scholarly journals Investigating the Molecular Basis of N-Substituted 1-Hydroxy-4-Sulfamoyl-2-Naphthoate Compounds Binding to Mcl1

Processes ◽  
2019 ◽  
Vol 7 (4) ◽  
pp. 224 ◽  
Author(s):  
Singaravelu ◽  
Balasubramanian ◽  
Marimuthu
Keyword(s):  
Molecular Mechanism ◽  
Md Simulation ◽  
External Validation ◽  
Myeloid Cell ◽  
3D Qsar ◽  
Qsar Model ◽  
Maximum Activity ◽  
Hydrogen Bond Donor ◽  
Contour Maps ◽  
Substituted 1

Myeloid cell leukemia-1 (Mcl1) is an anti–apoptotic protein that has gained considerable attention due to its overexpression activity prevents cell death. Therefore, a potential inhibitor that specifically targets Mcl1 with higher binding affinity is necessary. Recently, a series of N-substituted 1-hydroxy-4-sulfamoyl-2-naphthoate compounds was reported that targets Mcl1, but its binding mechanism remains unexplored. Here, we attempted to explore the molecular mechanism of binding to Mcl1 using advanced computational approaches: pharmacophore-based 3D-QSAR, docking, and MD simulation. The selected pharmacophore—NNRRR—yielded a statistically significant 3D-QSAR model containing high confidence scores (R2 = 0.9209, Q2 = 0.8459, and RMSE = 0.3473). The contour maps—comprising hydrogen bond donor, hydrophobic, negative ionic and electron withdrawal effects—from our 3D-QSAR model identified the favorable regions crucial for maximum activity. Furthermore, the external validation of the selected model using enrichment and decoys analysis reveals a high predictive power. Also, the screening capacity of the selected model had scores of 0.94, 0.90, and 8.26 from ROC, AUC, and RIE analysis, respectively. The molecular docking of the highly active compound—C40; 4-(N-benzyl-N-(4-(4-chloro-3,5-dimethylphenoxy) phenyl) sulfamoyl)-1-hydroxy-2-naphthoate—predicted the low-energy conformational pose, and the MD simulation revealed crucial details responsible for the molecular mechanism of binding with Mcl1.

scholarly journals 3D-QSAR Study of Indol-2-yl Ethanones Derivatives as Novel Indoleamine 2,3-Dioxygenase (IDO) Inhibitors

2012 ◽  
Vol 9 (4) ◽  
pp. 1753-1759 ◽  
Author(s):  
Kamlendra S. Bhadoriya ◽  
Shailesh V. Jain ◽  
Sanjaykumar B. Bari ◽  
Manish L. Chavhan ◽  
Kuldeep R. Vispute
Keyword(s):  
Nearest Neighbor ◽  
External Validation ◽  
3D Qsar ◽  
Qsar Model ◽  
Field Analysis ◽  
Qsar Study ◽  
Internal Validation ◽  
Contour Maps ◽  
Model Classification ◽  
Ido Inhibitors

3D-QSAR approach usingkNN-MFA was applied to a series of Indol-2-yl ethanones derivatives as novel IDO inhibitors. For the purpose, 22 compounds were used to develop models. To elucidate the structural properties required for IDO inhibitory activity, we report herek-nearest neighbor molecular field analysis (kNN-MFA)-based 3D-QSAR model for Indol-2-yl ethanones derivatives as novel IDO inhibitors. Overall model classification accuracy was 76.27% (q2= 0.7627, representing internal validation) in training set and 79.35% (pred_r2= 0.7935, representing external validation) in test set using sphere exclusion and forward as a method of data selection and variable selection, respectively. Contour maps using this approach showed that hydrophobic and steric effects dominantly determine binding affinities. The information rendered by 3D-QSAR model may lead to a better understanding of structural requirements of IDO inhibitors and can help in the design of novel potent molecules.

