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1.
The Aurora kinases have been regarded as attractive targets for the development of new anticancer agents. Recently a series
of azaindole derivatives with Aurora B inhibitory activities were reported. To explore the relationship between the structures
of substituted azaindole derivatives and their inhibition of Aurora B, 3D-QSAR and molecular docking studies were performed
on a dataset of 41 compounds. 3D-QSAR, including CoMFA and CoMSIA, were applied to identify the key structures impacting their
inhibitory potencies. The CoMSIA model showed better results than CoMFA, with r
2
cv value of 0.575 and r
2
value of 0.987. 3D contour maps generated from CoMFA and CoMSIA along with the docking binding structures provided enough
information about the structural requirements for better activity. Based on the structure-activity relationship revealed by
the present study, we have designed a set of novel Aurora B inhibitors that showed excellent potencies in the developed models.
Thus, our results allowed us to design new derivatives with desired activities. 相似文献
2.
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
3.
Vascular endothselial growth factor (VEGF) and its receptor tyrosine kinase VEGFR-2 or kinase insert domain receptor (KDR)
have been identified as new promising targets for the design of novel anticancer agents. It is reported that 4-(1H-indazol-4-yl)phenylamino and aminopyrazolopyridine urea derivatives exhibit potent inhibitory activities toward KDR. To investigate
how their chemical structures relate to the inhibitory activities and to identify the key structural elements that are required
in the rational design of potential drug candidates of this class, molecular docking simulations and three-dimensional quantitative
structure-activity relationship (3D-QSAR) methods were performed on 78 4-(1H-indazol-4-yl)phenylamino and aminopyrazolopyridine urea derivatives as KDR inhibitors. Surflex-dock was used to determine
the probable binding conformations of all the compounds at the active site of KDR. As a result, multiple hydrophobic and hydrogen-bonding
interactions were found to be two predominant factors that may be used to modulate the inhibitory activities. Comparative
molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) 3D-QSAR models were developed
based on the docking conformations. The CoMFA model produced statistically significant results with the cross-validated correlation
coefficient q2 of 0.504 and the non-cross-validated correlation coefficient r2 of 0.913. The best CoMSIA model was obtained from the combination of steric, electrostatic and hydrophobic fields. Its q2 and r2 being 0.595 and 0.947, respectively, indicated that it had higher predictive ability than the CoMFA model. The predictive
abilities of the two models were further validated by 14 test compounds, giving the predicted correction coefficients rpred2 of 0.727 for CoMFA and 0.624 for CoMSIA, respectively. In addition, the CoMFA and CoMSIA models were used to guide the design
of a series of new inhibitors of this class with predicted excellent activities. Thus, these models may be used as an efficient
tool to predict the inhibitory activities and to guide the future rational design of 4-(1H-indazol-4-yl)phenylamino and aminopyrazolopyridine urea derivatives-based novel KDR inhibitors with potent activities. 相似文献
4.
5.
Presently, an in silico modeling was carried out on a series of 63 phosphonic acid-containing thiazole derivatives as fructose-1,6-bisphosphatase
(FBPase) inhibitors using CoMFA/CoMSIA and molecular docking methods. The CoMFA and CoMSIA models using 51 molecules in the
training set gave r
cv2 values of 0.675 and 0.619, r
2
values of 0.985 and 0.979, respectively. The systemic external validation indicated that our CoMFA and CoMSIA models possessed
high predictive powers with r
02 values of 0.995 and 0.994, r
m(test)2 values of 0.887 and 0.860, respectively. The 3D contour maps of the CoMFA and CoMSIA provided smooth and interpretable explanation
of the structure-activity relationship for the inhibitors. Molecular docking studies revealed that a phosphonic group was
essential for binding to the AMP binding site, and some key features were also identified. The analyses of the 3D contour
plots and molecular docking results permitted interesting conclusions about the effects of different substituent groups at
different positions of the common scaffold, which might guide the design of novel FBPase inhibitors with higher activity and
bioavailability. A set of 60 new analogues were designed by utilizing the results revealed in the present study, and were
predicted with significantly improved potencies in the developed models. The findings can be quite useful to aid the designing
of new fructose-1,6-biphophatase inhibitors with improved biological response. 相似文献
6.
