DOI: 10.14457/tu.the.2018.865
title: Antimalarial activity prediction of enantiomeric cycloguanil analogues using extremely randomized trees and particle swarm optimized-support vector regression intelligent approaches

description: A series of antimalarial drugs, 1-(4-chlorophenyl)-6,6-dimethyl-1,3,5-triazine-2,4-diamine or cycloguanil (CYC) analogues have shown to effectively inhibit the Plasmodium falciparum dihydrofolate reductase (PfDFHR). CYC analogues have an asymmetric carbon atom which provide possible two stereoisomers, (R) and (S) enantiomers. These enantiomers are mirror images and cannot superposition of each other (not identical). There have not been reports on the stereochemistry of the CYC analogues, and this is considered important because the pure enantiomeric form of a chiral drug can exert desirable, and non-desirable responses on the human body or both. The enantiomeric study of these compounds will provide essential information to evaluate their clinical safety and/or effectiveness. In this work, the stereoselectivity of PfDHFR to the (R) and (S) enantiomer of CYC analogues was obtained from molecular docking calculations and integrated into quantitative structure-activity relationship (QSAR) study to obtain a more accurate prediction model. Three-dimensional structures of 50 CYC analogues in (R) and (S) configuration were constructed and minimized using the density functional theory M062X/6-31G(d,p) level. Molecular Operating Environment (MOE) program was used to calculate 336 molecular descriptor values of each CYC analogues. A set of 188 descriptors has 2D molecular descriptors which are the same values for (R) and (S) enantiomer. A set of 148 descriptors has 3D molecular descriptors and most of them have different values for the two enantiomers of each molecule. Their structures were docked into the binding pocket of the crystal structure of PfDHFR. Results indicate that the PfDHFR is enantioselective towards enantiomeric CYC analogues. CYC analogues with an alkyl chain substituent prefers the (R) enantiomer over (S) enantiomer because it does not experience steric hindrance with the Phe58 side chain, while CYC analogues with phenol chain substituent prefer the (S) enantiomer over (R) enantiomer because it does not experience steric hindrance with Leu46 and Met55 side chains. The preferred individual configurations of each enantiomeric CYC analogue and their docking binding energy are used to develop the QSAR model using extremely randomized trees and particle swarm optimized-support vector regression (PSO-SVR) intelligent approaches. The CYC dataset comprises 38 analogues and 12 analogues in the training and test set, respectively, with an antimalarial binding energy span from -12.81 to -7.38 kcal mol^-1. The extremely randomized trees build multiple decision trees and merges them together to get a more accurate and stable prediction of antimalarial activity of CYC analogues (R^2= 0.973; R^2_test = 0.823). Without hyper-parameter tuning, it is very easy to measure the relative importance of four features on the prediction model, which are descriptors related to the electrostatic interactions. The great disadvantage is that the overfitting percentage of all QSAR models obtained from the extremely randomized trees calculations have exceeded 50% with the leave-one-out cross validation (Q^2) less than 0.5. Particle swarm optimized (PSO) and support vector regression (SVR) were used to select relevant descriptors and generate the effective prediction model, with a high statistical significance level. PSO is a population-based optimization method and SVR is a hyper-parameter tuning technical that used orthogonal transformation to convert the original data set into a high dimensional space (a space for all possible combinations of predictive variables). Using four 2D molecular descriptors related to the electrostatic interactions and two 3D molecular descriptors (the heat of formation and the highest occupied molecular orbital) with docking binding energy yields the best QSAR model for antimalarial prediction of CYC analogues with R^2= 0.941, Q^2= 0.774, and R^2_test= 0.884. This work firstly reported the integration information about the stereoselectivity of PfDHFR to (R) and (S) enantiomer of CYC analogues into a QSAR study to obtain a more accurate prediction model which may provide useful insight towards the design of chiral antimalarial inhibitors. When both enantiomers are active in malaria treatment, but one cause adverse side effects, an enantiopure can be used instead of racemate of that compound.