In search of the representative pharmacophore hypotheses of the enzymatic proteome of Plasmodium falciparum: a multicomplex-based approach
- 36 Downloads
Drug resistance has made malaria an untreatable disease and therefore intensified the need for the development of new drugs and the identification of potential drug targets. In this pursuit, in silico efforts made in the past have not shown significant responses. Therefore, in the present work, the multicomplex-based pharmacophore modeling approach was employed to construct the pharmacophores of the 16 selected Plasmodium falciparum (Pf) targets. All the constructed hypotheses (153) were screened against a focused dataset made up of experimental actives of the chosen targets (3705 inhibitors). The rationale was to check the affinity of the inhibitors for the off-targets. Subsequently, the constructed hypotheses from each target were pooled based on the feature types and the pooled-hypotheses were then clustered to offer an insight about the pharmacophore similarity. Tanimoto similarity index was also calculated to look for the similarity among the inhibitors belonging to different Pf targets. Overall, the work was accomplished to bid healthier perceptive of the pharmacophore-based virtual screening and abet in providing guiding principles for the construction of stringent pharmacophores that can be employed for the screening.
KeywordsMulticomplex-based pharmacophore Enzymatic proteome Clustering Tanimoto similarity Virtual screening
Anu Manhas and PCJ acknowledge Science and Engineering Research Board (SERB), Department of Science and Technology (DST) for project grant through grant number EMR/2016/003025. MY Lone acknowledges the University Grants Commission (UGC), Govt. of India for the financial assistance.
Compliance with ethical standards
Conflict of interest
The authors declared no competing interest.
- 2.World Health Organisation- WHO (2016) World malaria report 2015. WHO. http://www.who.int/malaria/publications/world-malaria-report-2015/report/en/. Accessed 19 April 2016
- 3.World Health Organisation- WHO (2015) Investing to overcome the global impact of neglected tropical diseases: 3rd WHO report on neglected tropical diseases, vol 3. World Health Organization-WHO, GenevaGoogle Scholar
- 9.World Health Organisation- WHO (2016) Malaria vaccine: WHO position paper- January 2016. Wkly Epidemiol Rec 91:33–52. http://apps.who.int/iris/bitstream/handle/10665/254285/wer9104_33-52.pdf?sequence=1&isAllowed=y. Accessed Jan 2016
- 19.Kirchmair J, Wolber G, Laggner C, Langer T (2006) Comparative performance assessment of the conformational model generators omega and catalyst: a large-scale survey on the retrieval of protein-bound ligand conformations. J Chem Inf Model 46:1848–1861. https://doi.org/10.1021/ci060084g CrossRefPubMedGoogle Scholar
- 20.Kirchmair J, Ristic S, Eder K, Markt P, Wolber G, Laggner C, Langer T (2007) Fast and efficient in silico 3D screening: toward maximum computational efficiency of pharmacophore-based and shape-based approaches. J Chem Inf Model 47:2182–2196. https://doi.org/10.1021/ci700024q CrossRefPubMedGoogle Scholar
- 22.Manhas A, Patel A, Lone MY, Jha PK, Jha PC (2018) Identification of PfENR inhibitors: a hybrid structure based approach in conjunction with molecular dynamics simulations. J Cell Biochem. https://doi.org/10.1002/jcb.27075
- 29.Accelrys Discovery Studio version 4.0, Accelrys, San Diego, USA. https://www.accelrys.com/products/collaborativescience/biovia-discovery-studio/