Design of New Potent Insecticides of Organophosphate Derivatives Based on QSAR Analysis

Abstract

Design of new potent insecticide compounds of organophosphate derivatives based on QSAR (Quantitative Structure-Activity Relationship) analytical model has been conducted. Organophosphate derivative compounds and their activities were obtained from the literature. Computational modeling of the structure of organophosphate derivative compounds and calculation of their QSAR descriptors have been done by AM1 (Austin Model 1) method. The best QSAR model was selected from the QSAR models that used only electronic descriptors and from those using both electronic and molecular descriptors. The best QSAR model obtained was: r = 0.876, adjusted r 2 = 0.741, F cal /F tab = 9.636, PRESS = 2.414 x 10 -6) The best QSAR model was then used to design in silico new compounds of insecticide of organophosphate derivatives with better activity as compared to the existing synthesized organophosphate derivatives. So far, the most potent insecticide of organophosphate compound that has been successfully synthesized had log LD 50 of -5.20, while the new designed compound based on the best QSAR model, i.e.: 4-(diethoxy phosphoryloxy) benzene sulfonic acid, had log LD 50 prediction of -7.29. Therefore, the new designed insecticide compound is suggested to be synthesized and tested for its activity in laboratory for further verification. ABSTRAKTelah dilakukan desain senyawa insektisida baru turunan organofosfat berdasarkan pada model analisis Hubungan Kuantitatif Struktur-Aktivitas (HKSA). Senyawa turunan organofosfat dan aktivitasnya diperoleh dari literatur. Pemodelan komputasi terhadap struktur senyawa turunan organofosfat dan perhitungan deskriptor HKSAnya telah dilakukan menggunakan metode AM1 (Austin Model 1). Model HKSA terbaik dipilih dari model HKSA yang hanya menggunakan deskriptor elektronik dan dari model yang menggunakan baik deskriptor elektronik maupun molekul. Model HKSA terbaik yang diperoleh adalah: Log LD 50 = 50,735 qC6 + 83,115 qO7 (n = 30, r = 0,876, adjusted r 2 = 0,741, F cal /F tab = 9,636, PRESS = 2,414 x 10 -6 ) Model HKSA terbaik tersebut kemudian digunakan untuk merancang secara in silico senyawa insektisida baru turunan organofosfat yang mempunyai aktivitas lebih baik dibandingkan dengan turunan organofosfat yang sudah ada. Sejauh ini, insektisida organofosfat paling ampuh yang telah berhasil disintesis mempunyai log LD 50 sebesar -5,20, sedangkan senyawa baru yang telah dirancang berdasarkan model HKSA terbaik, yakni: asam 4-(diethoxy phosphoryloxy) benzena sulfonat mempunyai log LD 50 prediksi sebesar -7,29. Oleh karena itu, senyawa insektisida baru yang telah dirancang ini disarankan untuk disintesis dan diuji aktivitasnya di laboratorium untuk verifikasi lebih lanjut.

Characterization of acetylcholinesterase from elm left beetle, Xanthogaleruca luteola and QSAR of temephos derivatives against its activity

“…Compositions by this model was designed and tested in silicon. The results revealed that the insecticidal activity of newly synthesized compounds is greater than the existing insecticides [41]. Insecticidal effect of another class of derivatives was investigated on the AChE of housefly.…”

Binding organophosphate pesticides to acetylcholinesterase: risk assessment using the Monte Carlo method

“…They may have adverse impacts on various groups of soil microbes, wild animals, and also humans, through environmental contamination, or residues in food and feedstuff (Torres-Palma and Serna-Galvis 2018; Bora et al 2020;Toropov et al 2017Toropov et al , 2018. Experimental data on these chemicals can be used to improve the design of new pesticides, moving towards safer, greener substances, considering their adverse effects on humans and ecosystems (Mudasir et al 2013;Wibowo et al 2017). Furthermore, organophosphates are chemical warfare tools (Mendonca et al 2020).…”

Comparison between genetic algorithm‐multiple linear regression and back‐propagation‐artificial neural network methods for predicting the LD50 of organo (phosphate and thiophosphate) compounds

“…The best QSAR model showed that 74.1% of validation set was correctly predicted. [22] In a research, Hamadache and colleagues developed a validated QSAR model to predict acute oral toxicity of some pesticides to rats. [23] They found that the best results were obtained with the Quasi Newton back propagation (BFGS) algorithm Artificial Neural Network (ANN) model.…”

“…The correlation models between descriptors and insecticide activity were evaluated by multiple linear regression (MLR) analysis using software SPSS 13 on the Backward method. The best QSAR model showed that 74.1% of validation set was correctly predicted . In a research, Hamadache and colleagues developed a validated QSAR model to predict acute oral toxicity of some pesticides to rats .…”