scholarly journals In Silico Screening of Semi-Synthesized Compounds as Potential Inhibitors for SARS-CoV-2 Papain-Like Protease: Pharmacophoric Features, Molecular Docking, ADMET, Toxicity and DFT Studies

Molecules ◽  
2021 ◽  
Vol 26 (21) ◽  
pp. 6593
Author(s):  
Mohamed S. Alesawy ◽  
Eslam B. Elkaeed ◽  
Aisha A. Alsfouk ◽  
Ahmed M. Metwaly ◽  
Ibrahim. H. Eissa
Keyword(s):  
Structural Features ◽  
Docking Studies ◽  
Proteolytic Processing ◽  
Binding Modes ◽  
Free Energies ◽  
Essential Enzyme ◽  
Potential Inhibitors ◽  
Molecular Electrostatic Potential Maps ◽  
Better Than ◽  
Binding Free Energies

Papain-like protease is an essential enzyme in the proteolytic processing required for the replication of SARS-CoV-2. Accordingly, such an enzyme is an important target for the development of anti-SARS-CoV-2 agents which may reduce the mortality associated with outbreaks of SARS-CoV-2. A set of 69 semi-synthesized molecules that exhibited the structural features of SARS-CoV-2 papain-like protease inhibitors (PLPI) were docked against the coronavirus papain-like protease (PLpro) enzyme (PDB ID: (4OW0). Docking studies showed that derivatives 34 and 58 were better than the co-crystallized ligand while derivatives 17, 28, 31, 40, 41, 43, 47, 54, and 65 exhibited good binding modes and binding free energies. The pharmacokinetic profiling study was conducted according to the four principles of the Lipinski rules and excluded derivative 31. Furthermore, ADMET and toxicity studies showed that derivatives 28, 34, and 47 have the potential to be drugs and have been demonstrated as safe when assessed via seven toxicity models. Finally, comparing the molecular orbital energies and the molecular electrostatic potential maps of 28, 34, and 47 against the co-crystallized ligand in a DFT study indicated that 28 is the most promising candidate to interact with the target receptor (PLpro).

Molecular Docking Studies on Isocytosine Analogues as Xanthine Oxidase Inhibitors

Drug Research ◽  
2018 ◽  
Vol 68 (07) ◽  
pp. 395-402 ◽  
Author(s):  
Subhajit Roy ◽  
Bawneet Narang ◽  
Manish Gupta ◽  
Vikrant Abbot ◽  
Virender Singh ◽  
...  
Keyword(s):  
Xanthine Oxidase ◽  
Docking Studies ◽  
Binding Modes ◽  
Free Energies ◽  
Flexible Docking ◽  
Docking Simulations ◽  
Xanthine Oxidase Inhibitors ◽  
Best Fit ◽  
Insight Into ◽  
Binding Free Energies

AbstractFlexible docking simulations were carried out on a series of isocytosine analogs as xanthine oxidase (XO) inhibitors. This was done by analysing the interaction of these compounds at the active site of XO. The binding free energies of the analogs were calculated using GoldScore. The binding modes of the best-fit conformation were studied, providing some handy important interactions. The results obtained henceforth provided an insight into the pharmacophoric structural requirements for XO inhibition for this class of molecules.

scholarly journals SuCOS is Better than RMSD for Evaluating Fragment Elaboration and Docking Poses

2019 ◽  
Author(s):  
Susan Leung ◽  
Michael Bodkin ◽  
Frank von Delft ◽  
Paul Brennan ◽  
Garrett Morris
Keyword(s):  
Binding Mode ◽  
Docking Studies ◽  
Binding Modes ◽  
False Negatives ◽  
Ligand Interaction ◽  
Cross Docking ◽  
Protein Ligand Interaction ◽  
Feature Overlap ◽  
Better Than ◽  
Fragment Based Drug Discovery

One of the fundamental assumptions of fragment-based drug discovery is that the fragment’s binding mode will be conserved upon elaboration into larger compounds. The most common way of quantifying binding mode similarity is Root Mean Square Deviation (RMSD), but Protein Ligand Interaction Fingerprint (PLIF) similarity and shape-based metrics are sometimes used. We introduce SuCOS, an open-source shape and chemical feature overlap metric. We explore the strengths and weaknesses of RMSD, PLIF similarity, and SuCOS on a dataset of X-ray crystal structures of paired elaborated larger and smaller molecules bound to the same protein. Our redocking and cross-docking studies show that SuCOS is superior to RMSD and PLIF similarity. When redocking, SuCOS produces fewer false positives and false negatives than RMSD and PLIF similarity; and in cross-docking, SuCOS is better at differentiating experimentally-observed binding modes of an elaborated molecule given the pose of its non-elaborated counterpart. Finally we show that SuCOS performs better than AutoDock Vina at differentiating actives from decoy ligands using the DUD-E dataset. SuCOS is available at https://github.com/susanhleung/SuCOS . <br>

scholarly journals SuCOS is Better than RMSD for Evaluating Fragment Elaboration and Docking Poses

