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Quantum probability ranking principle for ligand-based virtual screening

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Abstract

Chemical libraries contain thousands of compounds that need screening, which increases the need for computational methods that can rank or prioritize compounds. The tools of virtual screening are widely exploited to enhance the cost effectiveness of lead drug discovery programs by ranking chemical compounds databases in decreasing probability of biological activity based upon probability ranking principle (PRP). In this paper, we developed a novel ranking approach for molecular compounds inspired by quantum mechanics, called quantum probability ranking principle (QPRP). The QPRP ranking criteria would make an attempt to draw an analogy between the physical experiment and molecular structure ranking process for 2D fingerprints in ligand based virtual screening (LBVS). The development of QPRP criteria in LBVS has employed the concepts of quantum at three different levels, firstly at representation level, this model makes an effort to develop a new framework of molecular representation by connecting the molecular compounds with mathematical quantum space. Secondly, estimate the similarity between chemical libraries and references based on quantum-based similarity searching method. Finally, rank the molecules using QPRP approach. Simulated virtual screening experiments with MDL drug data report (MDDR) data sets showed that QPRP outperformed the classical ranking principle (PRP) for molecular chemical compounds.

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Acknowledgements

This work is supported by the Ministry of Higher Education (MOHE) and the Research Management Centre (RMC) at the Universiti Teknologi Malaysia (UTM) under the Fundamental Research Grant Scheme (FRGS) Category (VOT R.J130000.7828.4F741). We also would like to thank MIS-MOHE for sponsoring the first author.

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Authors and Affiliations

  1. Faculty of Computing, Universiti Teknologi Malaysia, Skudia, 81310, Malaysia

    Mohammed Mumtaz Al-Dabbagh, Naomie Salim, Mubarak Himmat & Faisal Saeed

  2. Faculty of Engineering, Karary University, Khartoum, 12304, Sudan

    Ali Ahmed

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  1. Mohammed Mumtaz Al-Dabbagh
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  2. Naomie Salim
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  3. Mubarak Himmat
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  4. Ali Ahmed
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  5. Faisal Saeed
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Correspondence to Mohammed Mumtaz Al-Dabbagh.

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Al-Dabbagh, M.M., Salim, N., Himmat, M. et al. Quantum probability ranking principle for ligand-based virtual screening. J Comput Aided Mol Des 31, 365–378 (2017). https://doi.org/10.1007/s10822-016-0003-4

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  • DOI: https://doi.org/10.1007/s10822-016-0003-4

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