Molecular Dynamics in Mixed Solvents Reveals Protein–Ligand Interactions, Improves Docking, and Allows Accurate Binding Free Energy Predictions

2017 ◽  
Vol 57 (4) ◽  
pp. 846-863 ◽  
Author(s):  
Juan Pablo Arcon ◽  
Lucas A. Defelipe ◽  
Carlos P. Modenutti ◽  
Elias D. López ◽  
Daniel Alvarez-Garcia ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Binding Free Energy ◽  
Mixed Solvents ◽  
Protein Ligand Interactions ◽  
Ligand Interactions

Correction to Molecular Dynamics in Mixed Solvents Reveals Protein–Ligand Interactions, Improves Docking and Allows Accurate Binding Free Energy Predictions

2018 ◽  
Vol 58 (6) ◽  
pp. 1312-1312
Author(s):  
Juan Pablo Arcon ◽  
Lucas A. Defelipe ◽  
Carlos P. Modenutti ◽  
Elias D. López ◽  
Daniel Alvarez Garcia ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Binding Free Energy ◽  
Mixed Solvents ◽  
Protein Ligand Interactions ◽  
Ligand Interactions

Extracting atomic contributions to binding free energy from molecular dynamics simulations with mixed solvents (MDmix)

2021 ◽  
Vol 19 ◽  
Author(s):  
Daniel Alvarez- Garcia ◽  
Peter Schmidtke ◽  
Elena Cubero ◽  
Xavier Barril
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Drug Discovery ◽  
Drug Design ◽  
Binding Free Energy ◽  
Mixed Solvents ◽  
Md Simulations ◽  
Molecular Binding ◽  
Dynamics Simulations ◽  
Energy Maps

Background: Mixed solvents MD simulations have proved to be a useful and increasingly accepted technique with several applications in structure-based drug discovery Method: Mixed solvents MD simulations have proved to be a useful and increasingly accepted technique with several applications in structure-based drug discovery Result: As such, they are hardly transferable to different molecules. Conclusion: To achieve transferable energies, we present here a method for decomposing the molecular binding free energy into accurate atomic contributions and we demonstrate with two qualitative visual examples how the corrected energy maps better match known binding hotspots and how they can reveal hidden hotspots with actual drug design potential.

scholarly journals Rapid decomposition and visualisation of protein–ligand binding free energies by residue and by water

2014 ◽  
Vol 169 ◽  
pp. 477-499 ◽  
Author(s):  
Christopher J. Woods ◽  
Maturos Malaisree ◽  
Julien Michel ◽  
Ben Long ◽  
Simon McIntosh-Smith ◽  
...  
Keyword(s):  
Free Energy ◽  
Ligand Binding ◽  
Binding Free Energy ◽  
Chem Phys ◽  
Binding Affinities ◽  
Rapid Decomposition ◽  
Protein Ligand Interactions ◽  
Ligand Interactions ◽  
Site Water ◽  
Dynamics Simulations

Recent advances in computational hardware, software and algorithms enable simulations of protein–ligand complexes to achieve timescales during which complete ligand binding and unbinding pathways can be observed. While observation of such events can promote understanding of binding and unbinding pathways, it does not alone provide information about the molecular drivers for protein–ligand association, nor guidance on how a ligand could be optimised to better bind to the protein. We have developed the waterswap (C. J. Woods et al., J. Chem. Phys., 2011, 134, 054114) absolute binding free energy method that calculates binding affinities by exchanging the ligand with an equivalent volume of water. A significant advantage of this method is that the binding free energy is calculated using a single reaction coordinate from a single simulation. This has enabled the development of new visualisations of binding affinities based on free energy decompositions to per-residue and per-water molecule components. These provide a clear picture of which protein–ligand interactions are strong, and which active site water molecules are stabilised or destabilised upon binding. Optimisation of the algorithms underlying the decomposition enables near-real-time visualisation, allowing these calculations to be used either to provide interactive feedback to a ligand designer, or to provide run-time analysis of protein–ligand molecular dynamics simulations.

scholarly journals Molecular Dynamics Simulation of Bioactive Compounds Against Six Protein Target of Sars-Cov-2 As Covid-19 Antivirus Candidates

2021 ◽  
Vol 7 (2) ◽  
pp. 178-187
Author(s):  
Fikry Awaluddin ◽  
Irmanida Batubara ◽  
Setyanto Tri Wahyudi
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Molecular Dynamics Simulation ◽  
Bioactive Compounds ◽  
Dynamics Simulation ◽  
Ligand Complex ◽  
Energy Value ◽  
Protein Target ◽  
Protein Ligand Interactions ◽  
Ligand Interactions

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is the virus that causes Coronavirus 2019 (COVID-19). To date, there has been no proven effective drug for the treatment or prevention of COVID-19. A study on developing inhibitors for this virus was performed using molecular dynamics simulation. 3CL-Pro, PL-Pro, Helicase, N, E, and M protein were used as protein targets. This study aimed to determine the stability of the selected protein-ligand complex through molecular dynamics simulation by Amber20 to propose bioactive compounds from natural products that have potential as a drug for COVID-19. Based on our previous study, the best value of free binding energy and protein-ligand interactions of the candidate compounds are obtained for each target protein through molecular docking. Corilagin (-14.42 kcal/mol), Scutellarein 7-rutinoside (-13.2 kcal/mol), Genistein 7-O-glucuronide (-10.52 kcal/mol), Biflavonoid-flavone base + 3O (-11.88 and -9.61 kcal/mol), and Enoxolone (-6.96 kcal/mol) has the best free energy value at each protein target. In molecular dynamics simulation, the 3CL-Pro-Corilagin complex was the most stable compared to other complexes, so that it was the most recommended compound. Further research is needed to test the selected ligand activity, which has the lowest free energy value of the six target proteins.

scholarly journals Binding free energy predictions in host-guest systems using Autodock4. A retrospective analysis on SAMPL6, SAMPL7 and SAMPL8 challenges

2021 ◽  
Author(s):  
Lorenzo Casbarra ◽  
Piero Procacci
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Drug Discovery ◽  
Binding Free Energy ◽  
Cost Ratio ◽  
Benefit Cost Ratio ◽  
Docking Program ◽  
Benefit Cost ◽  
Overall Reliability ◽  
Absolute Binding Free Energy

AbstractWe systematically tested the Autodock4 docking program for absolute binding free energy predictions using the host-guest systems from the recent SAMPL6, SAMPL7 and SAMPL8 challenges. We found that Autodock4 behaves surprisingly well, outperforming in many instances expensive molecular dynamics or quantum chemistry techniques, with an extremely favorable benefit-cost ratio. Some interesting features of Autodock4 predictions are revealed, yielding valuable hints on the overall reliability of docking screening campaigns in drug discovery projects.

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