scholarly journals In Silico Discovery of Potential Azole-Containing mPGES-1 Inhibitors By Virtual Screening, Pharmacophore Modeling and Molecular Dynamics Simulations

2022 ◽  
Author(s):  
Lalehan Özalp ◽  
İlkay Küçükgüzel ◽  
Ayşe Ogan
Keyword(s):  
Molecular Dynamics ◽  
Side Effects ◽  
Virtual Screening ◽  
Correlation Coefficients ◽  
Pharmacokinetic Profile ◽  
Pharmacophore Modeling ◽  
Dynamics Simulation ◽  
Prostaglandin E ◽  
Binding Modes ◽  
Design Strategies

Abstract Inhibition of microsomal prostaglandin E2 synthase-1 (mPGES-1) is promising for designing novel nonsteroidal anti-inflammatory drugs, as they lack side-effects associated with inhibition of cyclooxygenase enzymes. Azole compounds are nitrogen-containing heterocycles and have a wide use in medicine and are considered as promising compounds in medicinal chemistry. Various computer-aided drug design strategies are incorporated in this study. Structure-based virtual screening was performed employing various docking programs. Receiver Operator Characteristic (ROC) curves were used to evaluate the selectivity of each program. Furthermore, scoring power of Autodock4 and Autodock Vina was assessed by Pearson’s correlation coefficients. Pharmacophore models were generated and Güner-Henry score of the best model was calculated as 0.89. Binding modes of the final 10 azole compounds were analyzed and further investigation of the best binding (-8.38 kcal/mol) compound was performed using molecular dynamics simulation, revealing that furazan1224 (ZINC001142847306) occupied the binding site of the substrate, prostaglandin H2 (PGH2) and remained stable for 100 ns. Continuous hydrogen bonds with amino acids in the active site supported the stability of furazan1224 throughout the trajectory. Pharmacokinetic profile showed that furazan1224 lacks the risks of inhibiting cytochrome P450 3A4 enzyme and central nervous system-related side-effects.

scholarly journals 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 ◽  
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.

Exploring dual agonists for PPARα/γ receptors using pharmacophore modeling, docking analysis and molecule dynamics simulation

2021 ◽  
Vol 24 ◽  
Author(s):  
Ting-Ting Ding ◽  
Ya-Ya Liu ◽  
Li-Ming Zhang ◽  
Jia-Rui Shi ◽  
Wei-Ren Xu ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Virtual Screening ◽  
Structural Characteristics ◽  
Pharmacophore Modeling ◽  
Dynamics Simulation ◽  
Lipid Lowering ◽  
Acid Oxidation ◽  
Peroxisome Proliferator ◽  
Docking Analysis ◽  
Molecule Dynamics

Background: The peroxisome proliferator-activated receptors (PPARs) are ligand-activated transcription factors belonging to the nuclear receptor family. The roles of PPARα in fatty acid oxidation and PPARγ in adipocyte differentiation and lipid storage have been widely characterized. Compounds with dual PPARα/γ activity have been proposed, combining the benefits of insulin sensitization and lipid-lowering into one drug, allowing a single drug to reduce hyperglycemia and hyperlipidemia while preventing the development of cardiovascular complications. Methods: The new PPARα/γ agonists were screened through virtual screening of pharmacophores and molecular dynamics simulations. First, in the article, the constructed pharmacophore was used to screen the Ligand Expo Components-pub database to obtain the common structural characteristics of representative PPARα/γ agonist ligands. Then, the obtained ligand structure was modified and replaced to obtain 12 new compounds. Using molecular docking, ADMET and molecular dynamics simulation methods, the designed 12 ligands were screened, their docking scores were analyzed when they bound to the PPARα/γ dual targets, and also their stability and pharmacological properties were assessed when they were bound to the PPARα/γ dual targets. Results: We performed pharmacophore-based virtual screening for 22949 molecules in the Ligand Expo Components-pub database. Structural analysis and modification were performed on the compounds that were superior to the original ligand , and a series of compounds with novel structures were designed. Using precise docking, ADMET prediction and molecular dynamics methods, newly designed compounds were screened and verified, and the above compounds showed higher docking scores and lower side effects. Conclusion: 9 new PPARα/γ agonists were obtained by pharmacophore modeling, docking analysis and molecule dynamics simulation.

Identification of novel selective MMP-9 inhibitors as potential anti-metastatic lead using structure-based hierarchical virtual screening and molecular dynamics simulation

2016 ◽  
Vol 12 (8) ◽  
pp. 2519-2531 ◽  
Author(s):  
Sukesh Kalva ◽  
Nikhil Agrawal ◽  
Adam A. Skelton ◽  
Lilly M. Saleena
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Molecular Dynamics Simulation ◽  
Virtual Screening ◽  
Binding Free Energy ◽  
Pharmacophore Modeling ◽  
Dynamics Simulation ◽  
Simulation Studies ◽  
Cross Docking

In this study, a novel MMP-9 inhibitor was identified using structure-based pharmacophore modeling, cross docking, binding free energy and molecular dynamics simulation studies.

scholarly journals Virtual Screening and Molecular Dynamics Simulation Study of Influenza Polymerase PB2 Inhibitors

