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 A simple model for predicting the free energy of binding between anthracycline antibiotics and DNA.

2000 ◽  
Vol 47 (1) ◽  
pp. 1-9 ◽  
Author(s):  
W R Rudnicki ◽  
M Kurzepa ◽  
T Szczepanik ◽  
W Priebe ◽  
B Lesyng
Keyword(s):  
Free Energy ◽  
Theoretical Model ◽  
Density Functional ◽  
Binding Free Energy ◽  
Binding Energies ◽  
Free Energies ◽  
Anthracycline Antibiotics ◽  
Free Energy Of Binding ◽  
Derivatives Of ◽  
Binding Free Energies

A theoretical model for predicting the free energy of binding between anthracycline antibiotics and DNA was developed using the electron density functional (DFT) and molecular mechanics (MM) methods. Partial DFT-ESP charges were used in calculating the MM binding energies for complexes formed between anthracycline antibiotics and oligodeoxynucleotides. These energies were then compared with experimental binding free energies. The good correlation between the experimental and theoretical energies allowed us to propose a model for predicting the binding free energy for derivatives of anthracycline antibiotics and for quickly screening new anthracycline derivatives.

scholarly journals Automation of absolute protein-ligand binding free energy calculations for docking refinement and compound evaluation

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Germano Heinzelmann ◽  
Michael K. Gilson
Keyword(s):  
Free Energy ◽  
Early Stage ◽  
Binding Free Energy ◽  
Low Cost ◽  
Free Energy Calculations ◽  
Free Energies ◽  
Energy Calculations ◽  
Drug Candidates ◽  
Binding Free Energy Calculations ◽  
Binding Free Energies

AbstractAbsolute binding free energy calculations with explicit solvent molecular simulations can provide estimates of protein-ligand affinities, and thus reduce the time and costs needed to find new drug candidates. However, these calculations can be complex to implement and perform. Here, we introduce the software BAT.py, a Python tool that invokes the AMBER simulation package to automate the calculation of binding free energies for a protein with a series of ligands. The software supports the attach-pull-release (APR) and double decoupling (DD) binding free energy methods, as well as the simultaneous decoupling-recoupling (SDR) method, a variant of double decoupling that avoids numerical artifacts associated with charged ligands. We report encouraging initial test applications of this software both to re-rank docked poses and to estimate overall binding free energies. We also show that it is practical to carry out these calculations cheaply by using graphical processing units in common machines that can be built for this purpose. The combination of automation and low cost positions this procedure to be applied in a relatively high-throughput mode and thus stands to enable new applications in early-stage drug discovery.

scholarly journals Alchemical Absolute Protein-Ligand Binding Free Energies for Drug Design

2021 ◽  
Author(s):  
Yuriy Khalak ◽  
Gary Tresdern ◽  
Matteo Aldeghi ◽  
Hannah Magdalena Baumann ◽  
David L. Mobley ◽  
...  
Keyword(s):  
Free Energy ◽  
Drug Discovery ◽  
Drug Design ◽  
Ligand Binding ◽  
Binding Free Energy ◽  
Free Energy Calculations ◽  
Free Energies ◽  
Energy Calculations ◽  
Binding Free Energy Calculations ◽  
Binding Free Energies

The recent advances in relative protein-ligand binding free energy calculations have shown the value of alchemical methods in drug discovery. Accurately assessing absolute binding free energies, although highly desired, remains...

Investigations on the mechanisms of interactions between matrix metalloproteinase 9 and its flavonoid inhibitors using a combination of molecular docking, hybrid quantum mechanical/molecular mechanical calculations, and molecular dynamics simulations

2014 ◽  
Vol 92 (9) ◽  
pp. 821-830 ◽  
Author(s):  
Zhi-Guang Zhou ◽  
Qi-Zheng Yao ◽  
Dong Lei ◽  
Qing-Qing Zhang ◽  
Ji Zhang
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Molecular Dynamics Simulations ◽  
Biological Activities ◽  
Dynamics Simulation ◽  
Quantum Mechanical ◽  
Free Energies ◽  
Hydrogen Bond Networks ◽  
Dynamics Simulations ◽  
Binding Free Energies

