Malaysian Journal of Analytical Sciences Vol 26 No 3 (2022): 457 - 477

 

 

 

 

Quantitative structure-activity relationship (QSAR) study of newly synthesized carbonyl thiourea derivatives on Acanthamoeba sp.

 

(Kajian Kuantitatif Hubungan Struktur-Aktiviti (QSAR) Terhadap Terbitan Karbonil Tiourea Hasilan Sintesis Baru Terhadap Acanthamoeba sp.)

 

Maizatul Akma Ibrahim¹*, Nor Hafizah Zakaria¹, Mohd Sukeri Mohd Yusof²

 

¹Department of Plant Science, Kulliyyah of Science,

International Islamic University Malaysia, Bandar Indera Mahkota, 25200 Kuantan, Pahang, Malaysia

²Faculty of Science and Marine Environment,

Universiti Malaysia Terengganu, 21030 Kuala Nerus, Terengganu, Malaysia.

 

*Corresponding author:  maizatulakma@iium.edu.my

 

 

Received: 3 December 2021; Accepted: 23 March 2022; Published:  27 June 2022

 

 

Abstract

This research aims to build a mathematical quantitative structure-activity relationship (QSAR) model, which could relate the relationship between newly-synthesized carbonyl thiourea derivatives with their anti-amoebic activities. Therefore, in this study, inhibition concentration of 50% cells population (IC₅₀) was evaluated for 44 carbonyl thiourea derivatives on pathogenic Acanthamoeba sp. (Hospital Kuala Lumpur isolate). QSAR analysis was conducted using the obtained IC₅₀ data with additional 4 thiourea compounds of the same group from our previous work by applying three linear regression techniques namely stepwise-MLR, GA-MLR, and GA-PLS. Results showed that these thiourea derivatives are positively active against the tested Acanthamoeba sp. with IC₅₀ values ranging from 2.56 to 7.81 µg/mL. From the evaluation of the obtained models, the GA-PLS technique is found to be the best model due to its best predictive ability. The final equation of GA-PLS model gave good statistical output with values of r² = 0.827, r²_cv = 0.682 RMSEC=0.047, RMSECV=0.064, and r²_test =0.790 and RMSEP=0.051. Y-randomization test has confirmed that the model did not occur from the chance of correlation with r² = 0.015-0.372. Small residual with values less than 0.25 from the prediction in the test set proves the robustness of the model. The information generated from this study will provide an insight into designing a new lead compound from carbonyl thiourea containing highly potential anti-amoebic properties.

 

Keywords:  thiourea derivatives, Acanthamoeba sp., IC₅₀, anti-amoebic activity, QSAR models

 

Abstrak

Kajian ini mensasarkan pembinaan model matematik kuantitatif hubungan struktur-aktiviti (QSAR) yang memberi hubungkait antara terhadap terbitan karbonil tiourea hasilan sintesis baru dengan aktiviti anti-amebik. Oleh itu, kepekatan penghambatan 50% populasi sel (IC₅₀) dikaji ke atas 44 sebatian karbonil tiourea terhadap Acanthamoeba sp. (Hospital Kuala Lumpur isolat) berstatus patogenik. Analisa hubungan struktur-aktiviti kuantitatif dijalankan menggunakan data IC₅₀ yang diperolehi bersama 4 sebatian tambahan kumpulan sama dari hasil kerja kami sebelum ini, dengan mengaplikasi tiga teknik regresi linear, iaitu stepwise-MLR, GA-MLR dan GA-PLS dijalankan. Hasil kajian menunjukkan bahawa sebatian tiourea ini aktif secara positif terhadap Acanthamoeba sp.yang diuji dengan nilai IC₅₀ antara 2.56 hingga 7.81 µg/mL. Penilaian terhadap semua model QSAR yang dibina dalam kajian ini menunjukkan teknik GA-PLS adalah model yang terbaik kerana kemampuan ramalannya yang terbaik. Persamaan akhir untuk model GA-PLS menunjukkan output statistik yang baik dengan nilai r² = 0.827, r²_cv = 0.682, RMSEC = 0.047, RMSECV = 0.064, r²_test = 0.790 dan RMSEP = 0.051. Ujian perawakan-y mengesahkan bahawa model tersebut tidak terhasil secara kebetulan dengan r² = 0.015-0.372. Baki kecil dengan nilai kurang dari 0.25 dari ramalan set ujian membuktikan kekuatan model tersebut. Data terbina dari kajian ini akan memberi maklumat untuk mencipta sebatian penting baru dari tiourea karbonil yang mempunyai aktiviti anti-amebik yang berpotensi tinggi.

 

Kata kunci:  tiourea terbitan, Acanthamoeba sp., IC₅₀, aktiviti anti-amebik, model QSAR

 

 

Graphical Abstract

 

 

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