Molecules ◽  
2021 ◽  
Vol 26 (22) ◽  
pp. 6944
Author(s):  
Keli Zong ◽  
Lei Xu ◽  
Yuxin Hou ◽  
Qian Zhang ◽  
Jinjing Che ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Virtual Screening ◽  
Influenza A ◽  
Md Simulations ◽  
Biological Evaluation ◽  
Dynamics Simulation ◽  
Binding Modes ◽  
Active Compounds ◽  
Binding Characteristics ◽  
Glide Docking

Influenza A virus is the main cause of worldwide epidemics and annual influenza outbreaks in humans. In this study, a virtual screen was performed to identify compounds that interact with the PB2 cap-binding domain (CBD) of influenza A polymerase. A virtual screening workflow based on Glide docking was used to screen an internal database containing 8417 molecules, and then the output compounds were selected based on solubility, absorbance, and structural fingerprints. Of the 16 compounds selected for biological evaluation, six compounds were identified that rescued cells from H1N1 virus-mediated death at non-cytotoxic concentrations, with EC50 values ranging from 2.5–55.43 μM, and that could bind to the PB2 CBD of H1N1, with Kd values ranging from 0.081–1.53 μM. Molecular dynamics (MD) simulations of the docking complexes of our active compounds revealed that each compound had its own binding characteristics that differed from those of VX-787. Our active compounds have novel structures and unique binding modes with PB2 proteins, and are suitable to serve as lead compounds for the development of PB2 inhibitors. An analysis of the MD simulation also helped us to identify the dominant amino acid residues that play a key role in binding the ligand to PB2, suggesting that we should focus on increasing and enhancing the interaction between inhibitors and these major amino acids during lead compound optimization to obtain more active PB2 inhibitors.

scholarly journals Computational Investigations on the Binding Mode of Ligands for the Cannabinoid-Activated G Protein-Coupled Receptor GPR18

Biomolecules ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 686 ◽  
Author(s):  
Alexander Neumann ◽  
Viktor Engel ◽  
Andhika B. Mahardhika ◽  
Clara T. Schoeder ◽  
Vigneshwaran Namasivayam ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
G Protein ◽  
Phenyl Ring ◽  
Binding Mode ◽  
Dynamics Simulation ◽  
Simulation Studies ◽  
Binding Modes ◽  
G Protein Coupled Receptor ◽  
G Protein Coupled

GPR18 is an orphan G protein-coupled receptor (GPCR) expressed in cells of the immune system. It is activated by the cannabinoid receptor (CB) agonist ∆9-tetrahydrocannabinol (THC). Several further lipids have been proposed to act as GPR18 agonists, but these results still require unambiguous confirmation. In the present study, we constructed a homology model of the human GPR18 based on an ensemble of three GPCR crystal structures to investigate the binding modes of the agonist THC and the recently reported antagonists which feature an imidazothiazinone core to which a (substituted) phenyl ring is connected via a lipophilic linker. Docking and molecular dynamics simulation studies were performed. As a result, a hydrophobic binding pocket is predicted to accommodate the imidazothiazinone core, while the terminal phenyl ring projects towards an aromatic pocket. Hydrophobic interaction of Cys251 with substituents on the phenyl ring could explain the high potency of the most potent derivatives. Molecular dynamics simulation studies suggest that the binding of imidazothiazinone antagonists stabilizes transmembrane regions TM1, TM6 and TM7 of the receptor through a salt bridge between Asp118 and Lys133. The agonist THC is presumed to bind differently to GPR18 than to the distantly related CB receptors. This study provides insights into the binding mode of GPR18 agonists and antagonists which will facilitate future drug design for this promising potential drug target.

scholarly journals Identification of Anti-SARS-CoV-2 Compounds from Food Using QSAR-Based Virtual Screening, Molecular Docking, and Molecular Dynamics Simulation Analysis

2021 ◽  
Vol 14 (4) ◽  
pp. 357
Author(s):  
Magdi E. A. Zaki ◽  
Sami A. Al-Hussain ◽  
Vijay H. Masand ◽  
Siddhartha Akasapu ◽  
Sumit O. Bajaj ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Virtual Screening ◽  
Simulation Analysis ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Dynamics Simulation ◽  
Multilinear Regression ◽  
Qsar Analysis ◽  
Main Protease

Due to the genetic similarity between SARS-CoV-2 and SARS-CoV, the present work endeavored to derive a balanced Quantitative Structure−Activity Relationship (QSAR) model, molecular docking, and molecular dynamics (MD) simulation studies to identify novel molecules having inhibitory potential against the main protease (Mpro) of SARS-CoV-2. The QSAR analysis developed on multivariate GA–MLR (Genetic Algorithm–Multilinear Regression) model with acceptable statistical performance (R2 = 0.898, Q2loo = 0.859, etc.). QSAR analysis attributed the good correlation with different types of atoms like non-ring Carbons and Nitrogens, amide Nitrogen, sp2-hybridized Carbons, etc. Thus, the QSAR model has a good balance of qualitative and quantitative requirements (balanced QSAR model) and satisfies the Organisation for Economic Co-operation and Development (OECD) guidelines. After that, a QSAR-based virtual screening of 26,467 food compounds and 360 heterocyclic variants of molecule 1 (benzotriazole–indole hybrid molecule) helped to identify promising hits. Furthermore, the molecular docking and molecular dynamics (MD) simulations of Mpro with molecule 1 recognized the structural motifs with significant stability. Molecular docking and QSAR provided consensus and complementary results. The validated analyses are capable of optimizing a drug/lead candidate for better inhibitory activity against the main protease of SARS-CoV-2.

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