Combined 3D-QSAR, molecular docking, ADMET, and drug-likeness scoring of novel diaminodihydrotriazines as potential antimalarial agents

Abstract

Plasmodium falciparum dihydrofolate reductase (PfDHFR) is a promising therapeutic target for antimalarial interventions. Diaminodihydrotriazine derivatives have demonstrated their efficacy as antimalarial agents by targeting PfDHFR inhibition. In this study, we used a multifaceted approach including 3D-QSAR, in silico pharmacokinetic/ADMET evaluation, molecular docking techniques, and molecular dynamics simulation to explore a series of diaminodihydrotriazine compounds, to identify new antimalarial drug candidates featuring the diaminodihydrotriazine scaffold. Using comparative molecular similarity indices analysis (CoMSIA), we built a robust 3D-QSAR model exhibiting favorable statistical parameters, with Q2 and R2 values of 0.553 and 0.981, respectively. External validation using a test set yielded an R2pre value of 0.787, confirming the model's predictive ability. In addition, we performed comprehensive ADMET and drug similarity profile analyses for potent designed compounds, yielding promising results. Molecular docking studies further complemented our investigation facilitating the elucidation of optimal interaction modes between these inhibitors and their target receptor. Additionally, molecular dynamics simulation was conducted for the promising compound 8a. This study not only provides valuable insights into the design of new antimalarial agents but also highlights the importance of computational methods for accelerating drug discovery processes, particularly in the context of infectious disease control.

Keywords

• Diaminodihydrotriazine
• PfDHFR
• 3D-QSAR
• ADMET
• Molecular docking