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1.
Cancer is a significant world health problem for which efficient therapies are in urgent demand. c-Src has emerged as an attractive
target for drug discovery efforts toward antitumor therapies. Toward this target several series of c-Src inhibitors that showed
activity in the assay have been reported. In this article, 3D-QSAR models have been built with 156 anilinoquinazoline and
quinolinecarbonitrile derivative inhibitors by using CoMFA and CoMSIA methods. These studies indicated that the QSAR models
were statistically significant with high predictabilities (CoMFA model, q
2 = 0.590, r
2 = 0.855; CoMSIA model, q
2 = 0.538, r
2 = 0.748). The details of c-Src kinase/inhibitor binding interactions in the crystal structure of complex provided new information
for the design of new inhibitors. As a result, docking simulations were also conducted on the series of potent inhibitors.
The flexible docking method, which was performed by the DOCK program, positioned all of the inhibitors into the active site
to determine the probable binding conformation. The CoMFA and CoMSIA models based on the flexible docking conformations also
yielded statistically significant and highly predictive QSAR models (CoMFA model, q
2 = 0.507, r
2 = 0.695; CoMSIA model, q
2 = 0.463, r
2 = 0.734). Our models would offer help to better comprehend the structure-activity relationships that exist for this class
of compounds and also facilitate the design of novel inhibitors with good chemical diversity. 相似文献
2.
Yuanqiang Wang Heng Zhang Yong Lin Qi Zhao Hui Liu Zhan Zhang Qingyou Xia Bo Zhu Zhihua Lin 《Journal of molecular modeling》2011,17(1):1-8
Phenols and its analogues are known to induce caspase-mediated apoptosis activity and cytotoxicity on various cancer cell
lines. In the current work, two types of molecular field analysis techniques were used to perform the three dimension quantitative
structure activity relationship (3D-QSAR) modeling between structural characters and anticancer activity of two sets of phenolic
compounds, which are comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA).
Then two 3D-QSAR models for two sets of phenolic analogues were obtained with good results. The first QSAR model, which was
derived from CoMFA for phenols with caspase-mediated apoptosis activity against L1210 cells, had good predictability (q
2 = 0.874, r
2 = 0.930), and the other one was derived from CoMSIA for electron-attracting phenols with cytotoxicity in L1210 cell (q
2 = 0.836, r
2 = 0.950). In addition, the CoMFA and CoMSIA contour maps provide valuable guidance for designing highly active phenolic compounds. 相似文献
3.
Lee JY Doddareddy MR Cho YS Choo H Koh HY Kang JH No KT Pae AN 《Journal of molecular modeling》2007,13(5):543-558
Comparative quantitative structure–activity relationship (QSAR) analyses of peptide deformylase (PDF) inhibitors were performed
with a series of previously published (British Biotech Pharmaceuticals, Oxford, UK) reverse hydroxamate derivatives having
antibacterial activity against Escherichia coli PDF, using 2D and 3D QSAR methods, comparative molecular field analysis (CoMFA), comparative molecular similarity indices
analysis (CoMSIA), and hologram QSAR (HQSAR). Statistically reliable models with good predictive power were generated from
all three methods (CoMFA r
2 = 0.957, q
2 = 0.569; CoMSIA r
2 = 0.924, q
2 = 0.520; HQSAR r
2 = 0.860, q
2 = 0.578). The predictive capability of these models was validated by a set of compounds that were not included in the training
set. The models based on CoMFA and CoMSIA gave satisfactory predictive r
2 values of 0.687 and 0.505, respectively. The model derived from the HQSAR method showed a low predictability of 0.178 for
the test set. In this study, 3D prediction models showed better predictive power than 2D models for the test set. This might
be because 3D information is more important in the case of datasets containing compounds with similar skeletons. Superimposition
of CoMFA contour maps in the active site of the PDF crystal structure showed a meaningful correlation between receptor–ligand
binding and biological activity. The final QSAR models, along with information gathered from 3D contour and 2D contribution
maps, could be useful for the design of novel active inhibitors of PDF.
Figure Superimposition of comparative molecular field analysis (CoMFA) contour plot in the active site of peptide deformylase (PDF) 相似文献
4.
Chai HF Liang XX Li L Zhao CS Gong P Liang ZJ Zhu WL Jiang HL Luo C 《Journal of molecular modeling》2011,17(8):1831-1840
Infection with hepatitis B virus (HBV) is a major cause of liver diseases such as cirrhosis and hepatocellular carcinoma.
