Development of 3D-pharmacophore model followed by successive virtual screening, molecular docking and ADME studies for the design of potent CCR2 antagonists for inflammation-driven diseases

2013 ◽  
Vol 39 (1) ◽  
pp. 49-58 ◽  
Author(s):  
Rajesh Singh ◽  
Anand Balupuri ◽  
M. Elizabeth Sobhia
Keyword(s):  
Molecular Docking ◽  
Virtual Screening ◽  
Pharmacophore Model ◽  
3D Pharmacophore

Ligand-based 3D pharmacophore design, virtual screening and molecular docking for novel p38 MAPK inhibitors

2014 ◽  
Vol 24 (2) ◽  
pp. 797-809 ◽  
Author(s):  
Lijuan He ◽  
Ru Dai ◽  
Xuan R. Zhang ◽  
Si Y. Gao ◽  
Yan Y. He ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Virtual Screening ◽  
P38 Mapk ◽  
3D Pharmacophore ◽  
P38 Mapk Inhibitors ◽  
Mapk Inhibitors

scholarly journals Structure based pharmacophore modeling, virtual screening, molecular docking and ADMET approaches for identification of natural anti-cancer agents targeting XIAP protein

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Firoz A. Dain Md Opo ◽  
Mohammed M. Rahman ◽  
Foysal Ahammad ◽  
Istiak Ahmed ◽  
Mohiuddin Ahmed Bhuiyan ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Virtual Screening ◽  
Md Simulation ◽  
Pharmacophore Model ◽  
Pharmacophore Modeling ◽  
Drug Candidate ◽  
Inhibitor Of Apoptosis ◽  
Inhibitor Of Apoptosis Protein ◽  
Apoptosis Protein ◽  
Apoptosis Process

AbstractX-linked inhibitor of apoptosis protein (XIAP) is a member of inhibitor of apoptosis protein (IAP) family responsible for neutralizing the caspases-3, caspases-7, and caspases-9. Overexpression of the protein decreased the apoptosis process in the cell and resulting development of cancer. Different types of XIAP antagonists are generally used to repair the defective apoptosis process that can eliminate carcinoma from living bodies. The chemically synthesis compounds discovered till now as XIAP inhibitors exhibiting side effects, which is making difficulties during the treatment of chemotherapy. So, the study has design to identifying new natural compounds that are able to induce apoptosis by freeing up caspases and will be low toxic. To identify natural compound, a structure-based pharmacophore model to the protein active site cavity was generated following by virtual screening, molecular docking and molecular dynamics (MD) simulation. Initially, seven hit compounds were retrieved and based on molecular docking approach four compounds has chosen for further evaluation. To confirm stability of the selected drug candidate to the target protein the MD simulation approach were employed, which confirmed stability of the three compounds. Based on the finding, three newly obtained compounds namely Caucasicoside A (ZINC77257307), Polygalaxanthone III (ZINC247950187), and MCULE-9896837409 (ZINC107434573) may serve as lead compounds to fight against the treatment of XIAP related cancer, although further evaluation through wet lab is necessary to measure the efficacy of the compounds.

scholarly journals Ligand Based 3D-QSAR Pharmacophore, Molecular Docking and Adme to Identify Potential Fibroblast Growth Factor Receptor 1 Inhibitors 

2020 ◽  
Author(s):  
Zizhong Tang ◽  
Lu Huang ◽  
Xiaoli Fu ◽  
Haoxiang Wang ◽  
Biao Tang ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Virtual Screening ◽  
Growth Factor Receptor ◽  
Pharmacophore Model ◽  
3D Qsar ◽  
Drug Carriers ◽  
Therapeutic Effects ◽  
Lipinski’S Rule ◽  
Discovery Studio ◽  
Zinc Database

Abstract The FGF/FGFR system may affect tumor cells and stromal microenvironment through autocrine and paracrine stimulation, thereby significantly promoting oncogene transformation and tumor growth. Abnormal expression of FGFR1 in cells is considered to be the main cause of tumorigenesis and a potential target for the treatment of cancer. In this study, a combination of structure-based drug carriers and molecular docking-based virtual screening was used to screen new potential FGFR1 inhibitors. Twenty-one known inhibitors were collected as training sets to establish a 3D-QSAR pharmacophore model, and cost analysis, test set validation, and Fischer randomization test were used to validate the efficiency of the pharmacophore model. In Accelrys Discovery Studio 2016, the zinc database was filtered by Lipinski's Rule of Five and SMART's filtration. Then, Hypo01 was used for virtual screening of ZINC database. Compounds with predicted activity values less than 1 μM were molecularly docked with FGFR1 protein crystals, the docking results were observed, and the interaction between compounds and targets was studied. The absorption, distribution, metabolism and excretion (ADME) and toxicity of potential inhibitors were studied, and a compound with new structural scaffolds were obtained. It could be further studied to explore their better therapeutic effects.