Computational Atom-based Three-Dimensional Quantitative Structure-Activity Relationship (3D QSAR) Model for Predicting Anti-Dengue Agents

2021 ◽  
Vol 16 (10) ◽  
pp. 50-58
Author(s):  
Ali Qusay Khalid ◽  
Vasudeva Rao Avupati ◽  
Husniza Hussain ◽  
Tabarek Najeeb Zaidan
Keyword(s):  
Dengue Fever ◽  
Three Dimensional ◽  
3D Qsar ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Activity Relationship ◽  
Quantitative Structure ◽  
Contour Maps ◽  
Structure Activity ◽  
Bioactive Ligands

Dengue fever is a viral infection spread by the female mosquito Aedes aegypti. It is a virus spread by mosquitoes found all over the tropics with risk levels varying depending on rainfall, relative humidity, temperature and urbanization. There are no specific medications that can be used to treat the condition. The development of possible bioactive ligands to combat Dengue fever before it becomes a pandemic is a global priority. Few studies on building three-dimensional quantitative structure-activity relationship (3D QSAR) models for anti-dengue agents have been reported. Thus, we aimed at building a statistically validated atom-based 3D-QSAR model using bioactive ligands reported to possess significant anti-dengue properties. In this study, the Schrodinger PhaseTM atom-based 3D QSAR model was developed and was validated using known anti-dengue properties as ligand data. This model was also tested to see if there was a link between structural characteristics and anti-dengue activity of a series of 3-acyl-indole derivatives. The established 3D QSAR model has strong predictive capacity and is statistically significant [Model: R2 Training Set = 0.93, Q2 (R2 Test Set) = 0.72]. In addition, the pharmacophore characteristics essential for the reported anti-dengue properties were explored using combined effects contour maps (coloured contour maps: blue: positive potential and red: negative potential) of the model. In the pathway of anti-dengue drug development, the model could be included as a virtual screening method to predict novel hits.

scholarly journals In Silico Ligand-Based Methods Targeting Porcupine Receptor Inhibitors with Potential Anticancer Effect

Proceedings ◽  
2018 ◽  
Vol 9 (1) ◽  
pp. 19
Author(s):  
Ana Borota ◽  
Luminita Crisan
Keyword(s):  
Wnt Signaling ◽  
In Silico ◽  
Pharmacophore Model ◽  
Correlation Coefficients ◽  
3D Qsar ◽  
Qsar Model ◽  
Hydrogen Bond Donor ◽  
Screening Process ◽  
Wnt Proteins ◽  
In Silico Study

Porcupine is a protein belonging to the O-acyltransferase family, involved in the catalyzing of palmitoylation of wingless-related integration (WNT) proteins. WNT signaling has significant roles in many physiological functions, e.g., hematopoiesis, homeostasis, neurogenesis, and apoptosis. Anomalous WNT signaling has been observed to be related to tumor generation, and metabolic and neurodegenerative disorders. Therefore, compounds that inhibit this pathway are of great interest for the development of therapeutic approaches. For a better understanding of the common traits of such compounds, we have undertaken an in silico study in order to develop a valid ligand-based pharmacophore model based on a series of porcupine inhibitors. The best pharmacophore hypothesis found after the 3D QSAR validation process is represented by the following features: one hydrogen bond donor (D), three rings (R) and one hydrophobic centroid (H). The 3D-QSAR model obtained using the DRRRH hypothesis shows statistically significant parameters: correlation coefficients for the training set: R2 of 0.90, and a predictive correlation coefficient for the test set, Q2 of 0.86. The assessment of the pharmacophore model was also done and provided very reliable metrics values (Receiver Operating Characteristic—ROC of 1; Robust Initial Enhancement—RIE of 17.97). Thereby, we obtained valuable results which can be further used in the virtual screening process for the discovery of new active compounds with potential anticancer activity.

scholarly journals A Modified 3D-QSAR Model Based on Ideal Point Method and Its Application in the Molecular Modification of Plasticizers with Flame Retardancy and Eco-Friendliness

Polymers ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 1942
Author(s):  
Haigang Zhang ◽  
Chengji Zhao ◽  
Hui Na
Keyword(s):  
Flame Retardancy ◽  
Evaluation Method ◽  
Comprehensive Evaluation ◽  
Ideal Point ◽  
Three Dimensional ◽  
3D Qsar ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Point Method ◽  
Contour Maps

