AI Article Synopsis

  • The study explores new anti-malarial compounds derived from Thiaplakortone-A, identifying three key descriptors that correlate with their effectiveness through 2D QSAR analysis.
  • Validation methods confirmed the model's reliability and predictive power, with Q values indicating strong correlations in the CoMFA and CoMSIA models.
  • Molecular docking revealed favorable interactions with specific protein targets, while data mining and toxicity assessments suggested that several modified compounds are both effective against malaria and non-toxic.

Article Abstract

In this work, an attempt was made to propose new leads based on the natural scaffold Thiaplakortone-A active against malaria. The 2D QSAR studies suggested that three descriptors correlate with the anti-malarial activity with an R value of 0.814. Robustness, reliability, and predictive power of the model were tested by internal validation, external validation, Y-scrambling, and applicability domain analysis. HQSAR studies were carried out as an additional tool to find the sub-structural fingerprints. The CoMFA and CoMSIA models gave Q values of 0.813 and 0.647, and [Formula: see text] values of 0.994 and 0.984, respectively. Using the 2D-QSAR equation, the activity values of the seven modified compounds were calculated and it was found that three molecules showed good anti-malarial activity. Molecular docking of the 42 Thiaplakortone-A derivatives with Plasmodium falciparum calcium-dependent protein kinase 1 (PfCDPK1) was carried out to find out protein-ligand interactions. Data mining of the bioassay data-set AID: 504850 using the classifier based on Random Forest of Weka suggested that all of the eight molecules selected and three out of the seven virtual molecules were anti-malarial active. Both the virtual molecules and drug molecules were docked with CYP3A4, indicating that the virtual molecules could metabolize easily. Toxicity studies using Osiris shows that three molecules showed no toxic characters.

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http://dx.doi.org/10.1080/07391102.2016.1220870DOI Listing

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