ABSTRACT
BACKGROUND: Plants of the Amaryllidaceae family have been under intense scrutiny for the presence of a couple of alkaloidal secondary metabolites with endued cytotoxic activity, such as pancratistatin (1), 7-deoxypancratistatin (2), narciclasine (3), 7-deoxynarciclasine (4), trans-dihydronarciclasine (5), and 7-deoxy-trans-dihydronarciclasine (6). Nevertheless, preclinical evaluation of these alkaloids has been put on hold because of the limited quantity of materials available from isolation. AIM: To explore the underlying cytotoxic molecular mechanisms of the Amaryllidaceae alkaloids (1-6) and to assess their absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiles using chemoinformatic tools. MATERIALS AND METHODS: AutoDock 4.0 software along with different in silico chemoinformatic tools, namely PharmMapper, Molinspiration, MetaPrint2D, and admetSAR servers, were used to assess the drugability of the Amaryllidaceae alkaloids (1-6). RESULTS: Deoxycytidine kinase (dCK) (PDB: 1P60) was predicted as a potential target with fitting score of 5.574. In silico molecular docking of (1-6) into dCK revealed good interactions, where interesting hydrogen bonds were observed with the amino acid residues-Gly-28 and Ser-35-located in the highly conserved P-loop motif. This motif plays a special role in dCK function. Contrary to (1), in silico pharmacokinetic results have shown good absorption and permeation and thus good oral bioavailability for (2-6). CONCLUSION: The in silico docking data have proposed that the reported cytotoxic activity of the Amaryllidaceae alkaloids (1-6) could be mediated through dCK inhibition. In addition, the ADMET profile of these alkaloids is promising and thus (1-6) could be candidates for future drug development.
ABSTRACT
A new CYP26A1 homology model was built based on the crystal structure of cyanobacterial CYP120A1. The model quality was examined for stereochemical accuracy, folding reliability, and absolute quality using a variety of different bioinformatics tools. Furthermore, the docking capabilities of the model were assessed by docking of the natural substrate all-trans-retinoic acid (atRA), and a group of known azole- and tetralone-based CYP26A1 inhibitors. The preferred binding pose of atRA suggests the (4S)-OH-atRA metabolite production, in agreement with recently available experimental data. The distances between the ligands and the heme group iron of the enzyme are in agreement with corresponding distances obtained for substrates and azole inhibitors for other cytochrome systems. The calculated theoretical binding energies agree with recently reported experimental data and show that the model is capable of discriminating between natural substrate, strong inhibitors (R116010 and R115866), and weak inhibitors (liarozole, fluconazole, tetralone derivatives).