scholarly journals Pharmacophore Modeling and Docking Studies on Some Nonpeptide-Based Caspase-3 Inhibitors

2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
Simant Sharma ◽  
Arijit Basu ◽  
R. K. Agrawal
Keyword(s):  
Neurodegenerative Disorders ◽  
Caspase 3 ◽  
3D Qsar ◽  
Qsar Model ◽  
Pharmacophore Modeling ◽  
Docking Studies ◽  
Aromatic Rings ◽  
Query Tool ◽  
Pharmacophore Hypothesis ◽  
Synthetic Derivatives

Neurodegenerative disorders are major consequences of excessive apoptosis caused by a proteolytic enzyme known as caspase-3. Therefore, caspase-3 inhibition has become a validated therapeutic approach for neurodegenerative disorders. We performed pharmacophore modeling on some synthetic derivatives of caspase-3 inhibitors (pyrrolo[3,4-c]quinoline-1,3-diones) using PHASE 3.0. This resulted in the common pharmacophore hypothesis AAHRR.6 which might be responsible for the biological activity: two aromatic rings (R) mainly in the quinoline nucleus, one hydrophobic (H) group (CH3), and two acceptor (A) groups (–C=O). After identifying a valid hypothesis, we also developed an atom-based 3D-QSAR model applying the PLS algorithm. The developed model was statistically robust (q2=0.53; pred_r2=0.80). Additionally, we have performed molecular docking studies, cross-validated our results, and gained a deeper insight into its molecular recognition process. Our developed model may serve as a query tool for future virtual screening and drug designing for this particular target.

scholarly journals In silico studies on smoothened human receptor and its antagonists in search of anticancer effects

2020 ◽  
Vol 85 (3) ◽  
pp. 335-346
Author(s):  
Ana Borota ◽  
Sorin Avram ◽  
Ramona Curpan ◽  
Alina Bora ◽  
Daniela Varga ◽  
...  
Keyword(s):  
Acquired Resistance ◽  
Area Under The Curve ◽  
Weighted Average ◽  
3D Qsar ◽  
Qsar Model ◽  
Docking Studies ◽  
Receptor Inhibition ◽  
In Silico Studies ◽  
Qsar Models ◽  
Pharmacophore Hypothesis

Lately, the cancers related with abnormal hedgehog (Hh) signalling pathway are targeted by smoothened (SMO) receptor inhibitors that are rapidly developing. Still, the problems of known inhibitors such as severe side effects, weak potency against solid tumors or even the acquired resistance need to be overcome by developing new suitable inhibitors. To explore the structural requirements of antagonists needed for SMO receptor inhibition, pharmacophore mapping, 3D-QSAR models, database screening and docking studies were performed. The best selected pharmacophore hypothesis based on which statistically significant atom-based 3D-QSAR model was developed (R2 = = 0.856, Q2 = 0.611 and Pearson-R = 0.817), was further subjected to dataset screening in order to evaluate its ability to prioritize active compounds over decoys. The efficiency of one four-points pharmacophore hypothesis (AAHR.524) was observed based on good evaluation metrics such as the area under the curve (0.795), and weighted average precision (0.835), suggesting that the model is trustworthy in predicting novel inhibitors against SMO receptor.

Validation of TZD Scaffold as Potential ARIs: Pharmacophore Modeling, Atom-based 3D QSAR and Docking Studies

2017 ◽  
Vol 20 (4) ◽  
Author(s):  
Lalita Dahiya ◽  
Manoj Kumar Mahapatra ◽  
Ramandeep Kaur ◽  
Vipin Kumar ◽  
Manoj Kumar
Keyword(s):  
3D Qsar ◽  
Pharmacophore Modeling ◽  
Docking Studies

scholarly journals STRUCTURAL EXPLORATION AND PHARMACOPHORIC INVESTIGATION OF PYRAZOLE BASED ANALOGS AS NOVEL HISTONE DEACETYLASE 1 INHIBITOR USING COMBINATORIAL STUDIES

