Hierarchical virtual screening of the dual MMP-2/HDAC-6 inhibitors from natural products based on pharmacophore models and molecular docking

Dengue is one of the crucial diseases in human-caused by dengue virus (DENV) infection. However, the development of DENV antiviral is often facing a problem because no effective drug to treat infection caused by all DENV serotypes. The inhibition of host protein involved in DENV life cycle can be a potential approach in dengue drug discovery, and also avoiding antiviral resistance. Endoplasmic Reticulum (ER) α-glucosidase II is one of the target host protein in DENV endoplasmic reticulum that plays an important role in the maturation process of DENV envelope glycoprotein. Natural products have been known as an essential source of a lead compound for drug discovery due to their therapeutic potency. In this research, pharmacophore-based virtual screening and molecular docking simulations were performed to find ligand that has potential to inhibit α-glucosidase II activity. About 67,609 natural products from InterBioScreen (IBS) database were used in the simulation as ligands with α-glucosidase II as the protein target. After subjected to Lipinski’s Rule of Five, druglikeness, nasty functions, and toxicity screening using DataWarrior software, 17,462 ligands were obtained. The pharmacophore features for molecular docking simulation was obtained from Protein-Ligand Interaction Fingerprint (PLIF) analysis using eight α-glucosidase II protein with different ligands. Based on virtual screening, rigid, and flexible docking simulations using Molecular Operating Environment (MOE) software, 32 ligands have lower Gibbs free binding energy (ΔGbinding) compared to the standards. Two best ligands, namely STOCK1N-85545 and STOCK1N-86400 which belong alkaloid derivatives, showed the exceptional ligand interaction and had the lowest ΔGbinding of-11.204 and-10.276 kcal/mol, respectively. The ligands were identified to have a binding interaction with amino acid Asp564 and Asp640 in α-glucosidase II catalytic site. STOCK1N-85545 and STOCK1N-86400 were also identified to have a good pharmacological properties after subjected to ADME-tox test using Toxtree, SwissADME, admetSAR, and pkCSM software.

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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 ◽

10.3390/molecules24162870 ◽

2019 ◽

Vol 24 (16) ◽

pp. 2870 ◽

Cited By ~ 4

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.

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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

Indonesian Journal of Chemistry ◽

10.22146/ijc.54745 ◽

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.

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Computer-Assisted Discovery of Alkaloids with Schistosomicidal Activity

Current Issues in Molecular Biology ◽

10.3390/cimb44010028 ◽

2022 ◽

Vol 44 (1) ◽

pp. 383-408

Author(s):

Renata Priscila Barros de Menezes ◽

Jéssika de Oliveira Viana ◽

Eugene Muratov ◽

Luciana Scotti ◽

Marcus Tullius Scotti

Keyword(s):

Drug Resistance ◽

Natural Products ◽

Molecular Docking ◽

Virtual Screening ◽

Schistosoma Mansoni ◽

In Silico ◽

Cost Benefit ◽

Computer Assisted ◽

Parasitic Disease

Schistosomiasis is a chronic parasitic disease caused by trematodes of the genus Schistosoma; it is commonly caused by Schistosoma mansoni, which is transmitted by Bioamphalaria snails. Studies show that more than 200 million people are infected and that more than 90% of them live in Africa. Treatment with praziquantel has the best cost–benefit result on the market. However, hypersensitivity, allergy, and drug resistance are frequently presented after administration. From this perspective, ligand-based and structure-based virtual screening (VS) techniques were combined to select potentially active alkaloids against S. mansoni from an internal dataset (SistematX). A set of molecules with known activity against S. mansoni was selected from the ChEMBL database to create two different models with accuracy greater than 84%, enabling ligand-based VS of the alkaloid bank. Subsequently, structure-based VS was performed through molecular docking using four targets of the parasite. Finally, five consensus hits (i.e., five alkaloids with schistosomicidal potential), were selected. In addition, in silico evaluations of the metabolism, toxicity, and drug-like profile of these five selected alkaloids were carried out. Two of them, namely, 11,12-methylethylenedioxypropoxy and methyl-3-oxo-12-methoxy-n(1)-decarbomethoxy-14,15-didehydrochanofruticosinate, had plausible toxicity, metabolomics, and toxicity profiles. These two alkaloids could serve as starting points for the development of new schistosomicidal compounds based on natural products.