The addition of plasticizers makes plastics flammable, and thus, poses a potential risk to the environment. In previous researches, plasticizers with flame retardancy had been synthesized, but their eco-friendliness had not been tested or described. Thus, in this paper, eco-friendliness plasticizers with flame retardancy were designed based on phthalic acid esters (PAEs), which are known as common plasticizers and major plastic additives. For a comprehensive analysis, such as flammability, biotoxicity, and enrichment effects, 17 PAEs’ comprehensive evaluation values were calculated based on the ideal point method. Further, a multi-effect three-dimensional quantitative structure-activity relationship (3D-QSAR) model of PAEs’ flammability, biotoxicity and enrichment effects was constructed. Thus, 18 dimethyl phthalate (DMP) derivatives and 20 diallyl phthalate (DAP) derivatives were designed based on three-dimensional contour maps. Through evaluation of eco-friendliness and flammability, six eco-friendly PAE derivatives with flame retardancy were screened out. Based on contour maps analysis, it was confirmed that the introduction of large groups and hydrophobic groups was beneficial to the simultaneous improvement of PAEs’ comprehensive effects, and multiple effects. In addition, the group properties were correlated significantly with improved degrees of the comprehensive effects of corresponding PAE derivatives, confirming the feasibility of the comprehensive evaluation method and modified scheme.

Improved 3D-QSAR Prediction by Multiple-Conformational Alignments and Molecular Docking Studies to Design and Discover HIV-I Protease Inhibitors

2020 ◽  
Vol 18 ◽  
Author(s):  
Paresh K. Patel ◽  
Hardik G. Bhatt
Keyword(s):  
Hydrogen Bond ◽  
Drug Design ◽  
Protease Inhibitors ◽  
Correlation Coefficient ◽  
3D Qsar ◽  
Qsar Model ◽  
Hydrogen Bond Acceptor ◽  
Contour Maps ◽  
Validation Parameters ◽  
Predicted Values

Background: Inhibition of HIV-I protease enzyme is a strategic step for providing better treatment in retrovirus infections which avoids resistance and has less toxicities. Objectives: In the course of our research to discover new and potent protease inhibitors, 3D-QSAR (CoMFA and CoMSIA) models were generated using 3 different alignment techniques including multifit alignment, docking based and Distill based alignment for 63 compounds. Novel molecules were designed from the output of this study Methods: Total 3 alignment methods were used to generate CoMFA and CoMSIA models. A Distill based alignment method was considered a better method according to different validation parameters. A 3D-QSAR model was generated and contour maps were discussed. The biological activity of designed molecules were predicted using generated QSAR model to validate QSAR. The newly designed molecules were docked to predict binding affinity. Results: In CoMFA, leave one out cross validated coefficient (q 2 ), conventional coefficient (r 2 ) and predicted correlation coefficient (r 2 Predicted) values were found to be 0.721, 0.991 and 0.780, respectively. The best obtained CoMSIA model also had significant cross validated coefficient (q 2 ), conventional coefficient (r 2 ) and predicted correlation coefficient (r 2 Predicted) values of 0.714, 0.987 and 0.721, respectively. Steric and electrostatic contour maps generated from CoMFA and hydrophobic and hydrogen bond donor and hydrogen bond acceptor contour maps from CoMSIA models were used to design new and bioactive protease inhibitors by incorporating bioisosterism and knowledge based structure activity relationship. Conclusion: The results from both these approaches, ligand based drug design and structure based drug design, are adequate and promising to discover protease inhibitors.

scholarly journals Molecular Modeling Studies of Substituted 2,4,5-Trisubstituted Triazolinones Aryl and Nonaryl Derivatives as Angiotensin II AT1Receptor Antagonists

2013 ◽  
Vol 2013 ◽  
pp. 1-14 ◽  
Author(s):  
Mukesh C. Sharma ◽  
D. V. Kohli ◽  
Smita Sharma
Keyword(s):  
Simulated Annealing ◽  
Statistical Significance ◽  
External Validation ◽  
Feature Selection Method ◽  
3D Qsar ◽  
Field Analysis ◽  
Molecular Field ◽  
Hydrogen Bond Donor ◽  
Molecular Field Analysis ◽  
Qsar Models