In our previous studies, we identified indole derivatives that have anti-HBV activities. In this study, we optimize a series
of 5-hydroxy-1H-indole-3-carboxylates, which exhibited potent anti-HBV activities, using three-dimensional quantitative structure-activity
relationship (3D QSAR) studies with comparative molecular field analysis (CoMFA) and comparative molecular similarity indices
analysis (CoMSIA). The lowest energy conformation of compound 3, which exhibited the most potent anti-HBV activity, obtained from systematic search was used as the template for alignment.
The best predictions were obtained with the CoMFA standard model (q
2 = 0.689, r
2 = 0.965, SEE = 0.082, F = 148.751) and with CoMSIA combined steric, electrostatic, hydrophobic and H-bond acceptor fields
(q
2 = 0.578, r
2 = 0.973, SEE = 0.078, F = 100.342). Both models were validated by an external test set of six compounds giving satisfactory
prediction. Based on the clues derived from CoMFA and CoMSIA models and their contour maps, another three compounds were designed
and synthesized. Pharmacological assay demonstrated that the newly synthesized compounds possessed more potent anti-HBV activities
than before (IC50: compound 35a is 3.1 μmol/l, compound 3 is 4.1 μmol/l). Combining the clues derived from the 3D QSAR studies and from further validation of the 3D QSAR models, the
activities of the newly synthesized indole derivatives were well accounted for. Furthermore, this showed that the CoMFA and
CoMSIA models proved to have good predictive ability. 相似文献
5.
M. Muddassar F. A. Pasha M. M. Neaz Y. Saleem S. J. Cho 《Journal of molecular modeling》2009,15(2):183-192
Protein kinase B (PKB; also known as Akt kinase) is located downstream in the PI-3 kinase pathway. Overexpression and constitutive
activation of PKB/Akt leads to human prostate, breast and ovarian carcinomas. A series of 69 PKB/Akt inhibitors were examined
to explore their binding modes using FlexX, and three-dimensional quantitative structure–activity relationship (3D-QSAR) studies
based on comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were
performed to provide structural insights into these compounds. CoMFA produced statistically significant results, with cross-validated
q
2
and non-cross validated correlation r
2
coefficients of 0.53 and 0.95, respectively. For CoMSIA, steric, hydrophobic and hydrogen bond acceptor fields jointly yielded
‘leave one out’ q
2
= 0.51 and r
2
= 0.84. The predictive power of CoMFA and CoMSIA was determined using a test set of 13 molecules, which gave correlation
coefficients, of 0.58 and 0.62, respectively. Molecular docking revealed that the binding modes of these molecules in the ATP binding sites
of the Akt kinase domain were very similar to those of the co-crystallized ligand. The information obtained from 3D contour
maps will allow the design of more potent and selective Akt kinase inhibitors. 相似文献
6.
Three-dimensional quantitative structure–activity relationship studies were performed on a series of 88 histamine receptor
4 (H4R) antagonists in an attempt to elucidate the 3D structural features required for activity. Several in silico modeling
approaches, including comparative molecular field analysis (CoMFA), comparative similarity indices analysis (CoMSIA), molecular
docking, and molecular dynamics (MD), were carried out. The results show that both the ligand-based CoMFA model (Q
2 = 0.548, R
ncv2 = 0.870, R
pre2 = 0.879, SEE = 0.410, SEP = 0.386) and the CoMSIA model (Q
2 = 0.526, R
ncv2 =0.866, R
pre2 = 0.848, SEE = 0.416, SEP = 0.413) are acceptable, as they show good predictive capabilities. Furthermore, a combined analysis
incorporating CoMFA, CoMSIA contour maps and MD results shows that (1) compounds with bulky or hydrophobic substituents at
positions 4–6 in ring A (R2 substituent), positively charged or hydrogen-bonding (HB) donor groups in the R1 substituent,
and hydrophilic or HB acceptor groups in ring C show enhanced biological activities, and (2) the key amino acids in the binding
pocket are TRP67, LEU71, ASP94, TYR95, PHE263 and GLN266. To our best knowledge, this work is the first to report the 3D-QSAR
modeling of these H4R antagonists. The conclusions of this work may lead to a better understanding of the mechanism of antagonism
and aid in the design of new, more potent H4R antagonists. 相似文献
7.
