DESIGN OF LOW CYTOTOXICITY DIARYLANILINE DERIVATIVES BASED ON QSAR RESULTS: AN APPLICATION OF ARTIFICIAL NEURAL NETWORK MODELLING

Ihsanul Arief,Bambang Setiaji,Muhammad Fachrie,Ria Armunanto

doi:10.20884/1.jm.2016.11.2.242

Ihsanul Arief, Bambang Setiaji + Show 2 more

Open Access

https://doi.org/10.20884/1.jm.2016.11.2.242

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Abstract

Study on cytotoxicity of diarylaniline derivatives by using quantitative structure-activity relationship (QSAR) has been done. The structures and cytotoxicities of diarylaniline derivatives were obtained from the literature. Calculation of molecular and electronic parameters was conducted using Austin Model 1 (AM1), Parameterized Model 3 (PM3), Hartree-Fock (HF), and density functional theory (DFT) methods. Artificial neural networks (ANN) analysis used to produce the best equation with configuration of input data-hidden node-output data = 5-8-1, value of r2 = 0.913; PRESS = 0.069. The best equation used to design and predict new diarylaniline derivatives. The result shows that compound N1-(4′-Cyanophenyl)-5-(4″-cyanovinyl-2″,6″-dimethyl-phenoxy)-4-dimethylether benzene-1,2-diamine) is the best-proposed compound with cytotoxicity value (CC50) of 93.037 μM.

Highlights

Toxicity is still a major safety concern for drug withdrawal, the 'black box warning', and the discontinuation of clinical trials
The failure rate becomes even higher when all drug candidates in preclinical research are Design of Low Cytotoxicity Diarylaniline Derivatives included in the statistics
QSAR method conducts a study of a relationship between molecular and electronic parameters of the activity or toxicity in the series of analog compounds

Summary

INTRODUCTION

Toxicity is still a major safety concern for drug withdrawal, the 'black box warning', and the discontinuation of clinical trials (such as Pfizer's hypercholesterolemia drug torcetrapib withdrawal from Phase III). QSAR method conducts a study of a relationship between molecular and electronic parameters of the activity or toxicity in the series of analog compounds. Their results are promising, which have the lower value of EC50 and higher value of CC50 than the control drug (rilpivirine). In this study, we performed QSAR modeling on cytotoxicities of DAAN derivatives to design the new compound with the lower cytotoxicity

COMPUTATIONAL METHODS Data Set

Rilpivirine

AND DISCUSSION

CONHCH2CH3 CH2CH2CN

Findings

CONCLUSION