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Application of molecular docking and PSO-SVR intelligent approaches in antimalarial activity prediction of enantiomeric cycloguanil analogues.

A series of antifolate compounds, i.e. 1-(4-chlorophenyl)-6,6-dimethyl-1,3,5-triazine-2,4-diamine, or cycloguanil analogues, have shown effective inhibiting properties against Plasmodium falciparum dihydrofolate reductase (PfDHFR). In this work, the stereoselectivity of PfDHFR to the R and S enantiomer of cycloguanil analogues was obtained from molecular docking calculations and integrated into QSAR study to obtain a more accurate prediction model. Results indicate that PfDHFR can bind to cycloguanil analogues in the R and S enantiomers. Cycloguanil analogues with alkyl chain substituent prefer the R enantiomer over S because they do not experience steric hindrance with the Phe58 side chain, while cycloguanil analogues with phenol chain substituent prefer the S enantiomer over R because they do not experience steric hindrance with Leu46 and Met55 side chains. Particle swarm optimization and support vector regression were used to select relevant descriptors and generate the effective prediction model, with a high statistical significance level (r2 training = 0.941; r2 test = 0.884).

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