2019 ◽  
Author(s):  
Susan Leung ◽  
Michael Bodkin ◽  
Frank von Delft ◽  
Paul Brennan ◽  
Garrett Morris
Keyword(s):  
Binding Mode ◽  
Docking Studies ◽  
Binding Modes ◽  
False Negatives ◽  
Ligand Interaction ◽  
Cross Docking ◽  
Protein Ligand Interaction ◽  
Feature Overlap ◽  
Better Than ◽  
Fragment Based Drug Discovery

One of the fundamental assumptions of fragment-based drug discovery is that the fragment’s binding mode will be conserved upon elaboration into larger compounds. The most common way of quantifying binding mode similarity is Root Mean Square Deviation (RMSD), but Protein Ligand Interaction Fingerprint (PLIF) similarity and shape-based metrics are sometimes used. We introduce SuCOS, an open-source shape and chemical feature overlap metric. We explore the strengths and weaknesses of RMSD, PLIF similarity, and SuCOS on a dataset of X-ray crystal structures of paired elaborated larger and smaller molecules bound to the same protein. Our redocking and cross-docking studies show that SuCOS is superior to RMSD and PLIF similarity. When redocking, SuCOS produces fewer false positives and false negatives than RMSD and PLIF similarity; and in cross-docking, SuCOS is better at differentiating experimentally-observed binding modes of an elaborated molecule given the pose of its non-elaborated counterpart. Finally we show that SuCOS performs better than AutoDock Vina at differentiating actives from decoy ligands using the DUD-E dataset. SuCOS is available at https://github.com/susanhleung/SuCOS . <br>

Theoretical study of the binding profile of an allosteric modulator NS-1738 with a chimera structure of the α7 nicotinic acetylcholine receptor

2016 ◽  
Vol 18 (40) ◽  
pp. 28003-28009 ◽  
Author(s):  
Guanglin Kuang ◽  
Xu Wang ◽  
Christer Halldin ◽  
Agneta Nordberg ◽  
Bengt Långström ◽  
...  
Keyword(s):  
Acetylcholine Receptor ◽  
Nicotinic Acetylcholine Receptor ◽  
Theoretical Study ◽  
Allosteric Modulator ◽  
Simulation Methods ◽  
Binding Modes ◽  
Free Energies ◽  
Α7 Nicotinic Acetylcholine Receptor ◽  
Nicotinic Acetylcholine ◽  
Binding Free Energies

The binding modes and binding free energies of the allosteric modulator NS-1738 with a chimera structure of the α7 nicotinic acetylcholine receptor have been studied by molecular simulation methods.

Molecular modeling and docking calculations of 4-acyloxy-biphenyl-4′-N-butylcarbamates as potential inhibitors of human butyrylcholinesterase

2016 ◽  
Vol 94 (1) ◽  
pp. 72-77 ◽  
Author(s):  
Yu-Fang Shen ◽  
Gan-Hong Chen ◽  
Shu-Hsien Lin ◽  
Gialih Lin
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Binding Energy ◽  
Linear Correlation ◽  
Kinetic Studies ◽  
Docking Studies ◽  
Binding Energies ◽  
Binding Modes ◽  
Docking Calculations ◽  
Potential Inhibitors

The kinetic studies and drug designs of butyrylcholinesterase play an important role in the development of Alzheimer’s disease therapeutics. In this research, automated docking studies were performed to provide useful insights into butyrylcholinesterase inhibition binding modes with designed 4-acyloxy-biphenyl-4′-N-butylcarbamates (compounds 1–8). Moreover, several significant linear correlations between experimental and calculated docking results are observed. Among compounds 1–7, compound 3, which exhibits the strongest hydrophobicity and has four carbonyl hydrogen bindings, shows the highest binding affinity (Ki = 1.4 μmol/L) with a binding energy of −7.99 kcal/mol. The observed linear correlation of experimental and calculated inhibition constants (Ki) indicates that the molecular docking results are reliable. Moreover, a good linear correlation is observed between calculated binding energies and experimental pKi. The experimental Hansch hydrophobicity constants (π values) are also correlated with the docked binding energy. This study reveals important correlations between butyrylcholinesterase experimental and docking results that contribute to the kinetic based identification of antagonists for the treatment of Alzheimer’s disease. Furthermore, these docked models provide important insights into a potential series of 4,4′-biphenol-based inhibitors of butyrylcholinesterase.

