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1.
《Journal of enzyme inhibition and medicinal chemistry》2013,28(6):792-804
Recently, benzothiophenes attract much attention of interest due to its possible inhibitory activity targeting FIXa, a blood coagulation factor that is essential for the amplification or consolidation phase of blood coagulation. To explore this inhibitory mechanism, three-dimensional quantitative structure–activity relationship (3D-QSAR), molecular docking and molecular dynamics (MD) studies on a series of 84 benzothiophene analogues, for the first time, were performed. As a result, a highly predictive CoMFA model was developed with the q2?=?0.52, r2?=?0.97 and r2pred?=?0.81, respectively. The CoMFA contour maps, the docking analysis, as well as the MD simulation results are all in a good agreement, proving the reliability and robustness of the model. These models and the information, we hoped, would be helpful in screening and development of novel drugs against thrombosis prior to synthesis. 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.
Fereshteh Shiri Maryam Salahinejad Rahmatollah Dijoor Massoud Nejati-Yazdinejad 《Journal of receptor and signal transduction research》2018,38(2):151-165
Pathogenic Gram-negative bacteria are responsible for nearly half of the serious human infections. Hologram quantitative structure–activity relationships (HQSAR), comparative molecular field analysis (CoMFA), and comparative molecular similarity index analysis (CoMSIA) were implemented on a group of 32 of potent Gram-negative LpxC inhibitors. The most effective HQSAR model was obtained using atoms, bonds, donor, and acceptor as fragment distinction. The cross-validated correlation coefficient (q2), non-cross-validated correlation coefficient (r2), and predictive correlation coefficient (r2Pred) for test set of HQSAR model were 0.937, 0.993, and 0.892, respectively. The generated models were found to be statistically significant as the CoMFA model had (r2?=?0.967, q2?=?0.804, r2Pred?=?0.827); the CoMSIA model had (r2?=?0.963, q2?=?0.752, r2Pred?=?0.857). Molecular docking was employed to validate the results of the HQSAR, CoMFA, and CoMSIA models. Based on the obtained information, six new LpxC inhibitors have been designed. 相似文献
4.
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
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.
Amirreza Dowlati Beirami Zahra Hajimahdi 《Journal of biomolecular structure & dynamics》2019,37(11):2999-3006
A series of 26 selective COX-2 inhibitors which reported previously by our laboratory was selected to generate three-dimensional quantitative structure activity relationship (3D-QSAR) model. Active conformation of each molecule was predicted by docking studies and used for molecular alignment. Activity of 20 molecules as a train set was predicted using three methods including comparative molecular field analysis (CoMFA), CoMFA region focusing (CoMFA-RG) and comparative molecular similarity index analysis (CoMSIA). The best models of CoMFA-RG and CoMSIA revealed correlation coefficients r2 of 0.955 and 0.947, the leave one out cross-validation coefficients q2 of 0.573 and 0.574, respectively. In addition, CoMFA-RG and CoMSIA models were validated by a test set of six molecules with predicted coefficients r2pred of 0.644 and 0.799, respectively. Contour maps of generated models provided fruitful information about structural aspect of molecules that affected their COX-2 inhibitory activity. Based on three models results, steric and electrostatic properties are the most important factors in controlling the activity of the molecules. Results of CoMFA-RG and CoMSIA models were utilized to design new molecules. Comparison of experimental and predicted pIC50 values of designed molecules indicated that CoMFA-RG had the more predictive ability.
Communicated by Ramaswamy H. Sarma 相似文献
7.
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
8.
Multiple receptors conformation docking (MRCD) and clustering of dock poses allows seamless incorporation of receptor binding
conformation of the molecules on wide range of ligands with varied structural scaffold. The accuracy of the approach was tested
on a set of 120 cyclic urea molecules having HIV-1 protease inhibitory activity using 12 high resolution X-ray crystal structures
and one NMR resolved conformation of HIV-1 protease extracted from protein data bank. A cross validation was performed on
25 non-cyclic urea HIV-1 protease inhibitor having varied structures. The comparative molecular field analysis (CoMFA) and
comparative molecular similarity indices analysis (CoMSIA) models were generated using 60 molecules in the training set by
applying leave one out cross validation method, rloo2 values of 0.598 and 0.674 for CoMFA and CoMSIA respectively and non-cross validated regression coefficient r2 values of 0.983 and 0.985 were obtained for CoMFA and CoMSIA respectively. The predictive ability of these models was determined
using a test set of 60 cyclic urea molecules that gave predictive correlation (rpred2) of 0.684 and 0.64 respectively for CoMFA and CoMSIA indicating good internal predictive ability. Based on this information
25 non-cyclic urea molecules were taken as a test set to check the external predictive ability of these models. This gave
remarkable out come with rpred2 of 0.61 and 0.53 for CoMFA and CoMSIA respectively. The results invariably show that this method is useful for performing
3D QSAR analysis on molecules having different structural motifs. 相似文献
9.
