Molecular Docking Studies and Pharmacophore Modeling of Some Insulin Mimetic Agents from Herbal Sources: A Rational Approach towards Designing of Orally Active Insulin Mimetic Agents

2020 ◽  
Vol 6 (2) ◽  
pp. 121-133
Author(s):  
Joohee Pradhan ◽  
Sunita Panchawat
Keyword(s):  
Hydrogen Bond ◽  
Insulin Receptor ◽  
Pharmacophore Modeling ◽  
Rational Approach ◽  
Oral Insulin ◽  
Hydrogen Bond Acceptor ◽  
Insulin Receptor Tyrosine Kinase ◽  
Lipinski’S Rule ◽  
Insulin Mimetic ◽  
Orally Active

Background:: Many herbal drugs have been found to possess oral insulin mimetic property as evidenced from the literature. Although, to date there is no efficient, synthetic orally active insulin-mimetic drug available clinically. Computer-Aided Drug Design (CADD) may help in the development of such agents through Pharmacophore modeling. Objective:: The present work is aimed at the In-silico designing of Pharmacophore that defines the structural requirements of a molecule to possess oral insulin-mimetic properties. Methods:: A set of 16 orally active insulin-mimetic natural compounds available through literature was used to develop a structure-based pharmacophore in a “three-step filtration process” comprised of Lipinski’s rule of 5, Minimum binding energy with the receptor and Ghose filter to the Lipinski’s rule for oral bioavailability of the drugs. The selected ligands were docked with phosphorylated insulin receptor tyrosine kinase in complex with peptide substrate and ATP analog (PDB ID: 1IR3) using Autodock 4.2 and their interaction with the receptor was analyzed followed by the generation of shared and merged feature pharmacophore by Ligandscout 4.2.1. Results:: There are three important structural features that contribute to interaction with the active site of the insulin receptor: these are hydrogen bond donor groups, hydrogen bond acceptor groups and hydrophobic interactions. It is important to note that positive or negative ionizable groups or the presence of aromatic rings are not important for the activity. Conclusion:: Taking a clue from the developed pharmacophore, one may design new lead having necessary groups required for the insulin-mimetic activity that can be elaborated synthetically to get a series of compounds with possible oral insulin-mimetic activity.

scholarly journals Ligand Based Pharmacophore Modeling and Virtual Screening Studies to Design Novel HDAC2 Inhibitors

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Naresh Kandakatla ◽  
Geetha Ramakrishnan
Keyword(s):  
Virtual Screening ◽  
Histone Deacetylases ◽  
Pharmacophore Model ◽  
3D Qsar ◽  
Pharmacophore Modeling ◽  
Hydrogen Bond Acceptor ◽  
Lipinski’S Rule ◽  
Discovery Studio ◽  
Pharmacophore Generation ◽  
Important Therapeutic Target

Histone deacetylases 2 (HDAC2), Class I histone deacetylase (HDAC) family, emerged as an important therapeutic target for the treatment of various cancers. A total of 48 inhibitors of two different chemotypes were used to generate pharmacophore model using 3D QSAR pharmacophore generation (HypoGen algorithm) module in Discovery Studio. The best HypoGen model consists of four pharmacophore features namely, one hydrogen bond acceptor (HBA), and one hydrogen donor (HBD), one hydrophobic (HYP) and one aromatic centres, (RA). This model was validated against 20 test set compounds and this model was utilized as a 3D query for virtual screening to validate against NCI and Maybridge database and the hits further screened by Lipinski’s rule of 5, and a total of 382 hit compounds from NCI and 243 hit compounds from Maybridge were found and were subjected to molecular docking in the active site of HDAC2 (PDB: 3MAX). Finally eight hit compounds, NSC108392, NSC127064, NSC110782, and NSC748337 from NCI database and MFCD01935795, MFCD00830779, MFCD00661790, and MFCD00124221 from Maybridge database, were considered as novel potential HDAC2 inhibitors.

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 Anti-(insulin receptor) monoclonal antibody-stimulated tyrosine phosphorylation in cells transfected with human insulin receptor cDNA

1990 ◽  
Vol 268 (3) ◽  
pp. 615-620 ◽  
Author(s):  
N P J Brindle ◽  
J M Tavare ◽  
M Dickens ◽  
J Whittaker ◽  
K Siddle
Keyword(s):  
Insulin Receptor ◽  
Tyrosine Phosphorylation ◽  
Human Insulin ◽  
Maximum Level ◽  
Absolute Level ◽  
Insulin Receptor Tyrosine Kinase ◽  
Insulin Mimetic ◽  
Human Insulin Receptor ◽  
Receptor Cdna ◽  
Receptor Antibodies

