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

被引:0
|
作者
CHINMAYEE CHOUDHURY
U DEVA PRIYAKUMAR
G NARAHARI SASTRY
机构
[1] Indian Institute of Chemical Technology,Centre for Molecular Modelling
[2] International Institute of Information and Technology,Centre for Computational Natural Sciences and Bioinformatics
来源
关键词
Virtual screening; pharmacophore model; docking; tuberculosis; HIV; ADMET filters; drug repositioning; poly-pharmacology;
D O I
暂无
中图分类号
学科分类号
摘要
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.
引用
收藏
页码:719 / 732
页数:13
相关论文
共 50 条
  • [31] Ligand-based approaches in virtual screening
    Douguet, Dominique
    [J]. CURRENT COMPUTER-AIDED DRUG DESIGN, 2008, 4 (03) : 180 - 190
  • [32] Studies on ligand-based pharmacophore modeling approach in identifying potent future EGFR inhibitors
    Shaikh, Gulam Moin
    Murahari, Manikanta
    Thakur, Shikha
    Kumar, Maushmi S.
    Mayur, Y. C.
    [J]. JOURNAL OF MOLECULAR GRAPHICS & MODELLING, 2022, 112
  • [33] Pharmacophore modeling and virtual screening studies to identify new c-Met inhibitors
    Tai, Wenting
    Lu, Tao
    Yuan, Haoliang
    Wang, Fengxiao
    Liu, Haichun
    Lu, Shuai
    Leng, Ying
    Zhang, Weiwei
    Jiang, Yulei
    Chen, Yadong
    [J]. JOURNAL OF MOLECULAR MODELING, 2012, 18 (07) : 3087 - 3100
  • [34] Pharmacophore modeling and virtual screening studies to identify new c-Met inhibitors
    Wenting Tai
    Tao Lu
    Haoliang Yuan
    Fengxiao Wang
    Haichun Liu
    Shuai Lu
    Ying Leng
    Weiwei Zhang
    Yulei Jiang
    Yadong Chen
    [J]. Journal of Molecular Modeling, 2012, 18 : 3087 - 3100
  • [35] Virtual screening workflow for glycogen synthase kinase 3β inhibitors: convergence of ligand-based and structure-based approaches
    VA Palyulin
    DI Osolodkin
    NS Zefirov
    [J]. Journal of Cheminformatics, 3 (Suppl 1)
  • [36] Combined ligand based pharmacophore modeling, virtual screening methods to identify critical chemical features of novel potential inhibitors for phosphodiesterase-5
    Chandrasekaran, Meganathan
    Sakkiah, Sugunadevi
    Lee, Keun Woo
    [J]. JOURNAL OF THE TAIWAN INSTITUTE OF CHEMICAL ENGINEERS, 2011, 42 (05) : 709 - 718
  • [37] Ligand-based pharmacophore modelling and virtual screening for the identification of amyloid-beta diagnostic molecules
    Marondedze, Ephraim Felix
    Govender, Krishna Kuben
    Govender, Penny Poomani
    [J]. JOURNAL OF MOLECULAR GRAPHICS & MODELLING, 2020, 101
  • [38] Pharmacophore modeling and structure-based virtual screening to identify potent inhibitors targeting LuxP of Vibrio harveyi
    Rajamanikandan, Sundaraj
    Srinivasan, Pappu
    [J]. JOURNAL OF RECEPTORS AND SIGNAL TRANSDUCTION, 2016, 36 (06) : 617 - 632
  • [39] Extensive ligand-based modeling and in silico screening reveal nanomolar inducible nitric oxide synthase (iNOS) inhibitors
    Suaifan, Ghadeer A. R. Y.
    Shehadehh, Mayyada
    Al-Ijel, Hebah
    Taha, Mutasem O.
    [J]. JOURNAL OF MOLECULAR GRAPHICS & MODELLING, 2012, 37 : 1 - 26
  • [40] New classes of potent heparanase inhibitors from ligand-based virtual screening
    Pala, Daniele
    Scalvini, Laura
    Elisi, Gian Marco
    Lodola, Alessio
    Mor, Marco
    Spadoni, Gilberto
    Ferrara, Fabiana F.
    Pavoni, Emiliano
    Roscilli, Giuseppe
    Milazzo, Ferdinando M.
    Battistuzzi, Gianfranco
    Rivara, Silvia
    Giannini, Giuseppe
    [J]. JOURNAL OF ENZYME INHIBITION AND MEDICINAL CHEMISTRY, 2020, 35 (01) : 1685 - 1696