2018 ◽  
Vol 10 (3) ◽  
pp. 90
Author(s):  
Avineesh Singh ◽  
Harish Rajak
Keyword(s):  
Molecular Docking ◽  
Histone Deacetylase ◽  
Histone Deacetylase Inhibitors ◽  
Research Work ◽  
3D Qsar ◽  
Qsar Model ◽  
Docking Studies ◽  
Inhibition Activity ◽  
Design Strategies ◽  
Histone Deacetylase 1

Objective: Histone deacetylase inhibitors (HDACi) have four essential pharmacophores as cap group, connecting unit, a linker moiety and zinc binding group for their anticancer and histone deacetylase (HDAC) inhibition activity. On the basis of this fact, the objective of this research was to evaluate the exact role of pyrazole nucleus as connecting unit and its role in the development of newer HDACi.Methods: Ligand and structure-based computer-aided drug design strategies such as pharmacophore and atom based 3D QSAR modelling, molecular docking and energetic based pharmacophore mapping have been frequently applied to design newer analogs in a precise manner. Herein, we have applied these combinatorial approaches to develop the structure-activity correlation among novel pyrazole-based derivatives.Results: the Pharmacophore-based 3D-QSAR model was developed employing Phase module and e-pharmacophore on compound 1. This 3D-QSAR model provides fruitful information regarding favourable and unfavourable substitution on pyrazole-based analogs for HDAC1 inhibition activity. Molecular docking studies indicated that all the pyrazole derivatives bind with HDAC1 proteins and showed critical hydrophobic interaction with 5ICN and 4BKX HDAC1 proteins.Conclusion: The outcome of the present research work clearly indicated that pyrazole nucleus added an essential hydrophobic feature in cap group and could be employed to design the ligand molecules more accurately.

scholarly journals COMBINATORIAL PHARMACOPHORE MODELING AND ATOM BASED 3D QSAR STUDIES OF BENZOTHIADIAZINES AS HCV-NS5B INHIBITORS

2018 ◽  
Vol 10 (3) ◽  
pp. 43
Author(s):  
Prasanthi Polamreddy ◽  
Vinita Vishwakarma ◽  
Manoj Kumar Mahto
Keyword(s):  
Virtual Screening ◽  
Correlation Coefficient ◽  
Current Model ◽  
Pharmacophore Model ◽  
3D Qsar ◽  
Qsar Model ◽  
Pharmacophore Modeling ◽  
Structural Protein ◽  
Pearson's R ◽  
Pearson’S R

Objective: The objective of the current study was to elucidate the 3D pharmacophoric features of benzothiadiazine derivatives that are crucial for inhibiting Hepatitis C virus (HCV) Non-structural protein 5B (NS5B) and quantifying the features by building an atom based 3D quantitative structure-activity relationship (3D QSAR) model.Methods: Generation of QSAR model was carried out using PHASE 3.3.Results: A five-point pharmacophore model with two hydrogen bond acceptors, one negative ionization potential and two aromatic rings (AANRR) was found to be common among a maximum number of benzothiadiazine based NS5B inhibitors. A statistically significant 3D QSAR model was obtained from AANRR.6 which had correlation-coefficient (R2) value of 0.924, cross-validated correlation-coefficient (Q2) of 0.774, high Fisher ratio of 138 and low root mean square standard error (RMSE=0.29). There is another parameter, Pearson’s R, its value emphasizes correlation between predicted and observed activities of the test set. For the current model, Pearson’s R-value is 0.90, hence underlining the good quality of the model. The present study suggests that nitrogen atom of benzothiadiazine sulfamide ring, oxyacetamide group attached to C7 carbon of benzothiadiazine and sulfonamide oxygens are crucial for NS5B inhibitory activity. Prediction of activities of hit drugs generated in earlier research suggests that Aprepitant (Phase predicted activity: 6.9) could be a potential NS5B inhibitor.Conclusion: This 3D QSAR model developed was statistically good and can be used to predict the activities of newly designed NS5B inhibitors and virtual screening as well. Predict the activities of newly designed NS5B inhibitors and virtual screening as well.

scholarly journals Combined Pharmacophore Modeling, 3D-QSAR, Homology Modeling and Docking Studies on CYP11B1 Inhibitors

