In silico screening of natural product databases reveals new potential leads against neglected diseases

Infections with “protozoan” parasites, such as Malaria, Leishmaniasis or Trypanosomiasis cause tremendous suffering in wide parts of the world. Due to a lack of novel therapeutics, more research in this field is urgently required. Many natural products (NPs) have shown impressive activity while their mechanisms of action are mostly unknown. In this in silico study [1], structures of enzymes of major protozoan pathogens and NP databases have been studied to reveal new leads against these neglected diseases. Structures of NPs that had been tested against at least one major protozoan pathogen were extracted from literature (Pubmed [2]). The search was focused on phenolic plant constituents. Optimized 3D structures were collected in a database (1712 compounds; PheDB). A second database with 928 NPs published in [3] was created accordingly (NPDB). These two collections of potentially active substances were used for virtual screening. Structures of potential protein targets [3] were acquired from the Protein Databank [4]. Co-crystallized ligands were used to create pharmacophore queries which were employed for a virtual screening (VS) of the databases. The hits resulting from this VS were docked into the relevant enzymes' active centers. Docking-scores were compared to those of the co-crystallized ligands (CCL). About 40 enzymes were studied so far yielding promising results (better docking scores than CCL) for NPs of various classes (Table 1). Experimental validation, i.e. enzyme inhibition tests, have been initiated.

Tab. 1: Results of the virtual screening of different protozoal proteins

	T. brucei	T. cruzi	Leishmania ssp.	P. falciparum
Number of investigated	10	9	13	13
Number of hits (PheDB)	71	235	133	162
Number of hits (NPDB)	85	101	403	123
Most promising target	TbIGNH	TcHPRT	LmexGAPDH	PfENR
PDB-entry number	3FZ0	1TC1	1N1G	2OL4
PRS (%)* of the most promising ligand	154	174	222	146
*PRS (%)= Protein relevance score: Ratio in % between docking score for best docking ligand and co-crystalized ligand

References:

[1] For all calculations: Molecular Operating Environment 2011.10 (MOE), Chemical Computing Group, Montreal, Canada, http://www.chemcomp.com

[2] http://www.ncbi.nlm.nih.gov/pubmed/

[3] Schmidt, T.J. et al. Curr Med Chem. 2012; 19: 2128 – 75 and 2176 – 228.

[4] http://www.rcsb.org/pdb/home/home.do

This work is part of the activities of ResNetNPND: http://www.uni-muenster.de/ResNetNPND/

Support of CCG, Montreal, is gratefully acknowledged