The development of new therapies to treat hypertension and cardiovascular diseases. A series of 2,4,5-trisubstituted triazolinones aryl and nonaryl derivatives were subjected toGroup-based QSAR,k-nearest neighbourmolecular field analysis, and pharmacophore mapping. Multiple linear regression (MLR) methodology coupled with feature selection method namely simulated annealing, was applied to derive Group based QSAR models which were further validated for statistical significance and predictive ability by internal and external validation. The best physicochemical descriptors, namely, R1chiV1, R2T_N_O_3, R2chlorines count, R2T_C_N_4, and R2SssNHE index, contribute significantly to the biological activity. The statistically significant best Group-based QSAR model hasr2=0.8357andq2=0.7266with pred_r2=0.8138. The 3D-QSAR studies were performed using the simulated annealing selectionk-nearest neighbormolecular field analysis approach; a leave-one-out cross-validated correlation coefficientq2=0.7461and predicate activity pred_r2=0.7790were obtained. Contour maps using this approach showed that steric, electrostatic, and hydrophobic effects dominantly determine binding affinities. Pharmacophore hypotheses were generated by the mol sign module and found to contain common features like hydrogen bond donor acceptor, donor, positive, negative ionizable, and hydrophobic features. This model can be used for preliminary screening of large number of substituted 3H-1,-2,-4 triazolinone aryl and nonaryl derivatives. The information rendered by 3D-QSAR models may lead to a better understanding of structural requirements of triazolinone aryl and nonaryl derivatives and also aid in designing novel potent antihypertensive molecules.

scholarly journals 3D-QSAR and Molecular Docking Approaches for the Identification of Novel Phyto-inhibitors of the Cyclin-dependent Kinase 4

2021 ◽  
Vol 9 (2) ◽  
pp. 42-48
Keyword(s):  
Pearson Correlation ◽  
External Validation ◽  
3D Qsar ◽  
Qsar Model ◽  
Cyclin Dependent Kinase ◽  
Lipinski’S Rule ◽  
Hydrogen Bond Interactions ◽  
Anti Cancer ◽  
R Value ◽  
Potential Inhibitors

Cyclin-dependent kinase 4 (CDK4) is an important target in designing anti-cancer drugs. The activation of CDK4 results in phosphorylation of the retinoblastoma gene product. In this study, a total of one hundred and seventy-eight phytochemicals characterized from various anti-cancer plants were retrieved from the literature and screened against the orthosteric sites of CDK4. Lipinski's rule of five was used to determine the drug-likeness and the activities of the lead phytochemicals. Bioassay IC50 data for reported CDK4 inhibitors from the Chembl database were used to generate the 3D-QSAR model for CDK4 inhibition. The virtual screening showed catechin, kaempferol and quercetin as the lead phytochemicals. A positive correlation of 0.829 between the pIC50 and glide scores at p<0.01 revealed that computers can accurately predict experimental data. The ADME screening showed that naringenin, aporphine, catechin, coreximine and stepharine obey the Lipinski rules of five. The generated model was robust and thoroughly validated with a Pearson correlation R value of 0.934 and R² value of 0.872. The model with an adjusted R² value of 0.769 possesses good external validation. Aporphine, catechin, naringenin, stepharine and coreximine form important hydrogen bond interactions. These interactions are likely responsible for their inhibition of CDK4. The lead phytochemicals are drug-like compounds and potential inhibitors of CDK4.

scholarly journals Insights into the Structural Requirements of 2(S)-Amino-6-Boronohexanoic Acid Derivatives as Arginase I Inhibitors: 3D-QSAR, Docking, and Interaction Fingerprint Studies

2018 ◽  
Vol 19 (10) ◽  
pp. 2956 ◽  
Author(s):  
José Velázquez-Libera ◽  
Carlos Navarro-Retamal ◽  
Julio Caballero
Keyword(s):  
Binding Site ◽  
External Validation ◽  
Three Dimensional ◽  
3D Qsar ◽  
Qsar Model ◽  
Cerebrovascular Diseases ◽  
Binding Modes ◽  
Structure Activity ◽  
Arginase I ◽  
Important Enzyme

Human arginase I (hARGI) is an important enzyme involved in the urea cycle; its overexpression has been associated to cardiovascular and cerebrovascular diseases. In the last years, several congeneric sets of hARGI inhibitors have been reported with possible beneficial roles for the cardiovascular system. At the same time, crystallographic data have been reported including hARGI–inhibitor complexes, which can be considered for the design of novel inhibitors. In this work, the structure–activity relationship (SAR) of Cα substituted 2(S)-amino-6-boronohexanoic acid (ABH) derivatives as hARGI inhibitors was studied by using a three-dimensional quantitative structure–activity relationships (3D-QSAR) method. The predictivity of the obtained 3D-QSAR model was demonstrated by using internal and external validation experiments. The best model revealed that the differential hARGI inhibitory activities of the ABH derivatives can be described by using steric and electrostatic fields; the local effects of these fields in the activity are presented. In addition, binding modes of the above-mentioned compounds inside the hARGI binding site were obtained by using molecular docking. It was found that ABH derivatives adopted the same orientation reported for ABH within the hARGI active site, with the substituents at Cα exposed to the solvent with interactions with residues at the entrance of the binding site. The hARGI residues involved in chemical interactions with inhibitors were identified by using an interaction fingerprints (IFPs) analysis.

