Pharmacophore modeling and 3D-QSAR studies of galloyl benzamides as potent P-gp inhibitors

被引:3
|
作者
Srivastava, Shubham [1 ]
Choudhary, Bhanwar Singh [1 ]
Sharma, Manish [2 ]
Malik, Ruchi [1 ]
机构
[1] Cent Univ Rajasthan, Sch Chem Sci & Pharm, Dept Pharm, Ajmer 305817, Rajasthan, India
[2] Bahra Univ Shimla Hills, Sch Pharmaceut Sci, Waknaghat 173234, Himachal Prades, India
关键词
P-glycoprotein; Pharmacophore model; QSAR; Partial least square analysis; Galloyl benzamides; GLYCOPROTEIN; TRANSPORTER; PREDICTION; DOCKING;
D O I
10.1007/s00044-016-1556-4
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
P-gp transporter regulates key ADME of drugs in MDR condition. In the present work, a pharmacophore-based 3D-QSAR model was generated for a series of galloyl benzamides analogs possessing P-gp inhibitory activity. Developed pharmacophore model contains two hydrogen-bond acceptors (A), one hydrophobic (H), one hydrogen-bond donor (D) and two aromatic rings (R). These are crucial molecular fingerprints which predict binding efficacy of high-affinity and low-affinity ligands to the P-gp efflux pump. These pharmacophoric features point toward key structural requirements of galloyl benzamides for potent P-gp inhibition. Furthermore, a biological correlation 3D-QSAR variants and functional fingerprints of P-gp responsible for the receptor binding were observed. Alignment of the developed model with P-gp crystal structure indicated importance of A2 and A4 H-bond acceptor sites, which are involved in the important interactions with Glu530 and His690 residues of the active site. Excellent statistical results of QSAR model such as good correlation coefficient (r (2) > 0.95), higher F value (F > 205) and excellent predictive power (Q (2) > 0.6) with low standard deviation (SD < 0.2) strongly suggest that the developed model is good for the future prediction of P-gp inhibitory activity of new galloyl benzamide analogs.
引用
收藏
页码:1140 / 1147
页数:8
相关论文
共 50 条
  • [1] Pharmacophore modeling and 3D-QSAR studies of galloyl benzamides as potent P-gp inhibitors
    Shubham Srivastava
    Bhanwar Singh Choudhary
    Manish Sharma
    Ruchi Malik
    Medicinal Chemistry Research, 2016, 25 : 1140 - 1147
  • [2] Pharmacophore modeling and 3D-QSAR studies of leucettines as potent Dyrk2 inhibitors
    Anu Bahl
    Prashant Joshi
    Sandip B. Bharate
    Harish Chopra
    Medicinal Chemistry Research, 2014, 23 : 1925 - 1933
  • [3] Pharmacophore modeling and 3D-QSAR studies of leucettines as potent Dyrk2 inhibitors
    Bahl, Anu
    Joshi, Prashant
    Bharate, Sandip B.
    Chopra, Harish
    MEDICINAL CHEMISTRY RESEARCH, 2014, 23 (04) : 1925 - 1933
  • [4] 3D-QSAR and Pharmacophore Identification of Benzothiazole Derivatives as Potent p56lck Inhibitors
    Arora, Kanika
    Khokra, Sukhbir Lal
    Khan, Shah Alam
    Husain, Asif
    CHIANG MAI JOURNAL OF SCIENCE, 2018, 45 (02): : 1062 - 1072
  • [5] Pharmacophore-Based 3D-QSAR Studies of Aromatase Inhibitors
    Kishore, Deb Pran
    Rana, Ajay
    Jain, Upendra Kumar
    Rao, P. Mallikarjuna
    ASIAN JOURNAL OF CHEMISTRY, 2013, 25 (18) : 10588 - 10594
  • [6] Combined Pharmacophore Modeling, Docking, and 3D-QSAR Studies of PLK1 Inhibitors
    Lu, Shuai
    Liu, Hai-Chun
    Chen, Ya-Dong
    Yuan, Hao-Liang
    Sun, Shan-Liang
    Gao, Yi-Ping
    Yang, Pei
    Zhang, Liang
    Lu, Tao
    INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, 2011, 12 (12): : 8713 - 8739
  • [7] 3D-QSAR, Pharmacophore Modeling, ADMET, and DFT Studies ofHalogenated Conjugated Dienones as Potent MAO-B Inhibitors
    Mathew, Githa Elizabeth
    Herrera-Acevedo, Chonny
    Scotti, Marcus Tullius
    Kumar, Sunil
    Berisha, Avni
    Kaya, Savas
    Alfarraj, Saleh
    Ansari, Mohammad Javed
    Dhyani, Archana
    Sudevan, Sachithra Thazhathuveedu
    Kumar, Mohan
    Mathew, Bijo
    CURRENT COMPUTER-AIDED DRUG DESIGN, 2025, 21 (02) : 179 - 193
  • [8] Pharmacophore modeling, 3D-QSAR, and in silico ADME prediction of N-pyridyl and pyrimidine benzamides as potent antiepileptic agents
    Malik, Ruchi
    Mehta, Pakhuri
    Srivastava, Shubham
    Choudhary, Bhanwar Singh
    Sharma, Manish
    JOURNAL OF RECEPTORS AND SIGNAL TRANSDUCTION, 2017, 37 (03) : 259 - 266
  • [9] Pharmacophore Based 3D-QSAR Modeling and Molecular Docking of Leucettines as Potent Dyrk1A Inhibitors
    Bahl, Anu
    Joshi, Prashant
    Bharate, Sandip B.
    Chopra, Harish
    LETTERS IN DRUG DESIGN & DISCOVERY, 2013, 10 (08) : 719 - 726
  • [10] Optimization, pharmacophore modeling and 3D-QSAR studies of sipholanes as breast cancer migration and proliferation inhibitors
    Foudah, Ahmed I.
    Sallam, Asmaa A.
    Akl, Mohamed R.
    El Sayed, Khalid A.
    EUROPEAN JOURNAL OF MEDICINAL CHEMISTRY, 2014, 73 : 310 - 324