Rational questing for inhibitors of endothelin converting enzyme-1 from Salvia miltiorrhiza by combining ligand- and structure-based virtual screening

2013 ◽  
Vol 91 (6) ◽  
pp. 448-456 ◽  
Author(s):  
Xing Wang ◽  
Yuhong Xiang ◽  
Zhenzhen Ren ◽  
Yanling Zhang ◽  
Yanjiang Qiao
Keyword(s):  
Molecular Docking ◽  
Virtual Screening ◽  
Salvia Miltiorrhiza ◽  
Scoring Function ◽  
Pharmacophore Model ◽  
Target Protein ◽  
Binding Modes ◽  
Converting Enzyme ◽  
Endothelin Converting Enzyme ◽  
Pharmacophore Models

In this study, a virtual screening approach based on pharmacophore and molecular docking was proposed to identify endothelin converting enzyme-1 (ECE-1) (EC 3.4.24.71) inhibitors from Salvia miltiorrhiza. First, the pharmacophore models were generated to recognize the common features of the ECE-1 inhibitors. The models were validated by a test database composed by a set of compounds known as ECE-1 inhibitors and nonactive compounds and proven to be successful in discriminating active and inactive inhibitors. Then, the best pharmacophore model was used to screen the compounds from S. miltiorrhiza. Furthermore, the Surflex-Dock procedure was used for molecular docking. All compounds from S. miltiorrhiza were docked into the active site of the target protein. An empirical scoring function was used to evaluate the affinity of the compounds and the target protein. Comparing the virtual screening results based on pharmacophore and molecular docking, respectively, 11 communal compounds with higher QFIT and docking score were hit, and the activity of some compounds was validated in the literature. The binding modes between these compounds and the ECE-1 binding site were predicted and used to identify the key interactions that contribute to the inhibitory activity of ECE-1 activity. The results show that the two methods have good consistency and can be validated and supplemented with each other.

scholarly journals Discovery of Novel DPP-IV Inhibitors as Potential Candidates for the Treatment of Type 2 Diabetes mellitus Predicted by 3D QSAR Pharmacophore Models, Molecular Docking and de novo Evolution

Molecules ◽  
2019 ◽  
Vol 24 (16) ◽  
pp. 2870 ◽  
Author(s):  
Musoev ◽  
Numonov ◽  
You ◽  
Gao
Keyword(s):  
Molecular Docking ◽  
Amino Acid ◽  
Virtual Screening ◽  
De Novo ◽  
Pharmacophore Model ◽  
3D Qsar ◽  
Amino Acid Residues ◽  
Training Set ◽  
Dpp Iv ◽  
Pharmacophore Models

Dipeptidyl peptidase-IV (DPP-IV) rapidly breaks down the incretin hormones glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic peptide (GIP). Thus, the use of DPP-IV inhibitors to retard the degradation of endogenous GLP-1 is a possible mode of therapy correcting the defect in incretin-related physiology. The aim of this study is to find a new small molecule and explore the inhibition activity to the DPP-IV enzyme using a computer aided simulation. In this study, the predicted compounds were suggested as potent anti-diabetic candidates. Chosen structures were applied following computational strategies: The generation of the three-dimensional quantitative structure-activity relationship (3D QSAR) pharmacophore models, virtual screening, molecular docking, and de novo Evolution. The method also validated by performing re-docking and cross-docking studies of seven protein systems for which crystal structures were available for all bound ligands. The molecular docking experiments of predicted compounds within the binding pocket of DPP-IV were conducted. By using 25 training set inhibitors, ten pharmacophore models were generated, among which hypo1 was the best pharmacophore model with the best predictive power on account of the highest cost difference (352.03), the lowest root mean squared deviation (RMSD) (2.234), and the best correlation coefficient (0.925). Hypo1 pharmacophore model was used for virtual screening. A total of 161 compounds including 120 from the databases, 25 from the training set, 16 from the test set were selected for molecular docking. Analyzing the amino acid residues of the ligand-receptor interaction, it can be concluded that Arg125, Glu205, Glu206, Tyr547, Tyr662, and Tyr666 are the main amino acid residues. The last step in this study was de novo Evolution that generated 11 novel compounds. The derivative dpp4_45_Evo_1 by all scores CDOCKER_ENERGY (CDOCKER, -41.79), LigScore1 (LScore1, 5.86), LigScore2 (LScore2, 7.07), PLP1 (-112.01), PLP2 (-105.77), PMF (-162.5)—have exceeded the control compound. Thus the most active compound among 11 derivative compounds is dpp4_45_Evo_1. Additionally, for derivatives dpp4_42_Evo_1, dpp4_43_Evo2, dpp4_46_Evo_4, and dpp4_47_Evo_2, significant upward shifts were recorded. The consensus score for the derivatives of dpp4_45_Evo_1 from 1 to 6, dpp4_43_Evo2 from 4 to 6, dpp4_46_Evo_4 from 1 to 6, and dpp4_47_Evo_2 from 0 to 6 were increased. Generally, predicted candidates can act as potent occurring DPP-IV inhibitors given their ability to bind directly to the active sites of DPP-IV. Our result described that the 6 re-docked and 27 cross-docked protein-ligand complexes showed RMSD values of less than 2 Å. Further investigation will result in the development of novel and potential antidiabetic drugs.

