Identification and Validation of a Potent Dual Inhibitor of the P. falciparum M1 and M17 Aminopeptidases Using Virtual Screening

Chiara Ruggeri, Nyssa Drinkwater, Komagal Kannan Sivaraman, Rebecca S. Bamert, Sheena McGowan, Alessandro Paiardini, Juan Carlos Pizarro
2015 PLoS ONE  
The Plasmodium falciparum PfA-M1 and PfA-M17 metalloaminopeptidases are validated drug targets for the discovery of antimalarial agents. In order to identify dual inhibitors of both proteins, we developed a hierarchical virtual screening approach, followed by in vitro evaluation of the highest scoring hits. Starting from the ZINC database of purchasable compounds, sequential 3D-pharmacophore and molecular docking steps were applied to filter the virtual 'hits'. At the end of virtual screening,
more » ... 2 compounds were chosen and tested against the in vitro aminopeptidase activity of both PfA-M1 and PfA-M17. Two molecules showed significant inhibitory activity (low micromolar/nanomolar range) against both proteins. Finally, the crystal structure of the most potent compound in complex with both PfA-M1 and PfA-M17 was solved, revealing the binding mode and validating our computational approach. One pathway that has attracted the attention of antimalarial drug discovery efforts is the catabolism of erythrocyte hemoglobin, which is catalyzed by several enzymes and therefore presents a number of potential therapeutic targets [3] . Among these novel targets are the aminopeptidase enzymes that remove N-terminal amino acids from short peptides with high specificity. The P. falciparum alanyl aminopeptidase, PfA-M1, and leucyl aminopeptidase, PfA-M17, act in concert to mediate the final stages of hemoglobin digestion [5, 6] . PfA-M1 has broad substrate specificity, preferentially cleaving P1 residues Leu, Ala, Arg and Lys; however, it can also cleave Phe, Tyr, Asn and Ser [7] . In contrast, PfA-M17 demonstrates a restricted specificity for Leu and, to a lesser extent, Ala [8, 9] . The active sites of PfA-M1 and PfA-M17 coordinate essential zinc ions that are required for the catalytic mechanism. PfA-M1 coordinates a single zinc metal ion, while PfA-M17 contains two metal binding sites [10] . The two aminopeptidases are each encoded by non-homologous genes and have been validated in vitro and in vivo as drug targets, as inhibition of their activity can control both murine and laboratory malaria parasites [10] . Previous work within our group has identified potent dual inhibitors of the enzymes [7, 9, [11] [12] [13] [14] , which bind via coordination of the zinc ions by a zinc binding group (ZBG). Virtual screening is now established as a valuable tool in early drug discovery, allowing fast and economical selection of "hit" molecules before, subsequent experimental validation of the virtual hits. This biological validation is absolutely required; indeed, in recent years several virtual screening campaigns have been undertaken, with many papers reporting "hits" from virtual screens that haven't been evaluated experimentally [15, 16] . Virtual screening can add significant value to a drug discovery campaign; however, it demands careful attention to methodology with regard to design, validation and experimental confirmation of the computational results. We were interested to evaluate whether a virtual screening study could identify novel molecules that are capable of dual inhibitors of both PfA-M1 and PfA-M17. To this end, we undertook a virtual screen of the ZINC database of purchasable subsets (~18 millions of compounds) [17, 18] and used successive 3D-pharmacophore and molecular docking to filter the virtual 'hits'. Our screen identified 12 compounds that satisfied both the 3D-pharmacophore and docking requirements. We investigated the inhibitory properties of the 12 compounds against the aminopeptidase activity of both PfA-M1 and PfA-M17 in vitro, and demonstrated that that two compounds were dual PfA-M1/PfA-M17 inhibitors. Finally, we determined the crystal structures of the most potent hit in complex with both PfA-M1 and PfA-M17. Despite some discrepancy between the predicted and experimentally determined poses of the most potent hit, the obtained results demonstrate that, overall, the presented virtual screening protocol was able to effectively identify dual inhibitors for PfA-M1 and PfA-M17. Materials and Methods Structure-based virtual screening Generation of a structure-based pharmacophore model. The structure-based pharmacophore model was generated using LigandScout software package v.3.0 [19] . The models were generated from PDB codes 3EBH and 3EBI for PfA-M1, and 3KR4 and 3KR5 for PfA-M17 [6-9]. We superposed the two inhibitors bestatin and hPheP[CH 2 ]Phe for both drug targets and generated a shared-features 3D pharmacophore. The pharmacophore model was validated by screening with a manually generated database of compounds having bestatin and hPheP[CH 2 ] Phe seeded into 100 decoys from DUD-E decoy compounds database [20] . During the initial validation step, the first generated pharmacophore model was associated with poor performance. Therefore, pharmacophore maps were manually modified by systematically including/
doi:10.1371/journal.pone.0138957 pmid:26406322 pmcid:PMC4583420 fatcat:5m4khtw3jrd3rodj4vpnmt3aai