《Journal of receptor and signal transduction research》2013,33(5):468-478
AbstractWith the purpose of designing novel chemical entities with improved inhibitory potencies against drug-resistant Mycobacterium tuberculosis, the 3D- quantitative structure–activity relationship (QSAR) studies were carried out on biphenyl analogs of the tuberculosis (TB) drug, PA-824. Anti-mycobacterial activity (MABA) was considered for the 3D-QSAR studies using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) approaches. The best CoMFA and CoMSIA models were found statistically significant with cross-validated coefficients (q2) of 0.784 and 0.768, respectively, and conventional coefficients (r2) of 0.823 and 0.981, respectively. The cross-validated and the external validation results revealed that both the CoMFA and CoMSIA models possesses high accommodating capacities and they would be reliable for predicting the pMIC values of new PA-824 derivatives. Based on the models and structural insights, a series of new PA-824 derivatives were designed and the anti-mycobacterial activities of the designed compounds were predicted based on the best 3D-QSAR model. The predicted data results suggest the designed compounds are more potent than existed ones. 相似文献
7.
Penghua Li Jiale Peng Yeheng Zhou Yaping Li XingYong Liu 《Journal of receptor and signal transduction research》2018,38(3):213-224
Human Coagulation Factor IXa (FIXa), specifically inhibited at the initiation stage of the blood coagulation cascade, is an excellent target for developing selective and safe anticoagulants. To explore this inhibitory mechanism, 86 FIXa inhibitors were selected to generate pharmacophore models and subsequently SAR models. Both best pharmacophore model and ROC curve were built through the Receptor–Ligand Pharmacophore Generation module. CoMFA model based on molecular docking and PLS factor analysis methods were developed. Model propagations values are q2?=?0.709, r2?=?0.949, and r2pred?=?0.905. The satisfactory q2 value of 0.609, r2 value of 0.962, and r2pred value of 0.819 for CoMSIA indicated that the CoMFA and CoMSIA models are both available to predict the inhibitory activity on FIXa. On the basis of pharmacophore modeling, molecular docking, and 3D-QSAR modeling screening, six molecules are screened as potential FIXa inhibitors. 相似文献
8.
Yan-Ke Jiang 《Journal of molecular modeling》2010,16(7):1239-1249
Three-dimensional quantitative structure-activity relationship (3D-QSAR) and molecular docking studies were carried out to
explore the binding of 73 inhibitors to dipeptidyl peptidase IV (DPP-IV), and to construct highly predictive 3D-QSAR models
using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The negative
logarithm of IC50 (pIC50) was used as the biological activity in the 3D-QSAR study. The CoMFA model was developed by steric and electrostatic field
methods, and leave-one-out cross-validated partial least squares analysis yielded a cross-validated value (rcv2 {\hbox{r}}_{{\rm{cv}}}^{\rm{2}} ) of 0.759. Three CoMSIA models developed by different combinations of steric, electrostatic, hydrophobic and hydrogen-bond
fields yielded significant rcv2 {\hbox{r}}_{{\rm{cv}}}^{\rm{2}} values of 0.750, 0.708 and 0.694, respectively. The CoMFA and CoMSIA models were validated by a structurally diversified
test set of 18 compounds. All of the test compounds were predicted accurately using these models. The mean and standard deviation
of prediction errors were within 0.33 and 0.26 for all models. Analysis of CoMFA and CoMSIA contour maps helped identify the
structural requirements of inhibitors, with implications for the design of the next generation of DPP-IV inhibitors for the
treatment of type 2 diabetes. 相似文献
9.
Three-dimensional quantitative structure–activity relationship (3D-QSAR) studies were performed on a series of substituted 1,4-dihydroindeno[1,2-c]pyrazoles inhibitors, using molecular docking and comparative molecular field analysis (CoMFA). The docking results from GOLD 3.0.1 provide a reliable conformational alignment scheme for the 3D-QSAR model. Based on the docking conformations and alignments, highly predictive CoMFA model was built with cross-validated q 2 value of 0.534 and non-cross-validated partial least-squares analysis with the optimum components of six showed a conventional r 2 value of 0.911. The predictive ability of this model was validated by the testing set with a conventional r 2 value of 0.812. Based on the docking and CoMFA, we have identified some key features of the 1,4-dihydroindeno[1,2-c]pyrazoles derivatives that are responsible for checkpoint kinase 1 inhibitory activity. The analyses may be used to design more potent 1,4-dihydroindeno[1,2-c]pyrazoles derivatives and predict their activity prior to synthesis. 相似文献
10.