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 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 Discovery of CNS-Like D3R-Selective Antagonists Using 3D Pharmacophore Guided Virtual Screening

Molecules ◽  
2018 ◽  
Vol 23 (10) ◽  
pp. 2452 ◽  
Author(s):  
June Lee ◽  
Sung Cho ◽  
Mi-hyun Kim
Keyword(s):  
Virtual Screening ◽  
Neurological Diseases ◽  
Scoring Function ◽  
Quantitative Structure Activity Relationship ◽  
Coefficient Of Determination ◽  
Dopamine D3 Receptor ◽  
D3 Receptor ◽  
Speed Increase ◽  
Dopamine D3 ◽  
Pharmacophore Models

The dopamine D3 receptor is an important CNS target for the treatment of a variety of neurological diseases. Selective dopamine D3 receptor antagonists modulate the improvement of psychostimulant addiction and relapse. In this study, five and six featured pharmacophore models of D3R antagonists were generated and evaluated with the post-hoc score combining two survival scores of active and inactive. Among the Top 10 models, APRRR215 and AHPRRR104 were chosen based on the coefficient of determination (APRRR215: R2training = 0.80; AHPRRR104: R2training = 0.82) and predictability (APRRR215: Q2test = 0.73, R2predictive = 0.82; AHPRRR104: Q2test = 0.86, R2predictive = 0.74) of their 3D-quantitative structure–activity relationship models. Pharmacophore-based virtual screening of a large compound library from eMolecules (>3 million compounds) using two optimal models expedited the search process by a 100-fold speed increase compared to the docking-based screening (HTVS scoring function in Glide) and identified a series of hit compounds having promising novel scaffolds. After the screening, docking scores, as an adjuvant predictor, were added to two fitness scores (from the pharmacophore models) and predicted Ki (from PLSs of the QSAR models) to improve accuracy. Final selection of the most promising hit compounds were also evaluated for CNS-like properties as well as expected D3R antagonism.

DRUG TARGET PRIORITIZATION IN PLASMODIUM FALCIPARUM THROUGH METABOLIC NETWORK ANALYSIS, AND INHIBITOR DESIGNING USING VIRTUAL SCREENING AND DOCKING APPROACH

2013 ◽  
Vol 11 (04) ◽  
pp. 1350003 ◽  
Author(s):  
MANOJ KUMAR YADAV ◽  
SAURABH KUMAR PANDEY ◽  
D. SWATI
Keyword(s):  
Plasmodium Falciparum ◽  
Network Analysis ◽  
Virtual Screening ◽  
Metabolic Network ◽  
Pharmacophore Model ◽  
Binding Pocket ◽  
Binding Modes ◽  
Metabolic Network Analysis ◽  
Screening Experiments ◽  
Monophosphate Decarboxylase

The genome sequence of Plasmodium falciparum reveals that many metabolic pathways are unique as compared to its human host. Metabolic Network Analysis was carried out to find the essential enzymes critical for the survival of the pathogen. In the present study, choke point and load point analysis was used to locate putative targets. The identified targets were further checked to confirm that no alternate pathway or human homolog exists. Among the top 15 enzymes obtained from this analysis, we have selected P. falciparum orotidine-5'-monophosphate decarboxylase (PfODCase) enzyme as it is sequentially and structurally different from that of humans, for searching novel inhibitors. A five-point 3D pharmacophore was generated for the crystal structure of PfODCase complexes with uridine-5'-monophosphate (U5P). The binding site environment shows three H-bond acceptors, one H-bond donor and one negative ionizable feature. This pharmacophore model was used as a 3D query to perform virtual screening experiments against 2,664,779 standard lead compounds obtained from the freely available ZINC database. Top 10 hits obtained from virtual screening were selected for molecular docking experiments against PfODCase in order to verify their results and to have a better insight into their binding modes. Here, docking of U5P with PfODCase is used as a control. We have identified six compounds, among them, few are U5P analogs and others are novel ones with diverse scaffolds. The key residues: Lys42, Asp20, Lys72, Ser127, Ala184, Gln185 and Arg203 at the main binding pocket of PfODCase are responsible for better stability of diverse ligands. These compounds according to their free energy of binding could serve as potent leads for designing novel inhibitors against malarial ODCase enzyme.