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

Canadian Journal of Chemistry ◽

10.1139/cjc-2012-0523 ◽

2013 ◽

Vol 91 (6) ◽

pp. 448-456 ◽

Cited By ~ 10

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.

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Combining Virtual Screening Protocol and In Vitro Evaluation towards the Discovery of BACE1 Inhibitors

Biomolecules ◽

10.3390/biom10040535 ◽

2020 ◽

Vol 10 (4) ◽

pp. 535

Author(s):

Judite R. M. Coimbra ◽

Salete J. Baptista ◽

Teresa C. P. Dinis ◽

Maria M. C. Silva ◽

Paula I. Moreira ◽

...

Keyword(s):

Molecular Docking ◽

Virtual Screening ◽

Treatment Options ◽

Amyloid Β ◽

Bioactive Molecules ◽

Screening Assay ◽

Screening Protocol ◽

Pharmacophore Models ◽

Early Drug

The treatment options for a patient diagnosed with Alzheimer’s disease (AD) are currently limited. The cerebral accumulation of amyloid-β (Aβ) is a critical molecular event in the pathogenesis of AD. When the amyloidogenic β-secretase (BACE1) is inhibited, the production of Aβ peptide is reduced. Henceforth, the main goal of this study is the discovery of new small bioactive molecules that potentially reach the brain and inhibit BACE1. The work was conducted by a customized molecular modelling protocol, including pharmacophore-based and molecular docking-based virtual screening (VS). Structure-based (SB) and ligand-based (LB) pharmacophore models were designed to accurately screen several drug-like compound databases. The retrieved hits were subjected to molecular docking and in silico filtered to predict their ability to cross the blood–brain barrier (BBB). Additionally, 34 high-scoring compounds structurally distinct from known BACE1 inhibitors were selected for in vitro screening assay, which resulted in 13 novel hit-compounds for this relevant therapeutic target. This study disclosed new BACE1 inhibitors, proving the utility of combining computational and in vitro approaches for effectively predicting anti-BACE1 agents in the early drug discovery process.

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Biomolecular and Molecular Docking: A Modern Tool in Drug Discovery and Virtual Screening of Natural Products

Applied Pharmaceutical Practice and Nutraceuticals ◽

10.1201/9781003054894-14 ◽

2021 ◽

pp. 209-223

Author(s):

Khemchand R. Surana ◽

Eknath D. Ahire ◽

Vijayraj N. Sonawane ◽

Swati G. Talele

Keyword(s):

Natural Products ◽

Molecular Docking ◽

Drug Discovery ◽

Virtual Screening ◽

Modern Tool

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Structure-Based Pharmacophore Modeling, Virtual Screening, Molecular Docking, ADMET, and Molecular Dynamics (MD) Simulation of Potential Inhibitors of PD-L1 from the Library of Marine Natural Products

Marine Drugs ◽

10.3390/md20010029 ◽

2021 ◽

Vol 20 (1) ◽

pp. 29

Author(s):

Lianxiang Luo ◽

Ai Zhong ◽

Qu Wang ◽

Tongyu Zheng

Keyword(s):

Molecular Dynamics ◽

Natural Products ◽

Molecular Docking ◽

Virtual Screening ◽

Marine Natural Products ◽

Md Simulation ◽

Pharmacophore Model ◽

Pharmacophore Modeling ◽

Dynamics Simulation ◽

Stable Conformation

Background: In the past decade, several antibodies directed against the PD-1/PD-L1 interaction have been approved. However, therapeutic antibodies also exhibit some shortcomings. Using small molecules to regulate the PD-1/PD-L1 pathway may be another way to mobilize the immune system to fight cancer. Method: 52,765 marine natural products were screened against PD-L1(PDBID: 6R3K). To identify natural compounds, a structure-based pharmacophore model was generated, following by virtual screening and molecular docking. Then, the absorption, distribution, metabolism, and excretion (ADME) test was carried out to select the most suitable compounds. Finally, molecular dynamics simulation was also performed to validate the binding property of the top compound. Results: Initially, 13 small marine molecules were screened based on the pharmacophore model. Then, two compounds were selected for further evaluation based on the molecular docking scores. After ADME and toxicity studies, molecule 51320 was selected for further verification. By molecular dynamics analysis, molecule 51320 maintains a stable conformation with the target protein, so it has the chance to become an inhibitor of PD-L1. Conclusions: Through structure-based pharmacophore modeling, virtual screening, molecular docking, ADMET approaches, and molecular dynamics (MD) simulation, the marine natural compound 51320 can be used as a small molecule inhibitor of PD-L1.