Many experimental studies have found that flavonoids can inhibit the activities of matrix metalloproteinases (MMPs), but the relevant mechanisms are still unclear. In this paper, the interaction mechanisms of MMP-9 with its five flavonoid inhibitors are investigated using a combination of molecular docking, hybrid quantum mechanical and molecular mechanical (QM/MM) calculations, and molecular dynamics simulations. The molecular dynamics simulation results show a good linear correlation between the calculated binding free energies of QM/MM−Poisson–Boltzmann surface area (PBSA) and the experimental −log(EC50) regarding the studied five flavonoids on MMP-9 inhibition in explicit solvent. It is found that compared with the MM−PBSA method, the QM/MM−PBSA method can obviously improve the accuracy for the calculated binding free energies. The predicted binding modes of the five flavonoid−MMP-9 complexes reveal that the different hydrogen bond networks can form besides producing the Zn−O coordination bonds, which can reasonably explain previous experimental results. The agreement between our calculated results and the previous experimental facts indicates that the force field parameters used here are effective and reliable for investigating the systems of flavonoid−MMP-9 interactions, and thus, these simulations and analyses could be reproduced for the other related systems involving protein−ligand interactions. This paper may be helpful for designing the new MMP-9 inhibitors having higher biological activities by carrying out the structural modifications of flavonoid molecules.

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).

scholarly journals Alchemical Free Energy Estimators and Molecular Dynamics Engines: Accuracy, Precision and Reproducibility

2021 ◽  
Author(s):  
Alexander Wade ◽  
Agastya Bhati ◽  
Shunzhou Wan ◽  
Peter Coveney
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Binding Free Energy ◽  
Thermodynamic Integration ◽  
Free Energy Perturbation ◽  
Free Energies ◽  
Ensemble Averaging ◽  
Relative Binding ◽  
Energy Perturbation ◽  
Binding Free Energies

The binding free energy between a ligand and its target protein is an essential quantity to know at all stages of the drug discovery pipeline. Assessing this value computationally can offer insight into where efforts should be focused in the pursuit of effective therapeutics to treat myriad diseases. In this work we examine the computation of alchemical relative binding free energies with an eye to assessing reproducibility across popular molecular dynamics packages and free energy estimators. The focus of this work is on 54 ligand transformations from a diverse set of protein targets: MCL1, PTP1B, TYK2, CDK2 and thrombin. These targets are studied with three popular molecular dynamics packages: OpenMM, NAMD2 and NAMD3. Trajectories collected with these packages are used to compare relative binding free energies calculated with thermodynamic integration and free energy perturbation methods. The resulting binding free energies show good agreement between molecular dynamics packages with an average mean unsigned error between packages of 0.5 $kcal/mol$ The correlation between packages is very good with the lowest Spearman's, Pearson's and Kendall's tau correlation coefficient between two packages being 0.91, 0.89 and 0.74 respectively. Agreement between thermodynamic integration and free energy perturbation is shown to be very good when using ensemble averaging.

scholarly journals COMPUTATIONAL SCREENING AND MOLECULAR DOCKING OF LICHEN SECONDARY METABOLITES AGAINST SEVERE ACUTE RESPIRATORY SYNDROME-COV-2 MAIN PROTEASE AND SPIKE PROTEIN

2021 ◽  
pp. 100-104
Author(s):  
SENTHIL PRABHU S ◽  
SATHISHKUMAR R ◽  
KIRUTHIKA B
Keyword(s):  
Molecular Docking ◽  
Severe Acute Respiratory Syndrome ◽  
Study Finding ◽  
Spike Protein ◽  
Protein Targets ◽  
Lipinski’S Rule ◽  
Computational Screening ◽  
Main Protease ◽  
Lichen Compounds ◽  
Potential Inhibitors

Objective: At present, the coronavirus disease (COVID)-19 pandemic is increasing global health concerns. This coronavirus outbreak is caused by severe acute respiratory syndrome coronavirus (SARS-CoV)-2. Since, no specific antiviral for treatment against COVID-19, so identification of new therapeutics is an urgent need. The objective of this study is to the analysis of lichen compounds against main protease and spike protein targets of SARS-CoV-2 using in silico approach. Methods: A total of 108 lichen compounds were subjected to ADMET analysis and 14 compounds were selected based on the ADMET properties and Lipinski’s rule of five. Molecular docking was performed for screening of selected individual lichen metabolites against the main protease and spike proteins of SARS-CoV-2 by Schrodinger Glide module software. Results: Among the lead compounds, fallacinol showed the highest binding energy value of −11.83 kcal/mol against spike protein, 4-O-Demethylbarbatic acid exhibited the highest dock score of −11.67 kcal/mol against main protease. Conclusion: This study finding suggests that lichen substances may be potential inhibitors of SARS-CoV-2.

Sign in / Sign up

Export Citation Format

Share Document