Molecules ◽  
2015 ◽  
Vol 20 (1) ◽  
pp. 1014-1030 ◽  
Author(s):  
Rui Yu ◽  
Juan Wang ◽  
Rui Wang ◽  
Yong Lin ◽  
Yong Hu ◽  
...  
Keyword(s):  
Homology Modeling ◽  
3D Qsar ◽  
Pharmacophore Modeling ◽  
Docking Studies

Identification of new checkpoint kinase-1 (Chk1) inhibitors by docking, 3D-QSAR, and pharmacophore-modeling methods

2012 ◽  
Vol 90 (8) ◽  
pp. 675-692 ◽  
Author(s):  
Premlata K. Ambre ◽  
Raghuvir R. S. Pissurlenkar ◽  
Evans C. Coutinho ◽  
Radhakrishnan P. Iyer
Keyword(s):  
Hydrogen Bond ◽  
3D Qsar ◽  
Pharmacophore Modeling ◽  
Docking Studies ◽  
Hydrogen Bond Donor ◽  
Hydrogen Bond Acceptor ◽  
Checkpoint Kinase ◽  
Checkpoint Kinase 1 ◽  
Qsar Models ◽  
Potential Inhibitors

Inhibition of checkpoint kinase-1 (Chk1) by small molecules is of great therapeutic interest in the field of oncology and for understanding cell-cycle regulations. This paper presents a model with elements from docking, pharmacophore mapping, the 3D-QSAR approaches CoMFA, CoMSIA and CoRIA, and virtual screening to identify novel hits against Chk1. Docking, 3D-QSAR (CoRIA, CoMFA and CoMSIA), and pharmacophore studies delineate crucial site points on the Chk1 inhibitors, which can be modified to improve activity. The docking analysis showed residues in the proximity of the ligands that are involved in ligand–receptor interactions, whereas CoRIA models were able to derive the magnitude of these interactions that impact the activity. The ligand-based 3D-QSAR methods (CoMFA and CoMSIA) highlight key areas on the molecules that are beneficial and (or) detrimental for activity. The docking studies and 3D-QSAR models are in excellent agreement in terms of binding-site interactions. The pharmacophore hypotheses validated using sensitivity, selectivity, and specificity parameters is a four-point model, characterized by a hydrogen-bond acceptor (A), hydrogen-bond donor (D), and two hydrophobes (H). This map was used to screen a database of 2.7 million druglike compounds, which were pruned to a small set of potential inhibitors by CoRIA, CoMFA, and CoMSIA models with predicted activity in the range of 8.5–10.5 log units.

scholarly journals The Integration of Pharmacophore-Based 3D QSAR Modeling and Virtual Screening in Identification of Natural Product Inhibitors against SARS-CoV-2

2020 ◽  
Author(s):  
Samira Norouzi ◽  
Maryam Farahani ◽  
Samad Nejad Ebrahimi
Keyword(s):  
Virtual Screening ◽  
3D Structure ◽  
3D Qsar ◽  
Qsar Model ◽  
Docking Studies ◽  
Molecular Characteristics ◽  
Qsar Modeling ◽  
Data Set ◽  
Public Health Emergencies ◽  
Current Outbreak

Background: The current outbreak of Coronavirus Disease 2019 (SARS-CoV-2) led to public health emergencies all over the world and made it a global concern. Also, the lack of an effective treatment to combat this virus is another concern that has appeared. Today, increasing knowledge of biological structures like increasing computer power brings about a chance to use computational methods efficiently in different phases of the drug discovery and development for helping solve this new global problem. Methods: In this study, 3D pharmacophores were generated based on thirty-one structures with functional affinity inhibition (antiviral drugs used for SARS and MERS) with IC50<250 µM from the literature data. A 3D-QSAR model has been developed and validated to be utilized in virtual screening. Results: The best pharmacophore models have been utilized as 3D queries for virtual screening to gain promising inhibitors from a data set of thousands of natural compounds retrieved from PubChem. The hit compounds were subsequently used for molecular docking studies to investigate their affinity to the 3D structure of the SARS-CoV-2 receptors. The ADMET properties calculate for the hits with high binding affinity. Conclusion: The study outcomes can help understand the molecular characteristics and mechanisms of the binding of hit compounds to SARS-CoV-2 receptors and promising identification inhibitors that are likely to be evolved into drugs.

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