Online citations, reference lists, and bibliographies.
Please confirm you are human
(Sign Up for free to never see this)
← Back to Search

QSAR Studies And Molecular Design Of Phenanthrene‐based Tylophorine Derivatives With Anticancer Activity

Siyan Liao, J. Chen, Li Qian, Y. Shen, K. Zheng
Published 2008 · Chemistry

Save to my Library
Download PDF
Analyze on Scholarcy
Share
The Quantitative Structure–Activity Relationship (QSAR) of a series of novel phenanthrene-based tylophorine derivatives with anticancer activity has been studied by using the Density Functional Theory (DFT), Molecular Mechanics (MM2), and statistical methods. The established model shows not only significant statistical quality, but also predictive ability, with the square of adjusted correlation coefficient (R2A=0.813) and the square of the cross-validation coefficient (q2=0.748). We find that the anticancer activity expressed as pIC50, which is defined as the negative value of the logarithm of necessary molar concentration of this series of compounds to cause 50% growth inhibition against the human A549 lung cancer cell line, closely relates with the energy (EHOMO) of the Highest Occupied Molecular Orbital (HOMO), the net charge of the terminal H atom of substituent R2 (), the hydrophobic coefficient of substituent R2 (log ), and the net charges of the first atom of substituent R1 (). The same model was further applied to predict the pIC50 for six recently reported congeneric compounds as external test set, and the predicted pIC50 values are close to the experimental ones, and thus it further confirms that this QSAR model has high predictive ability. The theoretical results can offer some useful references for understanding the action mechanism and designing new compounds with anticancer activity. Based on this QSAR equation, ten new compounds with higher anticancer activity have been theoretically designed and are expecting the experimental confirmation.
This paper references
10.1021/NP0106384
In vitro cytotoxic activity of phenanthroindolizidine alkaloids from Cynanchum vincetoxicum and Tylophora tanakae against drug-sensitive and multidrug-resistant cancer cells.
D. Staerk (2002)
10.1021/JA011490D
Intercalators. 1. Nature of Stacking Interactions between Intercalators (Ethidium, Daunomycin, Ellipticine, and 4‘,6-Diaminide-2-phenylindole) and DNA Base Pairs. Ab Initio Quantum Chemical, Density Functional Theory, and Empirical Potential Study
David Řeha (2002)
10.1039/B516152E
Expedient synthesis and structure-activity relationships of phenanthroindolizidine and phenanthroquinolizidine alkaloids.
Ta-Hsien Chuang (2006)
10.3987/COM-02-9615
Phenanthroindolizidine alkaloids and their cytotoxicity from the leaves of Ficus septica
P. Wu (2002)
10.1002/QUA.21285
DFT-based QSAR study and molecular design of AHMA derivatives as potent anticancer agents
J. Chen (2007)
10.1016/S1093-3263(01)00123-1
Beware of q2!
A. Golbraikh (2002)
10.1016/J.BMC.2004.03.055
QSAR modeling of globulin binding affinity of corticosteroids using AM1 calculations.
K. De (2004)
10.1002/ARDP.200600034
Biological Evaluation of Chalcones and Analogues as Hypolipidemic Agents
L. Santos (2006)
10.1016/J.BMC.2006.06.009
Antitumor agents 251: synthesis, cytotoxic evaluation, and structure-activity relationship studies of phenanthrene-based tylophorine derivatives (PBTs) as a new class of antitumor agents.
L. Wei (2006)
10.1016/J.BMC.2004.08.013
Electrophilicity index as a possible descriptor of biological activity.
R. Parthasarathi (2004)
10.1016/S0887-2333(99)00092-2
Inhibition of dihydrofolate reductase and cell growth activity by the phenanthroindolizidine alkaloids pergularinine and tylophorinidine: the in vitro cytotoxicity of these plant alkaloids and their potential as antimicrobial and anticancer agents.
K. N. Rao (2000)
10.1002/QSAR.200530146
An electrophilicity based analysis of toxicity of aromatic compounds towards Tetrahymena pyriformis
D. R. Roy (2006)
10.1007/s10822-007-9102-6
Antitumor Agents 252. Application of validated QSAR models to database mining: discovery of novel tylophorine derivatives as potential anticancer agents
S. Zhang (2007)
10.1016/0166-1280(88)80248-3
Analysis of the geometry of the hydroxymethyl radical by the “different hybrids for different spins” natural bond orbital procedure
J. E. Carpenter (1988)
10.1007/s11030-005-9009-x
Analyzing Toxicity Through Electrophilicity
D. R. Roy (2005)
10.1016/S0304-3835(98)00061-5
Thymidylate synthase activity in leukocytes from patients with chronic myelocytic leukemia and acute lymphocytic leukemia and its inhibition by phenanthroindolizidine alkaloids pergularinine and tylophorinidine.
K. Narasimha Rao (1998)
10.1021/ci010368v
Prediction of n-Octanol/Water Partition Coefficients from PHYSPROP Database Using Artificial Neural Networks and E-State Indices
I. Tetko (2001)
10.1021/BI00633A026
Mutants of CHO cells resistant to the protein synthesis inhibitors, cryptopleurine and tylocrebrine: genetic and biochemical evidence for common site of action of emetine, cryptopleurine, tylocrebine, and tubulosine.
R. Gupta (1977)
10.1016/J.BMCL.2005.02.022
Selective interaction between tylophorine B and bulged DNA.
Z. Xi (2005)
10.1158/0008-5472.CAN-03-1904
Novel Mode of Action of Tylophorine Analogs as Antitumor Compounds
W. Gao (2004)
10.1103/PHYSREV.136.B864
THE INHOMOGENEOUS ELECTRON GAS.
P. Hohenberg (1964)
10.1016/S0097-8485(99)00071-6
Density Functional MO Calculation for Stacked DNA Base-pairs with Backbones
N. Kurita (2000)