scholarly journals Molecular Modeling and Design Studies of Purine Derivatives as Novel CDK2 Inhibitors

Molecules ◽  
2018 ◽  
Vol 23 (11) ◽  
pp. 2924 ◽  
Author(s):  
Gaomin Zhang ◽  
Yujie Ren
Keyword(s):  
Molecular Docking ◽  
Molecular Modeling ◽  
Virtual Screening ◽  
Interaction Mechanism ◽  
3D Qsar ◽  
Md Simulations ◽  
Qsar Model ◽  
Purine Derivatives ◽  
Hydrogen Bond Donor ◽  
Comfa Model

Cyclin-dependent kinase 2 (CDK2) is a potential target for treating cancer. Purine heterocycles have attracted particular attention as the scaffolds for the development of CDK2 inhibitors. To explore the interaction mechanism and the structure–activity relationship (SAR) and to design novel candidate compounds as potential CDK2 inhibitors, a systematic molecular modeling study was conducted on 35 purine derivatives as CDK2 inhibitors by combining three-dimensional quantitative SAR (3D-QSAR), virtual screening, molecular docking, and molecular dynamics (MD) simulations. The predictive CoMFA model (q2 = 0.743, r pred 2 = 0.991), the CoMSIA model (q2 = 0.808, r pred 2 = 0.990), and the Topomer CoMFA model (q2 = 0.779, r pred 2 = 0.962) were obtained. Contour maps revealed that the electrostatic, hydrophobic, hydrogen bond donor and steric fields played key roles in the QSAR models. Thirty-one novel candidate compounds with suitable predicted activity (predicted pIC50 > 8) were designed by using the results of virtual screening. Molecular docking indicated that residues Asp86, Glu81, Leu83, Lys89, Lys33, and Gln131 formed hydrogen bonds with the ligand, which affected activity of the ligand. Based on the QSAR model prediction and molecular docking, two candidate compounds, I13 and I60 (predicted pIC50 > 8, docking score > 10), with the most potential research value were further screened out. MD simulations of the corresponding complexes of these two candidate compounds further verified their stability. This study provided valuable information for the development of new potential CDK2 inhibitors.

Development of 2D, 3D-QSAR and Pharmacophore Modeling of Chalcones for the Inhibition of Monoamine Oxidase B

2021 ◽  
Vol 24 ◽  
Author(s):  
Bijo Mathew ◽  
Chonny Herrera-Acevedo ◽  
Sanal Dev ◽  
T. M. Rangarajan ◽  
Mohamed Saheer Kuruniyan ◽  
...  
Keyword(s):  
Cross Validation ◽  
Molecular Descriptors ◽  
External Validation ◽  
3D Qsar ◽  
Qsar Model ◽  
Pharmacophore Modeling ◽  
Pharmacophore Modelling ◽  
Mao B ◽  
Chalcone Derivatives ◽  
2D And 3D

Background: Selective and reversible types of MAO-B inhibitors have emerged as promising candidates for the management of neurodegenerative diseases. Several functionalized chalcone derivatives were shown to have potential reversible MAO-B inhibitory activity, which have recently been reported from our laboratory. Methods: With the experimental results of about 70 chalcone derivatives, we further developed a pharmacophore modelling, and 2D and 3D- QSAR analyses of these reported chalcones for MAO-B inhibition. Results: The 2D-QSAR model presented four variables (MATS7v, GATS 1i and 3i, and C-006) from 143 Dragon 7 molecular descriptors, with a r2 value of 0.76 and a Q2cv for cross-validation equal to 0.72. An external validation also was performed using 11 chalcones, obtaining a Q2ext value of 0.74. The second 3D-QSAR model using MLR (multiple linear regression) was built starting from 128 Volsurf+ molecular descriptors, being identified as 4 variables (Molecular descriptors): D3, CW1 and LgS11, and L2LGS. Adetermination coefficient (r2) value of 0.76 and a Q2cv for cross-validation equal to 0.72 were obtained for this model. An external validation also was performed using 11 chalcones and a Q2ext value of 0.74 was found. Conclusion: This report exhibited a good correlation and satisfactory agreement between experiment and theory.

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