Computational approaches for the design of novel anticancer compounds based on pyrazolo[3,4-d]pyrimidine derivatives as trap1 inhibitor
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Date
2021
Journal Title
Journal ISSN
Volume Title
Publisher
MPDI
Abstract
In the present in-silico study, various computational techniques were applied to determine
potent compounds against TRAP1 kinase. The pharmacophore hypothesis DHHRR_1 consists of
important features required for activity. The 3D QSAR study showed a statistically significant model
with R2 = 0.96 and Q2 = 0.57. Leave one out (LOO) cross-validation (R2 CV = 0.58) was used to
validate the QSAR model. The molecular docking study showed maximum XP docking scores
(−11.265, −10.532, −10.422, −10.827, −10.753 kcal/mol) for potent pyrazole analogs (42, 46, 49, 56,
43), respectively, with significant interactions with amino acid residues (ASP 594, CYS 532, PHE 583,
SER 536) against TRAP1 kinase receptors (PDB ID: 5Y3N). Furthermore, the docking results were
validated using the 100 ns MD simulations performed for the selected five docked complexes. The
selected inhibitors showed relatively higher binding affinities than the TRAP1 inhibitor molecules
present in the literature. The ZINC database was used for a virtual screening study that screened
ZINC05297837, ZINC05434822, and ZINC72286418, which showed similar binding interactions to
those shown by potent ligands. Absorption, distribution, metabolism, and excretion (ADME) analysis
showed noticeable results. The results of the study may be helpful for the further development of
potent TRAP1 inhibitors.
Description
Keywords
TRAP1 kinase, Virtual screening, Molecular dynamics simulations, Pharmacophore modeling, TRAP1 inhibitors
Citation
Ali, A. et al. (2021). Computational approaches for the design of novel anticancer compounds based on pyrazolo[3,4-d]pyrimidine derivatives as trap1 inhibitor. Molecules, 26(18),5482. https:// doi.org/10.3390/molecules26195932