Farhan Ahmad Pasha Muhammad Muddassar Anil Kumar Srivastava Seung Joo Cho 《Journal of molecular modeling》2010,16(2):263-277
Members of the epidermal growth factor receptor (EGFR) family of proteins are frequently overactive in solid tumors. A relatively
new therapeutic approach to inhibit the kinase activity is the use of ATP-competitive small molecules. In silico techniques
were employed to identify the key interactions between inhibitors and their protein receptors. A series of EGFR inhibitory
anilinoquinolines was studied within the framework of hologram quantitative structure activity relationship (HQSAR), density
functional theory (DFT)-based QSAR, and three-dimensional (3D) QSAR (CoMFA/CoMSIA). The HQSAR analysis implied that substitutions
at certain sites on the inhibitors play an important role in EGFR inhibition. DFT-based QSAR results suggested that steric
and electronic interactions contributed significantly to the activity. Ligand-based 3D-QSAR and receptor-guided 3D-QSAR analyses
such as CoMFA and CoMSIA techniques were carried out, and the results corroborated the previous two approaches. The 3D QSAR
models indicated that steric and hydrophobic interactions are dominant, and that substitution patterns are an important factor
in determining activity. Molecular docking was helpful in identifying a bioactive conformer as well as a plausible binding
mode. The docked geometry-based CoMFA model with steric and electrostatic fields effect gave q
2 = 0.66, r
2 = = 0.94 with r
2
predictive = 0.72. Similarly, CoMSIA with hydrophobic field gave q
2 = 0.59, r
2 = 0.85 with r
2
predictive = 0.63. Bulky groups around site 3 of ring “C”, and hydrophilic and bulky groups at position 6 of ring “A” are desirable,
with a hydrophobic and electron-donating group at site 7 of ring “A” being helpful. Accordingly, potential EGFR inhibitors
may be designed by modification of known inhibitors. 相似文献
8.
ETA subtype selective antagonists constitute a novel and potentially important class of agents for the treatment of pulmonary
hypertension, heart failure, and other pathological conditions. In this paper, 60 benzodiazepine derivatives displaying potent
activities against ETA and ETB subtypes of endothelin receptor were selected to establish the 3D-QSAR models using CoMFA and CoMSIA approaches. These models
show excellent internal predictability and consistency, external validation using test-set 19 compounds yields a good predictive
power for antagonistic potency. Statistical parameters of models were obtained with CoMFA-ETA (q
2 = 0.787, r
2 = 0.935, r
2
pred
= 0.901), CoMFA-ETB (q
2 = 0.842, r
2 = 0.984, r
2
pred
= 0.941), CoMSIA-ETA (q
2 = 0.762, r
2 = 0.971, r
2
pred
= 0.958) and CoMSIA-ETB (q
2 = 0.771, r
2 = 0.974, r
2
pred
= 0.953) respectively. Field contour maps (CoMFA and CoMSIA) corresponding to the ETA and ETB subtypes reflects the characteristic similarities and differences between these types. The results of this paper provide
valuable information to facilitate structural modifications of the title compounds to increase the inhibitory potency and
subtype selectivity of endothelin receptor. 相似文献
9.
10.
Microsomal prostaglandin E2 synthase (mPGES-1) has been identified recently as a novel target for treating pain and inflammation. The aim of this study
is to understand the binding affinities of reported inhibitors for mPGES-1 and further to design potential new mPGES-1 inhibitors.
3D-QSAR-CoMFA (comparative molecular field analysis) and CoMSIA (comparative molecular similarity indices analysis) - techniques
were employed on a series of indole derivatives that act as selective mPGES-1 inhibitors. The lowest energy conformer of the
most active compound obtained from systematic conformational search was used as a template for the alignment of 32 compounds.
The models obtained were used to predict the activities of the test set of eight compounds, and the predicted values were
in good agreement with the experimental results. The 3D-QSAR models derived from the training set of 24 compounds were all
statistically significant (CoMFA; q
2 = 0.89, r
2 = 0.95, , and CoMSIA; q
2 = 0.84, r
2 = 0.93, , ). Contour plots generated for the CoMFA and CoMSIA models reveal useful clues for improving the activity of mPGES-1 inhibitors.
In particular, substitutions of an electronegative fluorine atom or a bulky hydrophilic phenoxy group at the meta or para positions of the biphenyl rings might improve inhibitory activity. A plausible binding mode between the ligands and mPGES-1
is also proposed. 相似文献
11.
12.
13.
Orvinols are potent analgesics that target opioid receptors. However, their analgesic mechanism remains unclear and no significant preference for subtype opioid receptor has been achieved. In order to find new orvinols that target the κ-receptor, comparative 3D–QSAR studies were performed on 26 orvinol analogs using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The best predictions for the κ-receptor were obtained with the CoMFA standard model (q
2=0.686, r
2=0.947) and CoMSIA model combined steric, electrostatic, hydrophobic, and hydrogen bond donor/acceptor fields (q
2=0.678, r
2=0.914). The models built were further validated by a test set made up of seven compounds, leading to predictive r
2 values of 0.672 for CoMFA and 0.593 for CoMSIA. The study could be helpful for designing and prepare new category κ-agonists from orvinols.
