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Dynamic ligand-based pharmacophore modeling and virtual screening to identify mycobacterial cyclopropane synthase inhibitors

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Abstract

Multidrug resistance in Mycobacterium tuberculosis (M. Tb) and its coexistence with HIV are the biggest therapeutic challenges in anti-M. Tb drug discovery. The current study reports a Virtual Screening (VS) strategy to identify potential inhibitors of Mycobacterial cyclopropane synthase (CmaA1), an important M. Tb target considering the above challenges. Five ligand-based pharmacophore models were generated from 40 different conformations of the cofactors of CmaA1 taken from molecular dynamics (MD) simulations trajectories of CmaA1. The screening abilities of these models were validated by screening 23 inhibitors and 1398 non-inhibitors of CmaA1. A VS protocol was designed with four levels of screening i.e., ligand-based pharmacophore screening, structure-based pharmacophore screening, docking and absorption, distribution, metabolism, excretion and the toxicity (ADMET) filters. In an attempt towards repurposing the existing drugs to inhibit CmaA1, 6,429 drugs reported in DrugBank were considered for screening. To find compounds that inhibit multiple targets of M. Tb as well as HIV, we also chose 701 and 11,109 compounds showing activity below 1 μM range on M. Tb and HIV cell lines, respectively, collected from ChEMBL database. Thus, a total of 18,239 compounds were screened against CmaA1, and 12 compounds were identified as potential hits for CmaA1 at the end of the fourth step. Detailed analysis of the structures revealed these compounds to interact with key active site residues of CmaA1.

The paper presents generation of dynamic ligand-based pharmacophore model for Mycobacterial cyclopropane synthase and their validation. Aiming towards drug repositioning and selection of multi-target inhibitors, selected compounds from DrugBank and ChEMBL have been screened by a four-step virtual screening using the models and 12 potential compounds are identified.

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Acknowledgements

CC thanks Department of Science and Technology (DST), New Delhi for financial assistance through INSPIRE fellowship. UDP thanks DAE-BRNS for financial assistance. GNS thanks CSIR, New Delhi for financial support in the form of XII five year project (GENESIS).

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Authors and Affiliations

  1. Centre for Molecular Modelling, Indian Institute of Chemical Technology, Hyderabad, India

    CHINMAYEE CHOUDHURY & G NARAHARI SASTRY

  2. Centre for Computational Natural Sciences and Bioinformatics, International Institute of Information and Technology, Hyderabad, India

    CHINMAYEE CHOUDHURY & U DEVA PRIYAKUMAR

Authors
  1. CHINMAYEE CHOUDHURY
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  2. U DEVA PRIYAKUMAR
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  3. G NARAHARI SASTRY
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Correspondence to U DEVA PRIYAKUMAR.

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Supplementary Information (SI)

Scheme S1 showing the reference CmaA1 inhibitors, List S1 gives the details of the dataset download and preparation, table S1 giving the details (number of compounds matched, docking and fitness scores, etc.) of all the ligand-based pharmacophore models, table S2–S5 giving the docking scores and QuickProp Descriptors of all screened compounds and List S2 giving the descriptions of the Quickprop descriptors are provided at www.ias.ac.in/chemsci.

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CHOUDHURY, C., PRIYAKUMAR, U.D. & SASTRY, G.N. Dynamic ligand-based pharmacophore modeling and virtual screening to identify mycobacterial cyclopropane synthase inhibitors. J Chem Sci 128, 719–732 (2016). https://doi.org/10.1007/s12039-016-1069-1

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  • DOI: https://doi.org/10.1007/s12039-016-1069-1

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