Exploration of the structural requirements of Aurora Kinase B inhibitors by a combined QSAR, modelling and molecular simulation approach

Abstract

Aurora kinase B plays an important role in the cell cycle to orchestrate the mitotic process. The amplification and overexpression of this kinase have been implicated in several human malignancies. Therefore, Aurora kinase B is a potential drug target for anticancer therapies. Here, we combine atom-based 3D-QSAR analysis and pharmacophore model generation to identify the principal structural features of acylureidoindolin derivatives that could potentially be responsible for the inhibition of Aurora kinase B. The selected CoMFA and CoMSIA model showed significant results with cross-validation values (q2) of 0.68, 0.641 and linear regression values (r2) of 0.971, 0.933 respectively. These values support the statistical reliability of our model. A pharmacophore model was also generated, incorporating features of reported crystal complex structures of Aurora kinase B. The pharmacophore model was used to screen commercial databases to retrieve potential lead candidates. The resulting hits were analyzed at each stage for diversity based on the pharmacophore model, followed by molecular docking and filtering based on their interaction with active site residues and 3D-QSAR predictions. Subsequently, MD simulations and binding free energy calculations were performed to test the predictions and to characterize interactions at the molecular level. The results suggested that the identified compounds retained the interactions with binding residues. Binding energy decomposition identified residues Glu155, Trp156 and Ala157 of site B and Leu83 and Leu207 of site C as major contributors to binding affinity, complementary to 3D-QSAR results. To best of our knowledge, this is the first comparison of WaterSwap field and 3D-QSAR maps. Overall, this integrated strategy provides a basis for the development of new and potential AK-B inhibitors and is applicable to other protein targets.

Identification of polypharmacological anticancerous molecules against Aurora kinase family of proteins

“…In the case of 3679‐AURK‐B docked complex, the molecule forms two hydrogen‐bonding interactions between the pyrazole nitrogen atom of 3679 and Glu155 and Ala157 amino acid residues of AURK‐B (Figure 2F). Glu155 and Ala157 mediated interactions were also observed in acyl derivatives of ZINC database compounds 51 . Heteroarene fused anthraquinone derivative (2‐benzyl‐4, 11‐dihydroxy‐1H‐anthra [2,3‐d]imidazole‐5,10‐dione (anthraimidazole 5)) was found to have similar interactions with AURK‐B 7 .…”

“…Glu155 and Ala157 mediated interactions were also observed in acyl derivatives of ZINC database compounds. 51 Heteroarene Molecule 5326 is stabilized by hydrogen bonding interactions mediated by Ala157 and Glu161 residues of AURK-B (Figure 2G). Molecule 7447 was found to form strong hydrogen-bonding interactions with Ala157 and Glu204 within the binding cavity of AURK-B (Figure 2H).…”

Pharmacophore Synergism in Diverse Scaffold Clinches in Aurora Kinase B

“…Therefore, the conditional occurrence of lipophilic atoms in the vicinity of H-bonding-capable atoms is a better choice. A plausible reason could be the composition of the active site of AKB, which consists of the persistent presence of lipophilic residues such as Gly, Leu, Val, Phe, etc., between the acidic or basic residues such as Glu, Asp, Lys [ 22 ]. This is why an aurora kinase B inhibitor also requires the presence of H-bond-capable atoms, preferably with separation by five bonds and the concomitant occurrence of lipophilic atoms in their vicinity.…”

“…The best developed QSAR model based on forty-one molecules had Q2LOO = 0.575. Likewise, Ashraf et al [ 22 ] used a dataset of 57 acylureidoindolin derivatives to develop a 3D-QSAR model, which had Q2LOO = 0.641, and indicated that electrostatic and hydrophobic fields determine the activity of compounds. Thus, AKB has been the subject of QSAR research; however, the developed QSAR models find little usage due to a lack of generalizability, low predictive power, being based on small datasets comprising limited scaffolds, or a combination of these factors.…”

Sesame oil ameliorates valproic acid-induced hepatotoxicity in mice: integrated in vivo–in silico study

“…Liver injury may be directly by the drug or its metabolites, or injury may result from the subsequent in ammatory reaction [4]. Many research focused on the pathophysiology of drug-induced toxicity mediated by reactive metabolites.…”