In silico comparative genomics analysis of Plasmodium falciparum for the identification of putative essential genes and therapeutic candidates Subhashree Rout a , David Charles Warhurst b , Mrutyunjay Suar a , Rajani Kanta Mahapatra a, ⁎ a School of Biotechnology, KIIT University, Bhubaneswar 751024, Orissa, India b Department of Pathogen Molecular Biology, London School of Hygiene and Tropical Medicine, London, United Kingdom abstract article info Article history: Received 3 November 2014 Received in revised form 27 November 2014 Accepted 27 November 2014 Available online 5 December 2014 Keywords: P. falciparum Comparative genomics Drug targets Molecular docking A sequence of computational methods was used for predicting novel drug targets against drug resistant malaria parasite Plasmodium falciparum. Comparative genomics, orthologous protein analysis among same and other ma- laria parasites and protein–protein interaction study provide us new insights into determining the essential genes and novel therapeutic candidates. Among the predicted list of 21 essential proteins from unique pathways, 11 proteins were prioritized as anti-malarial drug targets. As a case study, we built homology models of two uncharacterized proteins using MODELLER v9.13 software from possible templates. Functional annotation of these proteins was done by the InterPro databases and from ProBiS server by comparison of predicted binding site residues. The model has been subjected to in silico docking study with screened potent lead compounds from the ZINC database by Dock Blaster software using AutoDock 4. Results from this study facilitate the selection of proteins and putative inhibitors for entry into drug design production pipelines. © 2014 Elsevier B.V. All rights reserved. 1. Introduction Malaria, the widespread tropical parasitic disease, needs new antimalarial drugs and vaccines urgently, particularly to prevent its deadly effects seen mostly in children and during pregnancy. In 2013, 97 countries had ongoing malaria transmission with an esti- mated 3.4 billion people currently at risk of malaria (World Health Organization, 2013). Five Plasmodium species, namely, Plasmodium falciparum, Plasmodium vivax, Plasmodium ovale, Plasmodium malariae, and Plasmodium knowlesi cause malaria in humans (Arama and Blomberg, 2014) among which P. falciparum is responsible for most morbidity and mortality (Miller et al., 2013). Current malaria chemo- therapies are subject to resistance, and now even the artemisinins are seen as possibly a fading hope (Andrews et al., 2014). There is a con- tinuous need to search for additional drug targets for better protection and long term effectiveness. This study employs computational approaches for finding suitable antimalarial drug targets through comparative metabolic pathway anal- ysis of pathogen and host. Essentiality of proteins of interest which are non-homologous to the human host can be predicted if the protein is found in falciparum and other malaria parasite proteomes (Ludin et al., 2012) and has a high functional association with other proteins there through protein–protein interaction network(s) (Kushwaha and Shakya, 2010). Despite the global importance of P. falciparum, most components of the pathogen proteome have not yet been characterized experimentally. In the present study we have made an attempt to deter- mine the structure and functions of some uncharacterized proteins computationally, as suitable drug targets. 2. Methods A systematic workflow was defined that involved several bioinfor- matics tools, databases and drug target prioritization parameters (Fig. 1), with the goal of obtaining information about the drug targets in the P. falciparum genome but absent in its host, therefore avoiding any potential side effects. 2.1. Identification of metabolic pathways of pathogen and host Metabolic pathway information of P. falciparum 3D7 and Homo sapi- ens was taken from the PlasmoDB (Yeh et al., 2004) and KEGG pathway databases (Kanehisa et al., 2010) respectively. Manual comparisons were made between pathogen and host pathways. Pathways which appeared in both host and pathogen were considered as common and those which did not were considered as unique in nature. 2.2. Identification of non-homologous proteins The corresponding protein sequences from unique pathways of pathogen were taken from the Uniprot database (Boeckmann et al., 2003) with reference to Uniprot accession number from PlasmoDB. They were subjected to a BLASTP search (Altschul et al., 1997) against Journal of Microbiological Methods 109 (2015) 1–8 ⁎ Corresponding author. Tel.: +91 9337627961. E-mail address: rmahapatra@kiitbiotech.ac.in (R.K. Mahapatra). http://dx.doi.org/10.1016/j.mimet.2014.11.016 0167-7012/© 2014 Elsevier B.V. All rights reserved. Contents lists available at ScienceDirect Journal of Microbiological Methods journal homepage: www.elsevier.com/locate/jmicmeth