This paper is referenced by
10.1016/j.ejmech.2017.02.022
Design, synthesis, biological evaluation, molecular docking and QSAR studies of 2,4-dimethylacridones as anticancer agents.
M. Murahari (2017)
10.1002/QSAR.200860180
The QSAR Modeling of Cytotoxicity on Anthraquinones
Kalev Takkis (2009)
Original Open Access
M. Tako (2013)
10.1002/jcc.21471
A self‐adaptive genetic algorithm‐artificial neural network algorithm with leave‐one‐out cross validation for descriptor selection in QSAR study
Jingheng Wu (2010)
10.1016/j.ejmech.2008.12.020
CoMFA and docking studies of 2-phenylindole derivatives with anticancer activity.
S. Liao (2009)
10.1016/J.IBIOD.2017.01.030
Toxicity evaluation of five polyaromatic hydrocarbons to Escherichia coli using microcalorimetry and QASRs
Xiaoying Wu (2017)
A Density Function Theory Based Quantitative Structure Activity Relationships Study of Thiazoline Derivatives as Anticancer Agents
N. M. Mahani (2015)
10.3390/ijms12031807
Combined 3D-QSAR, Molecular Docking and Molecular Dynamics Study on Derivatives of Peptide Epoxyketone and Tyropeptin-Boronic Acid as Inhibitors Against the β5 Subunit of Human 20S Proteasome
J. Liu (2011)
10.1016/J.TETLET.2013.10.124
Total synthesis of (±)-antofine
Ming Yi (2014)
10.1016/j.bmcl.2012.03.109
Synthesis of indolizidinone analogues of cytotoxic alkaloids: monocyclic precursors are also active.
A. Boto (2012)
10.1007/978-90-481-2632-3_9
Particles of Biomedical Relevance and Their Interactions: A Classical and Quantum Mechanistic Approach to a Theoretical Description
E. Broclawik (2010)
10.1186/2191-2858-1-3
Analogue-based approaches in anti-cancer compound modelling: the relevance of QSAR models
Mohammed H Bohari (2011)
10.1088/1674-0068/22/03/285-289
3D-QSAR Study of 7,8-Dialkyl-1,3-diaminopyrrolo-[3,2-f] Quinazolines with Anticancer Activity as DHFR Inhibitors
J. Chen (2009)
10.3109/14756360903213499
Binding conformations and QSAR of CA-4 analogs as tubulin inhibitors
S. Liao (2010)
10.1007/s00894-009-0609-8
Theoretical studies on pyrimidine substituent derivatives as dual inhibitors of AP-1 and NF-κB
Li Qian (2010)
10.1088/1674-0068/22/05/473-480
Molecular Modeling and Design of Arylthioindole Derivatives as Tubulin Inhibitors
Si-Yan Liao (2009)
10.1007/s00044-014-1175-x
Eco-friendly synthesis and 2D-QSAR study of novel pyrazolines as potential anticolon cancer agents
T. A. Farghaly (2014)
Semantic Scholar Logo Some data provided by SemanticScholar