Novel chemical scaffolds of the tumor marker AKR1B10 inhibitors discovered by 3D QSAR pharmacophore modeling

Abstract

Aim: Recent evidence suggests that aldo-keto reductase family 1 B10 (AKR1B10) may be a potential diagnostic or prognostic marker of human tumors, and that AKR1B10 inhibitors offer a promising choice for treatment of many types of human cancers. The aim of this study was to identify novel chemical scaffolds of AKR1B10 inhibitors using in silico approaches. Methods: The 3D QSAR pharmacophore models were generated using HypoGen. A validated pharmacophore model was selected for virtual screening of 4 chemical databases. The best mapped compounds were assessed for their drug-like properties. The binding orientations of the resulting compounds were predicted by molecular docking. Density functional theory calculations were carried out using B3LYP. The stability of the protein-ligand complexes and the final binding modes of the hit compounds were analyzed using 10 ns molecular dynamics (MD) simulations. Results: The best pharmacophore model (Hypo 1) showed the highest correlation coefficient (0.979), lowest total cost (102.89) and least RMSD value (0.59). Hypo 1 consisted of one hydrogen-bond acceptor, one hydrogen-bond donor, one ring aromatic and one hydrophobic feature. This model was validated by Fischer's randomization and 40 test set compounds. Virtual screening of chemical databases and the docking studies resulted in 30 representative compounds. Frontier orbital analysis confirmed that only 3 compounds had sufficiently low energy band gaps. MD simulations revealed the binding modes of the 3 hit compounds: all of them showed a large number of hydrogen bonds and hydrophobic interactions with the active site and specificity pocket residues of AKR1B10. Conclusion: Three compounds with new structural scaffolds have been identified, which have stronger binding affinities for AKR1B10 than known inhibitors.

A computational drug repurposing approach in identifying the cephalosporin antibiotic and anti-hepatitis C drug derivatives for COVID-19 treatment

“…The RMSD of protein backbone atoms and potential energy profiles obtained from the simulations indicate the overall stability of the simulated systems ( Supplementary Fig. S1 ) [ 39 ]. The RMSD values were between 0.15 nm to 0.36 nm for all the protein-drug complexes.…”

“…The RMSD values were between 0.15 nm to 0.36 nm for all the protein-drug complexes. Varying RMSD values at the initial few nanoseconds of the simulations indicate the initial adjustment of ligands at the active site of SARS-CoV-2 M pro [ 39 , 40 , 41 ]. The analysis indicated that each system reached steady-state after convergence, and RMSD values remained within the acceptable value of <0.3 nm except the M pro -Atorvastatin complex (0.36 nm) during the 50 ns simulation run [ 42 ].…”

New compounds identified through in silico approaches reduce the α-synuclein expression by inhibiting prolyl oligopeptidase in vitro

“…The molecular dynamics (MD) simulations of POP in a complex with inhibitors and final hit compounds were carried out with CHARMM27 all-atom force field using Groningen machine for chemical simulations (GROMACS 4.5.7) software 55 , as previously described 56 – 58 . The topology files for all ligands were generated using the SwissParam program 59 .…”

Pharmacophore-based virtual screening of catechol-o-methyltransferase (COMT) inhibitors to combat Alzheimer’s disease

“…The structure has a depth of resolution 2.8 Å and contains 216 amino acids, ligand 3, 5-dinitrocatechol (DNC), cofactor S-adenosyl L- methionine (SAM), and magnesium ion (Mg +2 ). Removal of water molecules, energy minimization (Kumar et al, 2015; Modi et al, 2016) were performed with the help of the standard steepest decent conjugate method in YASARA (Parmar, Patel, Highland, Pandya, & George, 2016). The 36 ligands from ZINC database (Irwin et al, 2012) were docked in the place of DNC, located at the binding site of COMT.…”