Frontiers in Chemistry (Apr 2021)
Synthesis, Biological Evaluation, and QSAR Studies of 3-Iodochromone Derivatives as Potential Fungicides
Abstract
Despite the emergence of novel biotechnological and biological solutions, agrochemicals continue to play an important role in crop protection. Fungicide resistance is becoming a major problem; numerous cases of fungicide resistance have occurred worldwide in the last decade, resulting in the loss of several fungicides. The discovery of new molecules has therefore assumed critical importance in crop protection. In our quest for biologically active molecules, we herein report the synthesis of a series of twenty-one 3-Iodochromone derivatives (4a–4u), in a two-step process by condensation of 2-hydroxyacetophenone derivatives (2a–2u) with N,N-dimethylformamidedimethylacetal yielding enaminones (3a–3u), followed by cyclization with iodine to corresponding 3-iodochromones. Characterization of these compounds was done by IR, 1H NMR, 13C NMR, and LC-HRMS techniques. All synthesized compounds were screened for their fungicidal activity against Sclerotium rolfsii. Among these 6,8-Dichloro-3-iodochromone 4r was found to be most active (ED50 = 8.43 mg L−1). 2D-Quantitative Structural Activity Relationship (2D-QSAR) analysis was also performed by generating three different models viz., Multiple Linear Regression (MLR, Model 1), Principal Component Regression (PCR, Model 2), and Partial Least Squares (PLS, Model 3). Predictive power and statistical significance of these models were assessed with external and internal validation and leave one-out cross-validation was used for verification. In QSAR study, MLR (Model 1) was found to be best having correlation coefficient (r2) 0.943, cross-validated correlation coefficient (q2) 0.911 and r2pred 0.837. It was observed that DeltaEpsilonC, T_2_Cl_6, T_2_F_6, T_T_F_3, and ZCompDipole are the major descriptors which influence the fungicidal activity of 3-Iodochromone derivatives. The physicochemical parameters were estimated by the VLifeMDS 4.6 software. The QSAR study results will be helpful for structure optimization to improve the activity.
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