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
10.
11.
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
12.
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
13.
Junxia Zheng Hao Kong James M. Wilson Jialiang Guo Yiqun Chang Mengjia Yang Gaokeng Xiao Pinghua Sun 《PloS one》2014,9(4)
Several small-molecule CDK inhibitors have been identified, but none have been approved for clinical use in the past few years. A new series of 4-[(3-hydroxybenzylamino)-methylene]-4H-isoquinoline-1,3-diones were reported as highly potent and selective CDK4 inhibitors. In order to find more potent CDK4 inhibitors, the interactions between these novel isoquinoline-1,3-diones and cyclin-dependent kinase 4 was explored via in silico methodologies such as 3D-QSAR and docking on eighty-one compounds displaying potent selective activities against cyclin-dependent kinase 4. Internal and external cross-validation techniques were investigated as well as region focusing, bootstraping and leave-group-out. A training set of 66 compounds gave the satisfactory CoMFA model (q
2 = 0.695, r
2 = 0.947) and CoMSIA model (q
2 = 0.641, r
2 = 0.933). The remaining 15 compounds as a test set also gave good external predictive abilities with r
2
pred values of 0.875 and 0.769 for CoMFA and CoMSIA, respectively. The 3D-QSAR models generated here predicted that all five parameters are important for activity toward CDK4. Surflex-dock results, coincident with CoMFA/CoMSIA contour maps, gave the path for binding mode exploration between the inhibitors and CDK4 protein. Based on the QSAR and docking models, twenty new potent molecules have been designed and predicted better than the most active compound 12 in the literatures. The QSAR, docking and interactions analysis expand the structure-activity relationships of constrained isoquinoline-1,3-diones and contribute towards the development of more active CDK4 subtype-selective inhibitors. 相似文献
14.
Aurora-A, the most widely studied isoform of Aurora kinase overexpressed aberrantly in a wide variety of tumors, has been
implicated in early mitotic entry, degradation of natural tumor suppressor p53 and centrosome maturation and separation; hence,
potent inhibitors of Aurora-A may be therapeutically useful drugs in the treatment of various forms of cancer. Here, we report
an in silico study on a group of 220 reported Aurora-A inhibitors with six different substructures. Three-dimensional quantitative
structure–activity relationship (3D-QSAR) studies were carried out using comparative molecular field analysis (CoMFA) and
comparative molecular similarity indices analysis (CoMSIA) techniques on this series of molecules. The resultant optimum 3D-QSAR
models exhibited an r
cv2 value of 0.404-0.582 and their predictive ability was validated using an independent test set, ending in r
pred2 0.512-0.985. In addition, docking studies were employed to explore these protein–inhibitor interactions at the molecular
level. The results of 3D-QSAR and docking analyses validated each other, and the key structural requirements affecting Aurora-A
inhibitory activities, and the influential amino acids involved were identified. To the best of our knowledge, this is the
first report on 3D-QSAR modeling of Aurora-A inhibitors, and the results can be used to accurately predict the binding affinity
of related analogues and also facilitate the rational design of novel inhibitors with more potent biological activities. 相似文献
15.
《Bioorganic & medicinal chemistry》2016,24(2):73-84
In this work, 48 thrombin inhibitors based on the structural scaffold of dabigatran were analyzed using a combination of molecular modeling techniques. We generated three-dimensional quantitative structure–activity relationship (3D-QSAR) models based on three alignments for both comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) to highlight the structural requirements for thrombin protein inhibition. In addition to the 3D-QSAR study, Topomer CoMFA model also was established with a higher leave-one-out cross-validation q2 and a non-cross-validation r2, which suggest that the three models have good predictive ability. The results indicated that the steric, hydrophobic and electrostatic fields play key roles in QSAR model. Furthermore, we employed molecular docking and re-docking simulation explored the binding relationship of the ligand and the receptor protein in detail. Molecular docking simulations identified several key interactions that were also indicated through 3D-QSAR analysis. On the basis of the obtained results, two compounds were designed and predicted by three models, the biological evaluation in vitro (IC50) demonstrated that these molecular models were effective for the development of novel potent thrombin inhibitors. 相似文献
16.
Juan Wang Chenxi Zhao Jing Tu Hong Yang Wenjuan Lv 《Journal of biomolecular structure & dynamics》2019,37(11):2913-2925
Tuberculosis (TB) is an infectious disease that causes a number of deaths, and the development of new, safer and more adequate TB inhibitors/drugs has become a necessity as well as a great challenge. Mycobacterial DNA gyrase B subunit has been identified to be one of the potentially underexploited drug targets in the field of anti-tubercular drug discovery. To design the novel and potent Mycobacterium tuberculosis (MTB) inhibitors, we performed molecular modeling studies that combined the 3D-QSAR, molecular docking, molecular dynamics (MD) simulations, and binding free energy calculations. Forty eight quinoline-aminopiperidine inhibitors which act on DNA gyrase B subunit were used for constructing 3D-QSAR models. The results showed that the best CoMFA model had the high performance with q2?=?0.643, r2?=?0.947, while the best CoMSIA model yielded q2?=?0.536, r2?=?0.948. The contour map was in good agreement with the docking and MD simulations which strongly demonstrated that the molecular modeling was reliable. Based on this information, several potential compounds were designed and their inhibitory activities were also verified by the accomplished models and ADME/T predictions. We hope that our research could bring new ideas to facilitate the development of novel inhibitors with higher inhibitory activity for TB.