scholarly journals A Search for Cyclin-Dependent Kinase 4/6 Inhibitors by Pharmacophore-Based Virtual Screening, Molecular Docking, and Molecular Dynamic Simulations

2021 ◽  
Vol 22 (24) ◽  
pp. 13423
Author(s):  
Ni Made Pitri Susanti ◽  
Sophi Damayanti ◽  
Rahmana Emran Kartasasmita ◽  
Daryono Hadi Tjahjono
Keyword(s):  
Cell Cycle ◽  
Molecular Docking ◽  
Virtual Screening ◽  
Cell Cycle Progression ◽  
Cell Cycle Control ◽  
Pharmacophore Model ◽  
Progression Free Survival ◽  
Cyclin Dependent Kinase ◽  
Dynamic Simulations ◽  
Reference Drug

The G1 phase of cell cycle progression is regulated by Cyclin-Dependent Kinase 4 (CDK4) as well as Cyclin-Dependent Kinase 6 (CDK6), and the acivities of these enzymes are regulated by the catalytic subunit, cyclin D. Cell cycle control through selective pharmacological inhibition of CDK4/6 has proven to be beneficial in the treatment of estrogen receptor-positive (ER-positive) breast cancer, particularly improving the progression-free survival of patients. Thus, targeting specific inhibition on CDK4/6 is bound to increase therapeutic efficiency. This study aimed to obtain CDK4/6 inhibitors through a pharmacophore-based virtual screening of the ZINC15 purchasable compound database using the in silico method. The pharmacophore model was designed based on the FDA-approved cdk4/6 inhibitor structures, and molecular docking was performed to further screen the hit compounds obtained. A total of eight compounds were selected based on docking results and interactions with CDK4 and CDK6, using palbociclib as the reference drug. According to the results, the compounds of ZINC585292724 and ZINC585291674 were the best compounds based on free binding energy, as well as hydrogen bond stability, and, therefore, exhibit potential as starting points in the development of CDK4/6 inhibitors.

scholarly journals Structural Insight into PRMT5 Inhibitors through Amalgamating Pharmacophore-Based Virtual Screening, ADME-Toxicity and Binding Energy Studies and Identify New Inhibitors by Molecular Docking.

2021 ◽  
Author(s):  
Revanth Bathula ◽  
Sree kanth Sivan ◽  
Gururaj Somadi ◽  
Narasimha Muddagoni ◽  
Goverdhan Lanka ◽  
...  
Keyword(s):  
Free Energy ◽  
Molecular Docking ◽  
Virtual Screening ◽  
Binding Free Energy ◽  
Protein A ◽  
Pharmacophore Model ◽  
Receptor Site ◽  
3D Qsar ◽  
Qsar Modeling ◽  
Energy Prediction

Abstract Protein arginine methyltransferase 5 (PRMT5) is a member of the methyltransferases family, a type II arginine enzyme that is crucial for many cellular processes and is associated with many cancer diseases. In this study, pharmacophore-based 3D QSAR modeling, virtual screening and binding free energy studies were carried out from a set of 61 potent compounds reported being inhibitors of PRMT5 protein. A five-point pharmacophore model (AADHR) was generated and this model is used to generate an atom-based 3-Dimensional quantitative structure-activity relationship (3D-QSAR). The obtained 3D-QSAR model has high correlation coefficient (R2 = 0.91), cross-validation coefficient (Q2 = 0.82), F value (140.3), low RMSE (0.47) and pearson R-value (0.91). A library of 329825 molecules (ChEMBL database) is screened with pharmacophore model to retrieve hit molecules that are further subjected for molecular docking to identify best fit-active conformations binding at the receptor site of PRMT5 protein. Further, we are calculated ADME and toxicity properties using QikProp module and pkCSM server and finally prioritized the lead molecules by binding free energy prediction.

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