Malkeet Singh Bahia Shravan Kumar Gunda Shwetha Reddy Gade Saikh Mahmood Ravikumar Muttineni Om Silakari 《Journal of molecular modeling》2011,17(1):9-19
Anthranilic acid based derivatives (ANTs) have been identified as a novel class of potent tumor necrosis factor-α converting
enzyme (TACE) inhibitors. A computational strategy based on molecular docking studies, followed by CoMFA and CoMSIA analyses
has been performed to elucidate the atomic details of the TACE/ANT interactions and also to identify the most important features
impacting TACE inhibitory activity of ANTs. The CoMSIA model resulted to be slightly more predictive than CoMFA model, and
gave conventional r2 0.991, rcv2 0.793, q2 0.777, SEE 0.050, F-value 655.610, and rtest2 0.871. The 3D-QSAR field contributions and the structural features of the TACE binding site showed a good correlation. These
studies will be useful to design new TACE inhibitors with improved potency. 相似文献
11.
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
12.
3D-QSAR models of a series of fluorinated hexahydropyrimidine derivatives with cytotoxic activities have been developed using CoMFA and CoMSIA. These models provide a better understanding of the mechanism of action and structure–activity relationship of these compounds. By applying leave-one-out (LOO) cross validation study, the best predictive CoMFA model was achieved with 3 as the optimum number of components, which gave rise to a non-cross-validated r2 value of 0.978, and standard error of estimate of 0.059, and F value of 144.492. Similarly, the best predictive CoMSIA model was derived with 4 as the number of components, r2 value of 0.999, F value of 4381.143, and standard error of estimate, 0.011. The above models will inspire the design and synthesis of novel hexahydropyrimidines with enhanced potency and selectivity. 相似文献
13.
Diabetes remains a life-threatening disease. The clinical profile of diabetic subjects is often worsened by the presence of
several long-term complications, for example neuropathy, nephropathy, retinopathy, and cataract. Comparative molecular field
analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on a series of 2,4-thiazolidinediones
derivatives as aldose reductase (ALR2) inhibitors. Molecular ligand superimposition on a template structure was finished by
the database alignment method. The 3D-QSAR models resulted from 44 molecules gave q
2 values of 0.773 and 0.817, r
2 values of 0.981 and 0.979 for CoMFA and CoMSIA, respectively. The contour maps from the models indicated that a large volume
group next to the R-substituent will increase the ALR2 inhibitory activity. In fact, adding a -CH2COOH substituent at the R-position would generate a new compound with higher predicted activity. 相似文献
14.
3D-QSAR studies on the derivatives of 1-(3,3-diphenylpropyl)-piperidinyl amide and urea as CCR5 receptor antagonists were
performed by comparative molecular field analysis (CoMFA) and comparative molecular similarity indices (CoMSIA) methods to
rationalize the structural requirements responsible for the inhibitory activity of these compounds. The global minimum energy
conformer of the template molecule, the most active and pharmacokinetically stable molecule of the series, was obtained by
systematic search and used to build structures of the molecules in the dataset. The best predictions for the CCR5-receptor
were obtained with the CoMFA standard model (q
2 = 0.787, r
2 = 0.962) and CoMSIA model combined steric, electrostatic and hydrophobic fields (q
2 = 0.809, r
2 = 0.951). The predictive ability of CoMFA and CoMSIA were determined using a test set of 12 compounds giving predictive correlation
coefficients of 0.855 and 0.83, respectively, indicating good predictive power. Further, the robustness of the model was verified
by bootstrapping analysis. The contour maps produced by the CoMFA and CoMSIA models were used to identify the structural features
relevant to the biological activity in this series. Based on the CoMFA and CoMSIA analysis, we have identified some key features
in the series that are responsible for CCR5 antagonistic activity which may be used to design more potent 1-(3,3-diphenylpropyl)-piperidinyl
derivatives and predict their activity prior to synthesis.
Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users. 相似文献
15.
Seventy-five 1,5,6,7-tetrahydro-pyrrolo[3,2-C]pyridinone derivatives displaying potent activities against Cdc7 kinase were
selected to establish 3D-QSAR models using CoMFA and CoMSIA methods. Internal and external cross-validation techniques were
investigated as well as some measures including region focusing, progressive scrambling, bootstraping and leave-group-out.
The satisfactory CoMFA model predicted a q
2 value of 0.836 and an r
2 value of 0.950, indicating that electrostatic and steric properties play a significant role in potency. The best CoMSIA model,
based on a combination of steric, electrostatic and H-bond acceptor effects, predicted a q
2 value of 0.636 and an r
2 value of 0.907. The models were graphically interpreted using contour plots which provided insight into the structural requirements
for increasing the activity of a compound. The final 3D-QSAR results could be used for rational design of potent inhibitors
against Cdc7 kinase. 相似文献
16.
