of New Fungicides: A Perspective10.1007/s42360-021-00411-6 ↗
13. Molecular Topology QSAR Strategy for Crop Protection: New Natural Fungicides with Chitin Inhibitory Activity10.1021/acsomega.0c00177 ↗
14. Study on Amphipathic Modification and QSAR of Volatile Turpentine Analogues as Value-Added Botanical Fungicides against Crop-Threatening Pathogenic Fungi10.1021/acssuschemeng.6b00236 ↗
15. Garcia-Pereira, I. (2022, October 18). Desmol2 Software, 2018, Department of Physical Chemistry. Faculty of Pharmacy, University of Valencia. Available online: http://desmol2.uv.es.
16. Besalú, E. (2016). Fast Modeling of Binding Affinities by Means of Superposing Significant Interaction Rules (SSIR) Method. Int. J. Mol. Sci., 17.10.3390/ijms17060827 ↗
17. Superposing Significant Interaction Rules (SSIR) method: A simple procedure for rapid ranking of congeneric compounds
18. Putz, M.V. (2010). On Plots in QSAR/QSPR methodologies. Quantum Frontiers of Atoms and Molecules, NOVA Publishing Inc.
19. Understanding and using sensitivity, specificity and predictive values10.4103/0301-4738.37595 ↗
20. Sensitivity, specificity, and predictive values: Foundations, pliabilities, and pitfalls in research and practice10.3389/fpubh.2017.00307 ↗
21. Wikipedia (2022, October 18). Available online: https://en.wikipedia.org/wiki/Positive_and_negative_predictive_values.
22. Wikipedia (2022, October 18). Available online: https://en.wikipedia.org/wiki/Sensitivity_and_specificity.
23. Egan, J.P. (1975). Signal Detection Theory and ROC Analysis, Academic Press.
24. The area above the ordinal dominance graph and the area below the receiver operating characteristic graph10.1016/0022-2496(75)90001-2 ↗
25. The meaning and use of the area under a receiver operating characteristic (ROC) curve10.1148/radiology.143.1.7063747 ↗
26. A method of comparing the areas under receiver operating characteristic curves derived from the same cases10.1148/radiology.148.3.6878708 ↗