Identification of the natural compound inhibitors against Plasmodium falciparum plasmepsin-II via common feature based screening and molecular dynamics simulations

Abstract

Malaria is counted amongst the deadly disease caused by Plasmodium falciparum. Recently, plasmepsin-II enzyme has gained much importance as an attractive drug target for the exploration of antimalarials. Therefore, the common feature pharmacophore models were generated from the crystallized complexes of the plasmepsin-II proteome. These models were subjected to a series of validation procedures, i.e. test set and Güner Henry studies to enlist the representative models. The selected representative hypotheses incorporating the most essential chemical features (common ZHHA) were screened against the natural product database to retrieve the potential candidates. To ensure the selection of the drug-like candidates, prior to screening, filtering steps (Drug-likeness and ADMET filters) were employed on the selected database. To study the interaction pattern of the candidates within the protein, these molecules were advanced to the molecular docking studies. Subsequently, based on the selected cut-off criteria obtained via redocking of the reference (4Z22), 15 compounds showed higher docking score (> −16.05 kcal/mol), and displayed the presence of hydrogen bonding with the crucial amino acids, i.e. Asp34 and Asp214. Further, the stability of the docked molecules was scrutinized via molecular dynamics simulations, and the results were compared with the reference compound 4Z22. All the docked compounds showed stable dynamics behaviour. Thus, in the present contribution, the combination of screening and stability procedures resulted in the identification of 15 hits that can serve as a new chemical space in the designing of the novel antimalarials.

Communicated by Ramaswamy H. Sarma

Keywords:

• Plasmepsin-II
• pharmacophore
• molecular docking
• molecular dynamic simulations
• drug-likeness

Disclosure statement

The authors declared no competing interest.

Additional information

Funding

Anu Manhas and Prakash C Jha acknowledge Science and Engineering Research Board (SERB), Department of Science and Technology (DST) for project grant through grant number EMR/2016/003025.