The effects of insulin and anti-(insulin receptor) monoclonal antibodies on tyrosine phosphorylation were investigated in fibroblasts transfected with human insulin receptor cDNA (NIH 3T3HIR3.5 cells) using anti-phosphotyrosine immunoblotting. Insulin increased levels of tyrosine phosphorylation in two major proteins of molecular mass 97 kDa (pp97, assumed to be the insulin receptor beta-subunit) and 185 kDa (pp185). Insulin-mimetic anti-receptor antibodies also stimulated tyrosine phosphorylation of both pp97 and pp185. The observation of antibody-stimulated pp97 phosphorylation, as detected by immunoblotting, is in contrast with previous data which failed to show receptor autophosphorylation in NIH 3T3HIR3.5 cells labelled with [32P]P1. The effect of insulin on pp97 was maximal within 1 min, but the response to antibody was apparent only after a lag of 1-2 min and rose steadily over 20 min. The absolute level of antibody-stimulated phosphorylation of both pp97 and pp185 after 20 min was only about 20% of the maximum level induced by equivalent concentrations of insulin, even at concentrations of antibody sufficient for full occupancy of receptors. Another insulin-mimetic agent, wheat-germ agglutinin, stimulated receptor autophosphorylation with kinetics similar to those produced by the antibody. It is suggested that the relatively slow responses to both agents may be a function of the dependence on receptor cross-linking. These data are consistent with a role for the insulin receptor tyrosine kinase activity in the mechanism of action of insulin-mimetic anti-receptor antibodies.

scholarly journals Ligand Based Pharmacophore Modeling, Virtual Screening, and Molecular Docking Studies of Asymmetrical Hexahydro-2H-Indazole Analogs of Curcumin (AIACs) to Discover Novel Estrogen Receptors Alpha (ERα) Inhibitor

2020 ◽  
Vol 21 (1) ◽  
pp. 137
Author(s):  
Hariyanti Hariyanti ◽  
Kusmadi Kurmardi ◽  
Arry Yanuar ◽  
Hayun Hayun
Keyword(s):  
Molecular Docking ◽  
Virtual Screening ◽  
Estrogen Receptor Alpha ◽  
Pharmacophore Model ◽  
Pharmacophore Modeling ◽  
Cytotoxic Agents ◽  
Breast Development ◽  
Hydrogen Bond Acceptor ◽  
Lipinski’S Rule ◽  
Pharmacophore Models

The estrogen receptor alpha (ERα) plays an important role in breast development and pro-proliferation signal activation in the normal and cancerous breast. The ERα inhibitors were potentially active as cytotoxic agents against breast cancer. This study was conducted in order to find Asymmetrical Hexahydro-2H-Indazole Analogs of Curcumin (AIACs) as hits of ERα inhibitor. A training set of 17 selected ERα inhibitors was used to create 10 pharmacophore models using LigandScout 4.2. The pharmacophore models were validated using 383 active compounds as positive data and 20674 decoys as negative data obtained from DUD.E. Model 2 was found as the best pharmacophore model and consisted of three types of pharmacophore features, viz. one hydrophobic, one hydrogen bond acceptor, and aromatic interactions. Model 2 was utilized for ligand-based virtual screening 186 of AIACs, AMACs, intermediates, and Mannich base derivative compounds. The hits obtained were further screened using molecular docking, analyzed using drug scan, and tested for its synthesis accessibility. Fourteen compounds were fulfilled as hits in pharmacophore modeling, in which 10 hits were selected by molecular docking, but only seven hits met Lipinski’s rule of five and had medium synthesis accessibility. In conclusion, seven compounds were suggested to be potentially active as ERα inhibitors and deserve to be synthesized and further investigated.

scholarly journals Identification of 3-((1-(Benzyl(2-hydroxy-2-phenylethyl)amino)-1-oxo-3-phenylpropan-2-yl)carbamoyl)pyrazine-2-carboxylic Acid as a Potential Inhibitor of Non-Nucleosidase Reverse Transcriptase Inhibitors through In Silico Ligand- and Structure-Based Approaches

Molecules ◽  
2021 ◽  
Vol 26 (17) ◽  
pp. 5262
Author(s):  
Deepti Mathpal ◽  
Tahani M. Almeleebia ◽  
Kholoud M. Alshahrani ◽  
Mohammad Y. Alshahrani ◽  
Irfan Ahmad ◽  
...  
Keyword(s):  
Reverse Transcriptase ◽  
State Of The Art ◽  
Pharmacophore Model ◽  
Pharmacophore Modeling ◽  
Rational Approach ◽  
Binding Affinities ◽  
Reverse Transcriptase Inhibitors ◽  
Hydrogen Bond Acceptor ◽  
First Time ◽  
Screening Approaches

Non-nucleosidase reverse transcriptase inhibitors (NNRTIs) are highly promising agents for use in highly effective antiretroviral therapy. We implemented a rational approach for the identification of promising NNRTIs based on the validated ligand- and structure-based approaches. In view of our state-of-the-art techniques in drug design and discovery utilizing multiple modeling approaches, we report here, for the first time, quantitative pharmacophore modeling (HypoGen), docking, and in-house database screening approaches in the identification of potential NNRTIs. The validated pharmacophore model with three hydrophobic groups, one aromatic ring group, and a hydrogen-bond acceptor explains the interactions at the active site by the inhibitors. The model was implemented in pharmacophore-based virtual screening (in-house and commercially available databases) and molecular docking for prioritizing the potential compounds as NNRTI. The identified leads are in good corroboration with binding affinities and interactions as compared to standard ligands. The model can be utilized for designing and identifying the potential leads in the area of NNRTIs.

