Characterization, in Vi tro and in Silico Approach for the Management of Nigrospora Leaf Blight Disease of Guava in Bangladesh

Abstract

The current study was conducted to detect the pathogenic fungus causing leaf blight disease of guava in Bangladesh, and to evaluate the effect of various physical factors on the fungal growth, in vitro disease management, and the prediction of potential phyto-compounds against the fungus through in silico technique. The fungus was isolated following the tissue planting method, and morphological and molecular characterization confirmed the fungal identity as Nigrospora chinensis . In vitro pathogenicity tests ascertained the pathogenic nature of the fungus. The optimum fungal growth was found on PDA medium at 25˚C temperature and pH 7 conditions. Among three commercial fungicides—Amistar top 325 SC and Kazim 80 WG showed complete growth inhibition of the fungus, and fungal antagonist Trichoderma ha rzianum showed above 70% growth inhibition in in vitro dual culture. The virtual screening results for the target protein Tef-1 revealed that seven phytocompounds had a higher binding affinity. Among them, lawsaritol of Lawsenia inermis and andrograpanin of Andrographis paniculata showed the highest outcomes (binding affinity −7.5 and −11.4 kcal mol − 1 ) than the control chemical fungicide carbendazim. The average root-mean-square deviation (RMSD) value of the protein backbone regarding lawsaritol, andrograpanin, and carbendazim was 2.588 Å, 1.807 Å, and 2.026 Å, respectively, and the root mean square fluctuation (RMSF) values were 3.89 Å, 5.65 Å, and 4.51 Å during molecular dynamic simulation. In silico studies reveal that two compounds can be potential biogenic fungicides against the concerned disease caused by N. chinensis . To the best of our knowledge, leaf blight disease of guava and in silico drug prediction against the fungus are reported for the first time in Bangladesh.