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Pharmacophore Modelling and Virtual Screening Studies for the Discovery of Potential Natural Products Based PDE1B Inhibitor Lead Compounds

Central Nervous System Agents in Medicinal Chemistry ◽

10.2174/1871524922666211231115638 ◽

2021 ◽

Vol 22 ◽

Author(s):

Teng Woei Shy ◽

Anand Gaurav

Keyword(s):

Natural Products ◽

Virtual Screening ◽

Natural Product ◽

Neuropsychiatric Disorders ◽

Major Health ◽

Pharmacophore Modelling ◽

Lead Compounds ◽

Medical Need ◽

Total Brain ◽

Pharmacophore Models

Aim: The aim of the present study was to apply pharmacophore based virtual screening to a natural product database to identify potential PDE1B inhibitor lead compounds for neurodegenerative and neuropsychiatric disorders. Background: Neurodegenerative and neuropsychiatric disorders are a major health burden globally. The existing therapies do not provide optimal relief and are associated with substantial adverse effects. This has resulted in a huge unmet medical need for newer and more effective therapies for these disorders. Phosphodiesterase (PDEs) enzymes have been identified as potential targets of drugs for neurodegenerative and neuropsychiatric disorders, and one of the subtypes, i.e., PDE1B, accounts for more than 90 % of total brain PDE activity associated with learning and memory process, making it an interesting drug target for the treatment of neurodegenerative disorders. Objectives: The present study has been conducted to identify potential PDE1B inhibitor lead compounds from the natural product database. Methods: Ligand-based pharmacophore models were generated and validated; they were then employed for virtual screening of Universal Natural Products Database (UNPD) followed by docking with PDE1B to identify the best hit compound. Results: Virtual screening led to the identification of 85 compounds which were then docked into the active site of PDE1B. Out of the 85 compounds, six showed a higher affinity for PDE1B than the standard PDE1B inhibitors. The top scoring compound was identified as Cedreprenone. Conclusion: Virtual screening of UNPD using Ligand based pharmacophore led to the identification of Cedreprenone, a potential new natural PDE1B inhibitor lead compound.

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Strategy of Virtual Screening Based Discovery of HSP90 C-terminal Inhibitors and Network Pharmacological Analysis

Current Pharmaceutical Biotechnology ◽

10.2174/1389201022666210910101419 ◽

2021 ◽

Vol 22 ◽

Author(s):

Lihong Li ◽

Man Yang ◽

Chenyao Li ◽

Hongyu Xue ◽

Meiyun Shi ◽

...

Keyword(s):

Molecular Dynamics ◽

Drug Resistance ◽

Natural Products ◽

Molecular Docking ◽

Virtual Screening ◽

Anticancer Agents ◽

Binding Modes ◽

Pharmacological Analysis ◽

C Terminus ◽

Anticancer Target

Background: HSP90 has been considered as an important anticancer target for several decades, but traditional HSP90 N-terminal inhibitors often suffered from organ toxicity and/or drug resistance. Methods: The development of HSP90 C-terminal inhibitors represents a reliable alternative strategy. In the view of rare examples of structure based identification of HSP90 C-terminal inhibitors, we reported a virtual screening based strategy for the discovery of HSP90 C-terminal inhibitors as anticancer agents from natural products. Results & Discussion: 13 chemical ingredients from licorice were identified as possible HSP90 inhibitors and 3 of them have been reported as anticancer agents. The binding modes of them towards HSP90 C-terminus were predicted by molecular docking and refined by molecular dynamics stimulation. Conclusion: Further network pharmacological analysis predicted overall possible targets involved in the pathways in cancer and revealed that 8 molecules possibly interact with HSP90.

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