Patrice L. Jackson K.R. Scott William M. Southerland Ya-Yin Fang 《Bioorganic & medicinal chemistry》2009,17(1):133-140
3D-QSAR studies comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were carried out on 26 structurally diverse subcutaneous pentylenetetrazol (scPTZ) active enaminone analogues, previously synthesized in our laboratory. CoMFA and CoMSIA were employed to generate models to define the specific structural and electrostatic features essential for enhanced binding to the putative GABA receptor. The 3D-QSAR models demonstrated a reliable ability to predict the CLog P of the active anticonvulsant enaminones, resulting in a q2 of 0.558 for CoMFA, and a q2 of 0.698 for CoMSIA. The outcomes of the contour maps for both models provide detailed insight for the structural design of novel enaminone derivatives as potential anticonvulsant agents. 相似文献
17.
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
18.
Zaheer- Ul-Haq Abdul Wadood Reaz Uddin 《Journal of enzyme inhibition and medicinal chemistry》2013,28(1):272-278
Urease (EC 3.5.1.5) serves as a virulence factor in pathogens that are responsible for the development of many diseases in humans and animals. Urease allows soil microorganisms to use urea as a source of nitrogen and aid in the rapid break down of urea-based fertilizers resulting in phytopathiCIT000y. It has been well established that hydroxamic acids are the potent inhibitors of urease activity. The 3D-QSAR studies on thirty five hydroxamic acid derivatives as known urease inhibitors were performed by Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) methods to determine the factors required for the activity of these compounds. The CoMFA model produced statistically significant results with cross-validated (q2) 0.532 and conventional (r2) correlation coefficients 0.969.The model indicated that the steric field (70.0%) has greater influence on hydroxamic acid inhibitors than the electrostatic field (30.0%). Furthermore, five different fields: steric, electrostatic, hydrophobic, H-bond donor and H-bond acceptor assumed to generate the CoMSIA model, which gave q2 0.665 and r2 0.976.This model showed that steric (43.0%), electrostatic (26.4%) and hydrophobic (20.3%) properties played a major role in urease inhibition. The analysis of CoMFA and CoMSIA contour maps provided insight into the possible modification of the hydroxamic acid derivatives for improved activity. 相似文献
19.
Three-dimensional quantitative structure-activity relationship (3D-QSAR) analyses using CoMFA and CoMSIA methods were conducted
on a series of fluoropyrrolidine amides as dipeptidyl peptidase IV (DP-IV) inhibitors. The selected ligands were docked into
the binding site of the 3D model of DP-IV using the GOLD software, and the possible interaction models between DP-IV and the
inhibitors were obtained. Based on the binding conformations of these fluoropyrrolidine amides and their alignment inside
the binding pocket of DP-IV, predictive 3D-QSAR models were established by CoMFA and CoMSIA analyses, which had conventional
r
2 and cross-validated coefficient values () up to 0.982 and 0.555 for CoMFA and 0.953 and 0.613 for CoMSIA, respectively. The predictive ability of these models was
validated by six compounds that were in the testing set. Structure-based investigations and the final 3D-QSAR results provide
the guide for designing new potent inhibitors. 相似文献
20.
Inhibition of the protein chaperone Hsp90α is a promising approach for cancer therapy. In this work, a molecular modeling
study combining pharmacophore model, molecular docking and three-dimensional quantitative structure-activity relationships
(3D-QSAR) was performed to investigate a series of pyrazole/isoxazole scaffold inhibitors of human Hsp90α. The pharmacophore
model can provide the essential features required for the biological activities of the inhibitors. The molecular docking study
can give insight into the binding mode between Hsp90α and its inhibitors. 3D-QSAR based on CoMFA and CoMSIA models were performed
from three different strategies for conformational selection and alignment. The receptor-based models gave the most statistically
significant results with cross-validated q
2 values of 0.782 and 0.829 and r
2 values of 0.909 and 0.968, for CoMFA and CoMSIA respectively. Furthermore, the 3D contour maps superimposed within the binding
site of Hsp90α could help to understand the pivotal interaction and the structural requirements for potent Hsp90α inhibitors.
The results show 4-position of pyrazole/isoxazole ring requires bulky and hydrophobic groups, and bulky and electron repulsion
substituent of 5-amides is favorable for enhancing activity. This study will be helpful for the rational design of new potent
Hsp90α inhibitors. 相似文献