In-vitro and in-silico analysis of methanolic crude extracts of Mountain knotgrass Aerva lanta (L.) against two lepidopteran pests and non-target species

Abstract

The present research investigates the toxicological screening of crude methanol extracts Avera lanata (Mx-Al) traditionally used for its medicinal properties, and explored its potential as an insecticidal agent against the lepidopteran pests Spodoptera litura Fab. and Plutella xylostella L. and their non-target impact on Eudrilis eugeniae. Chemical characterization of Mx-Al revealed thirteen phyto-compounds and the peak area percentage is maximum at β-D-mannofuranoside (33.96%) and 1-Tetradecyne (21.46%). The larvicidal toxicity of Mx-AI on S. litura (97.23%) and P. xylostella (96.21%) delivered dose-dependent mortality and was significant at 500 ppm. The minimal dosage (200 ppm) extended the larval and pupal durations and significantly reduced the level of ACP, ALP, and LDH against both pests. The non-target toxicity against earthworm displayed higher toxicity to Cypermethrin (0.1 ppm) as compared to Mx-AI (1500 ppm). Further, the In-silico screening showed that the interpretation has significant implications for developing new and more selective inhibitors for P. xylostella and S. litura. Also, Bee-Tox, pkCSM and insecticide-likeness showed that all derivatives of Mx-Al are mostly nontoxic against Bees, protozoa, and rodents respectively, and obeyed the TICE rule violations. Overall, the present results proved that Mx-Al is target specific and harmless to non-target organisms.

Keywords:

• Bio-rational
• phyto-compounds
• economical pest
• eco-toxicology
• structural modeling
• non-targets

Author contributions

K.K- Writing - original draft, Conceptualization, Formal analysis; M.J- Writing - original draft, Conceptualization, Formal analysis; P.V- Writing - original draft, Investigation, Supervision, Methodology; R.P- Conceptualization, Data curation, Methodology, Validation, Writing-review & editing; N.R- Formal analysis, Software, Investigation, Visualization, Writing-review & editing; M.K- Methodology, Data curation, Software, Visualization, Writing-review & editing; S.K- Conceptualization, Software, Formal analysis, Writing-review & editing; R.G- Software, Visualization, Validation; S.S-Project administration, Resources, Supervision and funding acquisition; S.G- Visualization, Validation; R.R- Visualization, Funding acquisition, Validation; Y.S.H- Software, Formal analysis, Writing-review & editing; and All authors have read and agreed to the published version of the manuscript.

Acknowlegdement

We thank Pavana K. Sivadasan Unni for her support in collection of samples. This work was supported by Korea Institute of Planning and Evaluation for Technology in Food, Agriculture and Forestry (IPET) through Agricultural Machinery/Equipment Localization Technology Development Program, funded by Ministry of Agriculture, Food and Rural Affairs(MAFRA) (no. 321055–05), and was also supported by Korea Institute of Planning and Evaluation for Technology in Food, Agriculture and Forestry (IPET) through Agriculture, Food and Rural Affairs Convergence Technologies Program for Educating Creative Global Leader Program, funded by Ministry of Agriculture, Food and Rural Affairs (MAFRA) (no. 321001–03). The authors acknowledge Researchers Supporting Project Number (RSP2023R465), King Saud University, Riyadh, Saudi Arabia, for funding this research. The research was also supported by the DST-FIST program under the grant no. (SR/FIST/LS-1/2019/522).

Disclosure statement

No potential conflict of interest was reported by the author(s).