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This article is part of the supplement: 7th German Conference on Chemoinformatics: 25 CIC-Workshop

Open Access Poster presentation

Development of target focused library against drug target of P. falciparum using SVM and Molecular docking

Sangeetha Subramaniam1*, Monica Mehrotra2 and Dinesh Gupta1

Author Affiliations

1 Structural and Computational Biology, International Centre for Genetic Engineering and Biotechnology, Aruna Asaf Ali Marg, New Delhi, 110070, India

2 Department of Computer Science, Jamia Millia Islamia, New Delhi, 110025, India

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Journal of Cheminformatics 2012, 4(Suppl 1):P48  doi:10.1186/1758-2946-4-S1-P48

The electronic version of this article is the complete one and can be found online at: http://www.jcheminf.com/content/4/S1/P48


Published:1 May 2012

© 2012 Subramaniam et al; licensee BioMed Central Ltd.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Poster presentation

PfHslV, a homolog of β subunit of 20S proteasome forms the proteolytic core of the PfHslUV machinery in P. falciparum [1,2]. PfHslV has no homolog in the human host and it is a promising drug target essential to the plasmodial metabolism. The use of single proteasome inhibitor targeting these threonine proteases has a potential to be antimalarial drug candidate. One of our recent studies identified several promising inhibitors against 20S β5 subunit of P. falciparum [3]. The present study adopts a similar knowledge based virtual screening strategy using Support Vector Machines (SVM) and molecular docking to build a focused library of potential PfHslV inhibitors. SVM model has been trained using 170 molecular descriptors of 64 inhibitors and 208 putative non-inhibitors. The non-linear classifier based on Radial Basis Function (RBF) kernel yielded classification accuracy of 97%. The SVM model rapidly predicted inhibitors from NCI library and were subsequently docked in to the active site of an optimised three-dimensional model of PfHslV. The novel drug-like PfHslV inhibitors with very good binding affinity and novel scaffold can be a good starting point to develop new antimalarial drugs.

References

  1. Ramasamy G, Gupta D, Mohmmed A, Chauhan VS: Characterization and localization of Plasmodium falciparum homolog of prokaryotic ClpQ/HslV protease.

    Mol Biochem Parasitol 2007, 152:139-148. PubMed Abstract | Publisher Full Text OpenURL

  2. Subramaniam S, Mohmmed A, Gupta D: Molecular modeling studies of the interaction between Plasmodium falciparum HslU and HslV Subunits.

    J Biomol Struct Dyn 2009, 26:403-524. PubMed Abstract | Publisher Full Text OpenURL

  3. Subramaniam S, Mehrotra M, Gupta D: Support Vector Machine based prediction of P. falciparum proteasome inhibitors and development of focused library by molecular docking.

    Comb Chem High Throughput Screen 2011, 14(10):898-907. PubMed Abstract | Publisher Full Text OpenURL