Cluster-based molecular docking study for in silico identification of novel 6-fluoroquinolones as potential inhibitors against mycobacterium tuberculosis

被引:20
|
作者
Minovski, Nikola [1 ]
Perdih, Andrej [1 ]
Novic, Marjana [1 ]
Solmajer, Tom [1 ]
机构
[1] Natl Inst Chem, Ljubljana 1001, Slovenia
关键词
tuberculosis; antibacterial agents; fluoroquinolones; DNA gyrase; molecular docking; DNA GYRASE; NALIDIXIC-ACID; RESISTANCE; PURIFICATION; EXPLORATION; PERFORMANCE; VALIDATION; STRAINS; COMPLEX; TARGET;
D O I
10.1002/jcc.23205
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
A classical protein sequence alignment and homology modeling strategy were used for building three Mycobacterium tuberculosis-DNA gyrase protein models using the available topoII-DNA-6FQ crystal structure complexes originating from different organisms. The recently determined M. tuberculosis-DNA gyrase apoprotein structures and topoII-DNA-6FQ complexes were used for defining the 6-fluoroquinolones (6-FQs) binding pockets. The quality of the generated models was initially validated by docking of the cocrystallized ligands into their binding site, and subsequently by quantitative evaluation of their discriminatory performances (identification of active/inactive 6-FQs) for a set of 145 6-FQs with known biological activity values. The M. tuberculosis-DNA gyrase model with the highest estimated discriminatory power was selected and used afterwards in an additional molecular docking experiment on a mixed combinatorial set of 427 drug-like 6-FQ analogs for which the biological activity values were predicted using a prebuilt counter-propagation artificial neural network model. A novel three-level Boolean-based [T/F (true/false)] clustering algorithm was used to assess the generated binding poses: Level 1 (geometry properties assessment), Level 2 (score-based clustering and selection of the (T)-signed highly scored Level 1 poses), and Level 3 (activity-based clustering and selection of the most active (T)-signed Level 2 hits). The frequency analysis of occurrence of the fragments attached at R1 and R7 position of the (T)-signed 6-FQs selected in Level 3 revealed several novel attractive fragments and confirmed some previous findings. We believe that this methodology could be successfully used in establishing novel possible structure-activity relationship recommendations in the 6-FQs optimization, which could be of great importance in the current antimycobacterial hit-to-lead processes. (c) 2012 Wiley Periodicals, Inc.
引用
收藏
页码:790 / 801
页数:12
相关论文
共 50 条
  • [21] Microbial-based natural products as potential inhibitors targeting DNA gyrase B of Mycobacterium tuberculosis: an in silico study
    Elsaman, Tilal
    Mohamed, Magdi Awadalla
    Mohamed, Malik Suliman
    Eltayib, Eyman Mohamed
    Abdalla, Abualgasim Elgaili
    FRONTIERS IN CHEMISTRY, 2025, 13
  • [22] Identification of peptidomimetic compounds as potential inhibitors against MurA enzyme of Mycobacterium tuberculosis
    Kumar, Prateek
    Saumya, Kumar Udit
    Giri, Rajanish
    JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS, 2020, 38 (17) : 4997 - 5013
  • [23] An In Silico Study Based on QSAR and Molecular Docking and Molecular Dynamics Simulation for the Discovery of Novel Potent Inhibitor against AChE
    Khedraoui, Meriem
    Abchir, Oussama
    Nour, Hassan
    Yamari, Imane
    Errougui, Abdelkbir
    Samadi, Abdelouahid
    Chtita, Samir
    PHARMACEUTICALS, 2024, 17 (07)
  • [24] Preparation, biological evaluation and molecular docking study of imidazolyl dihydropyrimidines as potential Mycobacterium tuberculosis dihydrofolate reductase inhibitors
    Desai, N. C.
    Trivedi, A. R.
    Khedkar, Vijay M.
    BIOORGANIC & MEDICINAL CHEMISTRY LETTERS, 2016, 26 (16) : 4030 - 4035
  • [25] Identification of Novel Inhibitors of Type-I Mycobacterium Tuberculosis Fatty Acid Synthase Using Docking-Based Virtual Screening and Molecular Dynamics Simulation
    Singh, Nidhi
    Mao, Shi-Qing
    Li, Wenjin
    APPLIED SCIENCES-BASEL, 2021, 11 (15):
  • [26] Molecular docking, molecular dynamics and binding free energy based identification of novel potential multitarget inhibitors of Nipah virus
    Sinha, Prashasti
    Yadav, Anil Kumar
    JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS, 2024, 42 (24) : 13663 - 13679
  • [27] Virtual Screening, Docking, ADMET and Molecular Dynamics: A Study to Find Novel Inhibitors of Mycobacterium tuberculosis Targeting QcrB
    Jain, Surabhi
    Sharma, Smriti
    Sen, Dhrubo Jyoti
    JORDAN JOURNAL OF CHEMISTRY, 2021, 16 (03) : 131 - 146
  • [28] In silico virtual screening for the identification of novel inhibitors against dihydrodipicolinate reductase (DapB) of Mycobacterium tuberculosis, a key enzyme of diaminopimelate pathway
    Angrish, Nupur
    Lalwani, Neha
    Khare, Garima
    MICROBIOLOGY SPECTRUM, 2023, 11 (06):
  • [29] In silico approaches for the identification of novel ULK1 inhibitors: pharmacophore model, molecular docking and molecular dynamics simulations
    Yang, Yifan
    Ji, Cuicui
    Zhong, Qidi
    Yan, Hong
    Wang, Juan
    JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS, 2024, 42 (24) : 13372 - 13385
  • [30] In silico identification of colchicine derivatives as novel and potential inhibitors based on molecular docking and dynamic simulations targeting multifactorial drug targets involved in Alzheimer's disease
    Raturi, Adity
    Yadav, Vikas
    Hoda, Nasimul
    Subbarao, Naidu
    Chaudhry, Saif Ali
    JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS, 2024, 42 (21) : 11555 - 11573