TY - JOUR
T1 - The systematic modeling studies and free energy calculations of the phenazine compounds as anti-tuberculosis agents
AU - Wang, Yueqi
AU - Khan, Abbas
AU - Chandra Kaushik, Aman
AU - Junaid, Muhammad
AU - Zhang, Xuehong
AU - Wei, Dong Qing
N1 - Funding Information:
This work was supported by the National Natural Science Foundation of China [No. 31670033], the Key Research Area [grant number 2016YFA0501703] from the Ministry of Science and Technology of China, and Joint Research Funds for Medical and Engineering & Scientific Research at Shanghai Jiao Tong University. The simulations in this work were supported by the Center for High Performance Computing, Shanghai Jiao Tong University.
Publisher Copyright:
© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2019/10/13
Y1 - 2019/10/13
N2 - Phenazine compounds have good activity against Mycobacterium tuberculosis (MTB). Based on the reported activities that were obtained in MTB H37Rv, a three-dimensional quantitative structure–activity relationship (3D-QSAR) model was built to design novel compounds against MTB. A fivefold cross-validation method and external validation were used to analyze the accuracy of forecasting. The model has a cross-validation coefficient q2=0.7 and a non-cross-validation coefficient r2 = 0.903, indicating that the model has good predictive possibility. The design of anti-pneumococcus MTB compounds was guided by the obtained 3D-QSAR model, and several compounds with better activity were obtained. To test the activity of these compounds, molecular docking, molecular dynamics simulation, and post-simulation analysis of the already reported drug targets in MTB were carried out. Among the total 15 drug targets, only three targets (Rv2361c, Rv2965c, and Rv3048c) were selected based on the docking results. Initial results reported that these compounds possessed good inhibition activity for Rv2361c. The top nine complexes of Rv2361 ligands were only subjected to MD simulation which resulted in a stable dynamics of the structures and showed a residual fluctuation in inhibitors binding pocket. Free energy reported that overall, the derivatives hold strong energy against the protein target. Energetic contribution results showed that residues, Asp76, Arg80, Asn124, Arg127, Arg244, and Arg250, play a major role in total energy. Systems biology approach validates shortlisted drug effect on the entire system which might be useful to predict potential drug in wet lab as well. Communicated by Ramaswamy H. Sarma.
AB - Phenazine compounds have good activity against Mycobacterium tuberculosis (MTB). Based on the reported activities that were obtained in MTB H37Rv, a three-dimensional quantitative structure–activity relationship (3D-QSAR) model was built to design novel compounds against MTB. A fivefold cross-validation method and external validation were used to analyze the accuracy of forecasting. The model has a cross-validation coefficient q2=0.7 and a non-cross-validation coefficient r2 = 0.903, indicating that the model has good predictive possibility. The design of anti-pneumococcus MTB compounds was guided by the obtained 3D-QSAR model, and several compounds with better activity were obtained. To test the activity of these compounds, molecular docking, molecular dynamics simulation, and post-simulation analysis of the already reported drug targets in MTB were carried out. Among the total 15 drug targets, only three targets (Rv2361c, Rv2965c, and Rv3048c) were selected based on the docking results. Initial results reported that these compounds possessed good inhibition activity for Rv2361c. The top nine complexes of Rv2361 ligands were only subjected to MD simulation which resulted in a stable dynamics of the structures and showed a residual fluctuation in inhibitors binding pocket. Free energy reported that overall, the derivatives hold strong energy against the protein target. Energetic contribution results showed that residues, Asp76, Arg80, Asn124, Arg127, Arg244, and Arg250, play a major role in total energy. Systems biology approach validates shortlisted drug effect on the entire system which might be useful to predict potential drug in wet lab as well. Communicated by Ramaswamy H. Sarma.
KW - 3D-QSAR
KW - Mycobacterium tuberculosis
KW - Phenazine
KW - free energy calculations
KW - molecular design
KW - systems biology
UR - http://www.scopus.com/inward/record.url?scp=85057338439&partnerID=8YFLogxK
U2 - 10.1080/07391102.2018.1537896
DO - 10.1080/07391102.2018.1537896
M3 - Article
C2 - 30332914
AN - SCOPUS:85057338439
VL - 37
SP - 4051
EP - 4069
JO - Journal of Biomolecular Structure and Dynamics
JF - Journal of Biomolecular Structure and Dynamics
SN - 0739-1102
IS - 15
ER -