scholarly journals Icotinib, Almonertinib, and Olmutinib: A 2D Similarity/Docking-based Study to Predict the Potential Binding Modes and Interactions into EGFR

Molecules ◽  
2021 ◽  
Vol 26 (21) ◽  
pp. 6423
Author(s):  
Faisal Almalki ◽  
Ahmed Shawky ◽  
Ashraf Abdalla ◽  
Ahmed Gouda
Keyword(s):  
Similarity Search ◽  
Docking Study ◽  
Binding Modes ◽  
Free Energies ◽  
Binding Characteristics ◽  
High Binding ◽  
Egfr Ligands ◽  
Potential Binding ◽  
Michael Acceptor ◽  
Binding Free Energies

In the current study, a 2D similarity/docking-based study was used to predict the potential binding modes of icotinib, almonertinib, and olmutinib into EGFR. The similarity search of icotinib, almonertinib, and olmutinib against a database of 154 EGFR ligands revealed the highest similarity scores with erlotinib (0.9333), osimertinib (0.9487), and WZ4003 (0.8421), respectively. In addition, the results of the docking study of the three drugs into EGFR revealed high binding free energies (Gb = −6.32 to −8.42 kcal/mol) compared to the co-crystallized ligands (Gb = −7.03 to −8.07 kcal/mol). Analysis of the top-scoring poses of the three drugs was done to identify their potential binding modes. The distances between Cys797 in EGFR and the Michael acceptor sites in almonertinib and olmutinib were determined. In conclusion, the results could provide insights into the potential binding characteristics of the three drugs into EGFR which could help in the design of new more potent analogs.

scholarly journals Molecular Docking, ADME Analysis, and Estimation of MM/GBSA Binding-Free Energies of Coumarin Derivatives as Potential Inhibitors of SARS CoV-2 Receptors

2020 ◽  
Author(s):  
Akhilesh Kumar Maurya ◽  
Nidhi Mishra
Keyword(s):  
Free Energy ◽  
Molecular Docking ◽  
Severe Acute Respiratory Syndrome ◽  
Specific Drug ◽  
Coumarin Derivatives ◽  
Free Energies ◽  
Potential Inhibitors ◽  
Stimulatory Factor ◽  
Free Energy Of Binding ◽  
Binding Free Energies

Abstract Coronavirus Disease (COVID-19) is recently declared pandemic (WHO) caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Currently, there is no specific drug for the therapy of COVID-19. In the present study, in silico study have been done to find out possible inhibitors of SARS CoV-2. Coumarin derivatives with 2755 compounds were virtually screen against methyltransferase-stimulatory factor complex of NSP16 and NSP10, NSP15 Endoribonuclease, ADP ribose phosphatase (ADRP)of NSP3 and protease enzymes of SARS CoV-2. Docked top five compounds showed good docking scores and free energy of binding with the respective receptors. ADME/T analysis of docked compound shows the docked ligands are showing drug-likeness properties.

scholarly journals Molecular Docking Study of COVID-19 Main Protease with Clinically Approved Drugs

2020 ◽  
Author(s):  
TACHOUA Wafa ◽  
KABRINE Mohamed
Keyword(s):  
Docking Study ◽  
Docking Studies ◽  
Binding Modes ◽  
Molecular Docking Study ◽  
In Vivo Evaluation ◽  
Binding Cavity ◽  
Approved Drugs ◽  
Potential Inhibitors

<p>A novel strain of coronavirus, namely, Corona Virus Infection Disease 19 has been identified in Wuhan city of China in December 2019, continues to spread at a rapid rate worldwide. There are no specific therapies available and investigations regarding the treatment of this disease are still lacking. In order to identify a novel potent inhibitor we performed docking studies on the main virus protease with eight drugs belonging to four pharmacological classes: anti-malarial, anti-bacterial, anti-infective and anti-histamine. Among the eight studied compounds, Lymecycline and Mizolastine appear as potential inhibitors of this protease. These two compounds revealed a minimum binding energy of -8.87 and -8.71 Kcal/mol with 168 and 256 binding modes detected in the binding substrate pocket, respectively. Lymecycline and Mizolastine interact with specific residues in substrate binding cavity. Thus, Lymecycline and Mizolastione may serve as a tool to fight COVID-19 disease. However, this data need further in vitro and in vivo evaluation to repurpose these two drugs against COVID-19 disease.</p>

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