Communicated by Ramaswamy H. Sarma 相似文献
17.
Zhen Wang Li Ping Cheng Xing Hua Zhang Wan Pang Liang Li Jin Long Zhao 《Bioorganic & medicinal chemistry letters》2017,27(24):5429-5435
Neuraminidase (NA) is one of the particular potential targets for novel antiviral therapy. In this work, a series of neuraminidase inhibitors with the cyclohexene scaffold were studied based upon the combination of 3D-QSAR, molecular docking, and molecular dynamics techniques. The results indicate that the built 3D-QSAR models yield reliable statistical information: the correlation coefficient (r2) and cross-validation coefficient (q2) of CoMFA (comparative molecular field analysis) are 0.992 and 0.819; the r2 and q2 of CoMSIA (comparative molecular similarity analysis) are 0.992 and 0.863, respectively. Molecular docking and MD simulations were conducted to confirm the detailed binding mode of enzyme-inhibitor system. The new NA inhibitors had been designed, synthesized, and their inhibitory activities against group-1 neuraminidase were determined. One agent displayed excellent neuraminidase inhibition, with IC50 value of 39.6?μM against NA, while IC50 value for oseltamivir is 61.1?μM. This compound may be further investigated for the treatment of infection by the new type influenza virus. 相似文献
18.
Li Ping Cheng Tian Chi Wang Rao Yu Meng Li Jin Wen Huang 《Bioorganic & medicinal chemistry letters》2018,28(23-24):3622-3629
Neuraminidase (NA) is an important antiviral drug target. Zanamivir is one of the most potent NA inhibitors. In this paper, a series of zanamivir derivatives as potential NA inhibitors were studied by combination of molecular modeling techniques including 3D-QSAR, molecular docking, and molecular dynamics (MD) simulation. The results show that the best CoMFA (comparative molecular field analysis) model has q2?=?0.728 and r2?=?0.988, and the best CoMSIA (comparative molecular similarity indices analysis) model has q2?=?0.750 and r2?=?0.981, respectively. The built 3D-QSAR models show significant statistical quality and excellent predictive ability. Seven new NA inhibitors were designed and predicted. 20?ns of MD simulations were carried out and their binding free energies were calculated. Two designed compounds were selected to be synthesized and biologically evaluated by NA inhibition and virus inhibition assays. One compound (IC50?=?0.670?µM, SI?>?149) exhibits excellent antiviral activity against A/WSN/33 H1N1, which is superior to the reference drug zanamivir (IC50?=?0.873?µM, SI?>?115). The theoretical and experimental results may provide reference for development of new anti-influenza drugs. 相似文献
19.
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
20.
Vijay M. Khedkar Premlata K. Ambre Jitender Verma Mushtaque S. Shaikh Raghuvir R. S. Pissurlenkar Evans C. Coutinho 《Journal of molecular modeling》2010,16(7):1251-1268
HIV-1 protease is an obligatory enzyme in the replication process of the HIV virus. The abundance of structural information
on HIV-1PR has made the enzyme an attractive target for computer-aided drug design strategies. The daunting ability of the
virus to rapidly generate resistant mutants suggests that there is an ongoing need for new HIV-1PR inhibitors with better
efficacy profiles and reduced toxicity. In the present investigation, molecular modeling studies were performed on a series
of 54 cyclic urea analogs with symmetric P2/P2′ substituents. The binding modes of these inhibitors were determined by docking.
The docking results also provided a reliable conformational superimposition scheme for the 3D-QSAR studies. To gain insight
into the steric, electrostatic, hydrophobic and hydrogen-bonding properties of these molecules and their influence on the
inhibitory activity, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA)
were performed. Two different alignment schemes viz. receptor-based and atom-fit alignment, were used in this study to build the QSAR models. The derived 3D-QSAR models were found to be robust with statistically
significant r
2
and r
2
pred
values and have led to the identification of regions important for steric, hydrophobic and electronic interactions. The predictive
ability of the models was assessed on a set of molecules that were not included in the training set. Superimposition of the
3D-contour maps generated from these models onto the active site of enzyme provided additional insight into the structural
requirements of these inhibitors. The CoMFA and CoMSIA models were used to design some new inhibitors with improved binding
affinity. Pharmacokinetic and toxicity predictions were also carried out for these molecules to gauge their ADME and safety
profile. The computational results may open up new avenues for synthesis of potent HIV-1 protease inhibitors. 相似文献