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 Virtual Screening Peptida Bioaktif Antihipertensi dari Hidrolisat Kasein Susu Kambing Etawa

ALCHEMY ◽  
2016 ◽  
Vol 5 (2) ◽  
pp. 45
Author(s):  
Sandra Hermanto
Keyword(s):  
Molecular Docking ◽  
Virtual Screening ◽  
Angiotensin Converting Enzyme ◽  
Protease Inhibitor ◽  
In Silico ◽  
Reference Sequence ◽  
Capra Hircus ◽  
Converting Enzyme

Penapisan peptida bioaktif dari hidrolisat kasein susu kambing Etawa yang berpotensi sebagai obat antihipertensi berdasarkan kajian <em>in silico </em>telah dilakukan. Protein yang digunakan adalah α-S1-kasein prekursor [<em>Capra hircus</em>] NCBI <em>Reference Sequence</em>: NP_001272624.1, α-S2-kasein prekursor [<em>C. hircus</em>] NCBI <em>Reference Sequence</em>: NP_001272514.1, β-kasein [<em>C. hircus</em>] NCBI <em>Reference Sequence</em>: AAA30906.1 dan κ-kasein prekursor [<em>C. hircus</em>] NCBI <em>Reference Sequence</em>: NP_001272516.1. Perancangan struktur peptida bioaktif dilakukan melalui simulasi hidrolisis enzimatik dengan menggunakan 3 jenis enzim proteolitik (tripsin, kimotripsin dan pepsin) dan dilanjutkan dengan preparasi struktur 3D ligan hasil pemotongan secara <em>in silico</em>. <em>Virtual screening</em> terhadap fragmen peptida dilakukan melalui penentuan nilai <em>drug likeness</em> dan <em>protease inhibitor.</em> Dari 104 fragmen peptida diperoleh 10 kandidat peptida bioaktif yang dilakukan simulasi <em>molecular docking</em> dengan mengeksplorasi daya inhibisi fragmen melalui perhitungan nilai (∆<em>G<sub>binding</sub></em>) dan interaksi antara kandidat peptida bioaktif dengan residu asam amino pada sisi aktif enzim ACE (<em>Angiotensin Converting Enzyme)</em>. Sebagai kontrol positif digunakan lisinopril yang merupakan inhibitor ACE komersil. Hasil penelitian menunjukkan dari 10 kandidat peptida bioaktif terdapat 6 peptida yang diduga bersifat antihipertensi dengan nilai ∆<em>G<sub>binding</sub></em><em></em><sub> </sub>yang lebih rendah dari kontrol positif (lisinopril). Keenam peptida tersebut diharapkan dapat berfungsi sebagai obat alternatif antihipertensi.

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 Virtual Screening in Search for a Chemical Probe for Angiotensin-Converting Enzyme 2 (ACE2)

Molecules ◽  
2021 ◽  
Vol 26 (24) ◽  
pp. 7584
Author(s):  
Iryna O. Kravets ◽  
Dmytro V. Dudenko ◽  
Alexander E. Pashenko ◽  
Tatiana A. Borisova ◽  
Ganna M. Tolstanova ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Virtual Screening ◽  
Angiotensin Converting Enzyme ◽  
Cost Effective ◽  
Converting Enzyme ◽  
Chemical Probes ◽  
Angiotensin Converting Enzyme 2 ◽  
Cpu Time ◽  
New Models ◽  
The Cost

We elaborate new models for ACE and ACE2 receptors with an excellent prediction power compared to previous models. We propose promising workflows for working with huge compound collections, thereby enabling us to discover optimized protocols for virtual screening management. The efficacy of elaborated roadmaps is demonstrated through the cost-effective molecular docking of 1.4 billion compounds. Savings of up to 10-fold in CPU time are demonstrated. These developments allowed us to evaluate ACE2/ACE selectivity in silico, which is a crucial checkpoint for developing chemical probes for ACE2.

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