scholarly journals Prediction of Novel Anoctamin1 (ANO1) Inhibitors Using 3D-QSAR Pharmacophore Modeling and Molecular Docking

2018 ◽  
Vol 19 (10) ◽  
pp. 3204 ◽  
Author(s):  
Yoon Lee ◽  
Gwan-Su Yi
Keyword(s):  
Hydrogen Bond ◽  
Molecular Docking ◽  
Correlation Coefficient ◽  
High Throughput Screening ◽  
Interaction Analysis ◽  
Pharmacophore Model ◽  
3D Qsar ◽  
Pharmacophore Modeling ◽  
Hydrogen Bond Acceptor ◽  
Test Set

Recently, anoctamin1 (ANO1), a calcium-activated chloride channel, has been considered an important drug target, due to its involvement in various physiological functions, as well as its possibility for treatment of cancer, pain, diarrhea, hypertension, and asthma. Although several ANO1 inhibitors have been discovered by high-throughput screening, a discovery of new ANO1 inhibitors is still in the early phase, in terms of their potency and specificity. Moreover, there is no computational model to be able to identify a novel lead candidate of ANO1 inhibitor. Therefore, three-dimensional quantitative structure-activity relationship (3D-QSAR) pharmacophore modeling approach was employed for identifying the essential chemical features to be required in the inhibition of ANO1. The pharmacophore hypothesis 2 (Hypo2) was selected as the best model based on the highest correlation coefficient of prediction on the test set (0.909). Hypo2 comprised a hydrogen bond acceptor, a hydrogen bond donor, a hydrophobic, and a ring aromatic feature with good statistics of the total cost (73.604), the correlation coefficient of the training set (0.969), and the root-mean-square deviation (RMSD) value (0.946). Hypo2 was well assessed by the test set, Fischer randomization, and leave-one-out methods. Virtual screening of the ZINC database with Hypo2 retrieved the 580 drug-like candidates with good potency and ADMET properties. Finally, two compounds were selected as novel lead candidates of ANO1 inhibitor, based on the molecular docking score and the interaction analysis. In this study, the best pharmacophore model, Hypo2, with notable predictive ability was successfully generated, and two potential leads of ANO1 inhibitors were identified. We believe that these compounds and the 3D-QSAR pharmacophore model could contribute to discovering novel and potent ANO1 inhibitors in the future.

scholarly journals In Silico Study Probes Potential Inhibitors of Human Dihydrofolate Reductase for Cancer Therapeutics

2019 ◽  
Vol 8 (2) ◽  
pp. 233 ◽  
Author(s):  
Rabia Mukhtar Rana ◽  
Shailima Rampogu ◽  
Amir Zeb ◽  
Minky Son ◽  
Chanin Park ◽  
...  
Keyword(s):  
Hydrogen Bond ◽  
Root Mean Square ◽  
Dihydrofolate Reductase ◽  
Binding Free Energy ◽  
Pharmacophore Model ◽  
Cancer Therapeutics ◽  
Randomization Test ◽  
Pharmacophore Modeling ◽  
Mean Square ◽  
Hydrogen Bond Acceptor

Dihydrofolate reductase (DHFR) is an essential cellular enzyme and thereby catalyzes thereduction of dihydrofolate to tetrahydrofolate (THF). In cancer medication, inhibition of humanDHFR (hDHFR) remains a promising strategy, as it depletes THF and slows DNA synthesis and cellproliferation. In the current study, ligand-based pharmacophore modeling identified and evaluatedthe critical chemical features of hDHFR inhibitors. A pharmacophore model (Hypo1) was generatedfrom known inhibitors of DHFR with a correlation coefficient (0.94), root mean square (RMS)deviation (0.99), and total cost value (125.28). Hypo1 was comprised of four chemical features,including two hydrogen bond donors (HDB), one hydrogen bond acceptor (HBA), and onehydrophobic (HYP). Hypo1 was validated using Fischer's randomization, test set, and decoy setvalidations, employed as a 3D query in a virtual screening at Maybridge, Chembridge, Asinex,National Cancer Institute (NCI), and Zinc databases. Hypo1-retrieved compounds were filtered byan absorption, distribution, metabolism, excretion, and toxicity (ADMET) assessment test andLipinski's rule of five, where the drug-like hit compounds were identified. The hit compounds weredocked in the active site of hDHFR and compounds with Goldfitness score was greater than 44.67(docking score for the reference compound), clustering analysis, and hydrogen bond interactionswere identified. Furthermore, molecular dynamics (MD) simulation identified three compounds asthe best inhibitors of hDHFR with the lowest root mean square deviation (1.2 Å to 1.8 Å), hydrogenbond interactions with hDHFR, and low binding free energy (−127 kJ/mol to −178 kJ/mol). Finally,the toxicity prediction by computer (TOPKAT) affirmed the safety of the novel inhibitors of hDHFRin human body. Overall, we recommend novel hit compounds of hDHFR for cancer and rheumatoidarthritis chemotherapeutics.

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