3.9 Article

3D QSAR, pharmacophore and molecular docking studies of known inhibitors and designing of novel inhibitors for M18 aspartyl aminopeptidase of Plasmodium falciparum

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BMC STRUCTURAL BIOLOGY
卷 16, 期 -, 页码 -

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BMC
DOI: 10.1186/s12900-016-0063-7

关键词

Plasmodium falciparum; M18 aspartyl aminopeptidase; 3D QSAR; PLSR; PCR; kNN-MFA; Molecular docking; HTVS; Pharmacophore modeling

资金

  1. University Performance excellence-II funds (from University Grants Commission)
  2. Purse funds of Department of Science and Technology, Govt of India

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Background: The Plasmodium falciparum M18 Aspartyl Aminopeptidase (PfM18AAP) is only aspartyl aminopeptidase which is found in the genome of P. falciparum and is essential for its survival. The PfM18AAP enzyme performs various functions in the parasite and the erythrocytic host such as hemoglobin digestion, erythrocyte invasion, parasite growth and parasite escape from the host cell. It is a valid target to develop antimalarial drugs. In the present work, we employed 3D QSAR modeling, pharmacophore modeling, and molecular docking to identify novel potent inhibitors that bind with M18AAP of P. falciparum. Results: The PLSR QSAR model showed highest value for correlation coefficient r(2) (88 %) and predictive correlation coefficient (pred_r2) = 0.6101 for external test set among all QSAR models. The pharmacophore modeling identified DHRR (one hydrogen donor, one hydrophobic group, and two aromatic rings) as an essential feature of PfM18AAP inhibitors. The combined approach of 3D QSAR, pharmacophore, and structure-based molecular docking yielded 10 novel PfM18AAP inhibitors from ChEMBL antimalarial library, 2 novel inhibitors from each derivative of quinine, chloroquine, 8-aminoquinoline and 10 novel inhibitors from WHO antimalarial drugs. Additionally, high throughput virtual screening identified top 10 compounds as antimalarial leads showing G-scores -12.50 to -10.45 (in kcal/mol), compared with control compounds(G-scores -7.80 to -4.70) which are known antimalarial M18AAP inhibitors (AID743024). This result indicates these novel compounds have the best binding affinity for PfM18AAP. Conclusion: The 3D QSAR models of PfM18AAP inhibitors provided useful information about the structural characteristics of inhibitors which are contributors of the inhibitory potency. Interestingly, In this studies, we extrapolate that the derivatives of quinine, chloroquine, and 8-aminoquinoline, for which there is no specific target has been identified till date, might show the antimalarial effect by interacting with PfM18AAP.

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