相似文献
14.
Vaibhav Jain Ashish Pandey Shikhar Gupta C. Gopi Mohan 《Journal of molecular modeling》2010,16(4):669-676
Asthma is an inflammatory disease of the lungs. Clinical studies suggest that eotaxin and chemokine receptor-3 (CCR3) play
a primary role in the recruitment of eosinophils in allergic asthma. Development of novel and potent CCR3 antagonists could
provide a novel mechanism for inhibition of this recruitment process, thereby preventing asthma. With the intention of designing
new ligands with enhanced inhibitor potencies against CCR3, a 3D-QSAR CoMFA study was carried out on 41 4-benzylpiperidinealkylureas
and amide derivatives. The best statistics of the developed CoMFA model were r
2 = 0.960, rcv2 = 0.589 r_{cv}^2 = 0.589 , n = 32 for the training set and rpred2 = 0.619 r_{pred}^2 = 0.619 , n = 9 for the test set. The generated 3D-QSAR contribution maps shed some light on the effects of the substitution pattern
related to CCR3 antagonist activity. 相似文献
15.
As a tumor suppressor, p53 protein regulates the cell cycle and is involved in preventing tumorgenesis. The protein level
of p53 is under the tight control of its negative regulator human double minute 2 (HDM2) via ubiquitination. Therefore, the design of inhibitors of HDM2 has attracted much interest of research on developing novel anticancer drugs. Presently, two classes of molecules, i.e.,
the 1,4-benzodiazepine-2,5-diones (BDPs) and N-Acylpolyamine (NAPA) derivatives were studied by three-dimensional quantitative
structure–activity relationship (3D-QSAR) modeling approaches including the comparative molecular field analysis (CoMFA) and
comparative molecular similarity index analysis (CoMSIA) as promising p53-HDM2 inhibitors. Based on both the ligand-based and receptor-guided (docking) alignments, two optimal 3D-QSAR models were obtained
with good predictive power of q
2 = 0.41, r
2
pred = 0.60 for BDPs, and q
2 = 0.414, r
2
pred = 0.69 for NAPA analogs, respectively. By analysis of the model and its related contour maps, it is revealed that the electrostatic
interactions contributed much larger to the compound binding affinity than the steric effects. And the contour maps intuitively
suggested where to modify the molecular structures in order to improve the binding affinity. In addition, molecular dynamics
simulation (MD) study was also carried out on the dataset with purpose of exploring the detailed binding modes of ligand in
the HDM2 binding pocket. Based on the CoMFA contour maps and MD-based docking analyses, some key structural aspects responsible for
inhibitory activity of these two classes of compounds were concluded as follows: For BDPs, the R1 and R3 regions should have small electronegativity groups; substituents R2 and R4 should be larger, and R3 substituent mainly involves in H-bonds forming. For NAPA derivatives, bulky and electropositive groups in ring B and ring
A, small substituent at region P is favorable for the inhibitory activity. The models and related information, we hope, may
provide important insight into the inhibitor-p53-HDM2 interactions and be helpful for facilitating the design of novel potent inhibitors. 相似文献
16.
In the current study, the applicability and scope of 3D-QSAR models (CoMFA and CoMSIA) to complement virtual screening using
3D pharmacophore and molecular docking is examined and applied to identify potential hits against Mycobacterium tuberculosis Enoyl acyl carrier protein reductase (MtENR). Initially CoMFA and CoMSIA models were developed using series of structurally
related arylamides as MtENR inhibitors. Docking studies were employed to position the inhibitors into MtENR active site to
derive receptor based 3D-QSAR models. Both CoMFA and CoMSIA yielded significant cross validated q2 values of 0.663 and 0.639 and r2 values of 0.989 and 0.963, respectively. The statistically significant models were validated by a test set of eight compounds
with predictive r2 value of 0.882 and 0.875 for CoMFA and CoMSIA. The contour maps from 3D-QSAR models in combination with docked binding structures
help to better interpret the structure activity relationship. Integrated with CoMFA and CoMSIA predictive models structure
based (3D-pharmacophore and molecular docking) virtual screening have been employed to explore potential hits against MtENR.
A representative set of 20 compounds with high predicted IC50 values were sorted out in the present study. 相似文献
17.
Ki Hwan Kim Irina Gaisina Franck Gallier Denise Holzle Sylvie Y. Blond Andrew Mesecar Alan P. Kozikowski 《Journal of molecular modeling》2009,15(12):1463-1479
Molecular modeling and docking studies along with three-dimensional quantitative structure relationships (3D-QSAR) studies
have been used to determine the correct binding mode of glycogen synthase kinase 3β (GSK-3β) inhibitors. The approaches of
comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) are used for the
3D-QSAR of 51 substituted benzofuran-3-yl-(indol-3-yl)maleimides as GSK-3β inhibitors. Two binding modes of the inhibitors
to the binding site of GSK-3β are investigated. The binding mode 1 yielded better 3D-QSAR correlations using both CoMFA and
CoMSIA methodologies. The three-component CoMFA model from the steric and electrostatic fields for the experimentally determined
pIC50 values has the following statistics: R2(cv) = 0.386 nd SE(cv) = 0.854 for the cross-validation, and R2 = 0.811 and SE = 0.474 for the fitted correlation. F (3,47) = 67.034, and probability of R2 = 0 (3,47) = 0.000. The binding mode suggested by the results of this study is consistent with the preliminary results of
X-ray crystal structures of inhibitor-bound GSK-3β. The 3D-QSAR models were used for the estimation of the inhibitory potency
of two additional compounds. 相似文献
18.
Ran T Lu T Yuan H Liu H Wang J Zhang W Leng Y Lin G Zhuang S Chen Y 《Journal of molecular modeling》2012,18(1):171-186
The phosphatidylinositol-3-kinase (PI3K)/Akt/mammalian target of rapamycin (mTOR) signaling pathway plays a critical role
in the regulation of cellular growth, survival and proliferation. mTOR and PI3K have attracted particular attention as cancer
targets. These kinases belong to the phosphatidylinositol-3-kinase-related kinase (PIKK) family and therefore have considerable
homology in their active sites. To accelerate the discovery of inhibitors with selective activity against mTOR and PI3K as
cancer targets, in this work, a homology model of mTOR was developed to identify the structural divergence in the active sites
between mTOR and PI3Kα. Furthermore, two highly predictive comparative molecular similarity index analyses (CoMSIA) models
were built based on 304 selective inhibitors docked into mTOR and PI3Kα, respectively (mTOR: q
2 = 0.658, r
pre2 = 0.839; PI3Kα: q
2 = 0.540, r
pre2 = 0.719). The results showed that steric and electrostatic fields have an important influence on selectivity towards mTOR
and PI3Kα—a finding consistent with the structural divergence between the active sites. The findings may be helpful in investigating
selective mTOR/PI3Kα inhibitors. 相似文献
19.
3D-QSAR (CoMFA and CoMSIA) studies were performed on human equlibrative nucleoside transporter (hENT1) inhibitors displaying Ki values ranging from 10,000 to 0.7 nM. Both CoMFA and CoMSIA analysis gave reliable models with q2 values >0.50 and r2 values >0.92. The models have been validated for their stability and robustness using group validation and bootstrapping techniques and for their predictive abilities using an external test set of nine compounds. The high predictive r2 values of the test set (0.72 for CoMFA model and 0.74 for CoMSIA model) reveals that the models can prove to be a useful tool for activity prediction of newly designed nucleoside transporter inhibitors. The CoMFA and CoMSIA contour maps identify features important for exhibiting good binding affinities at the transporter, and can thus serve as a useful guide for the design of potential equilibrative nucleoside transporter inhibitors. 相似文献
20.
Michell O. Almeida Gustavo H. G. Trossini Vinícius G. Maltarollo Danielle da C. Silva 《Journal of biomolecular structure & dynamics》2016,34(9):2045-2053
Studies have showed that there are many biological targets related to the cancer treatment, for example, TGF type I receptor (TGF-βRI or ALK5). The ALK5 inhibition is a strategy to treat some types of cancer, such as breast, lung, and pancreas. Here, we performed CoMFA and CoMSIA studies for 70 ligands with ALK5 inhibition. The internal validation for both models (q2LOO = 0.887 and 0.822, respectively) showed their robustness, while the external validations showed their predictive power (CoMFA: r2test = 0.998; CoMSIA: r2test = 0.975). After all validations, CoMFA and CoMSIA maps indicated physicochemical evidences on the main factors involved in the interaction between bioactive ligands and ALK5. Therefore, these results suggest molecular modifications to design new ALK5 inhibitors. 相似文献