Free-energy calculations using classical molecular simulation: application to the determination of the melting point and chemical potential of a flexible RDX model

2016 ◽  
Vol 18 (11) ◽  
pp. 7841-7850 ◽  
Author(s):  
Michael S. Sellers ◽  
Martin Lísal ◽  
John K. Brennan
Keyword(s):  
Free Energy ◽  
Melting Point ◽  
Molecular Simulation ◽  
Chemical Potential ◽  
Free Energy Calculations ◽  
Energy Calculations ◽  
Liquid Phases

Several methods are used in sequence to determine the chemical potential of atomistic RDX in the solid and liquid phases, and its corresponding melting point. Results yield the thermodynamic melting point of 488.75 K at 1.0 atm.

scholarly journals Reproducibility of Free Energy Calculations across Different Molecular Simulation Software Packages

2018 ◽  
Vol 14 (11) ◽  
pp. 5567-5582 ◽  
Author(s):  
Hannes H. Loeffler ◽  
Stefano Bosisio ◽  
Guilherme Duarte Ramos Matos ◽  
Donghyuk Suh ◽  
Benoit Roux ◽  
...  
Keyword(s):  
Free Energy ◽  
Molecular Simulation ◽  
Simulation Software ◽  
Free Energy Calculations ◽  
Energy Calculations ◽  
Software Packages

scholarly journals Challenges in the use of atomistic simulations to predict solubilities of drug-like molecules

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 686 ◽  
Author(s):  
Guilherme Duarte Ramos Matos ◽  
David L. Mobley
Keyword(s):  
Free Energy ◽  
Chemical Potential ◽  
Computational Cost ◽  
Energy Model ◽  
Free Energy Calculations ◽  
Limiting Factor ◽  
Solubility Prediction ◽  
Energy Calculations ◽  
Chemical Potentials ◽  
The Absolute

Background: Solubility is a physical property of high importance to the pharmaceutical industry, the prediction of which for potential drugs has so far been a hard task. We attempted to predict the solubility of acetylsalicylic acid (ASA) by estimating the absolute chemical potentials of its most stable polymorph and of solutions with different concentrations of the drug molecule. Methods: Chemical potentials were estimated from all-atom molecular dynamics simulations.  We used the Einstein molecule method (EMM) to predict the absolute chemical potential of the solid and solvation free energy calculations to predict the excess chemical potentials of the liquid-phase systems. Results: Reliable estimations of the chemical potentials for the solid and for a single ASA molecule using the EMM required an extremely large number of intermediate states for the free energy calculations, meaning that the calculations were extremely demanding computationally. Despite the computational cost, however, the computed value did not agree well with the experimental value, potentially due to limitations with the underlying energy model. Perhaps better values could be obtained with a better energy model; however, it seems likely computational cost may remain a limiting factor for use of this particular approach to solubility estimation.    Conclusions: Solubility prediction of drug-like solids remains computationally challenging, and it appears that both the underlying energy model and the computational approach applied may need improvement before the approach is suitable for routine use.

scholarly journals Reproducibility of Free Energy Calculations Across Different Molecular Simulation Software

2018 ◽  
Author(s):  
Hannes H. Loeffler ◽  
Stefano Bosisio ◽  
Guilherme Duarte Ramos Matos ◽  
Donghyuk Suh ◽  
Benoît Roux ◽  
...  
Keyword(s):  
Free Energy ◽  
Molecular Simulation ◽  
Simulation Software ◽  
Free Energy Calculations ◽  
Free Energies ◽  
Small Organic Molecules ◽  
Energy Calculations ◽  
Alchemical Free Energy ◽  
Attention To Detail ◽  
Alchemical Free Energy Calculations

<div> <div> <div> <p>Alchemical free energy calculations are an increasingly important modern simulation technique. Contemporary molecular simulation software such as AMBER, CHARMM, GROMACS and SOMD include support for the method. Implementation details vary among those codes but users expect reliability and reproducibility, i.e. for a given molec- ular model and set of forcefield parameters, comparable free energy should be obtained within statistical bounds regardless of the code used. Relative alchemical free energy (RAFE) simulation is increasingly used to support molecule discovery projects, yet the reproducibility of the methodology has been less well tested than its absolute counter- part. Here we present RAFE calculations of hydration free energies for a set of small organic molecules and demonstrate that free energies can be reproduced to within about 0.2 kcal/mol with aforementioned codes. Achieving this level of reproducibility requires considerable attention to detail and package–specific simulation protocols, and no uni- versally applicable protocol emerges. The benchmarks and protocols reported here should be useful for the community to validate new and future versions of software for free energy calculations.</p></div></div></div>

scholarly journals Reproducibility of Free Energy Calculations Across Different Molecular Simulation Software

2018 ◽  
Author(s):  
Hannes H. Loeffler ◽  
Stefano Bosisio ◽  
Guilherme Duarte Ramos Matos ◽  
Donghyuk Suh ◽  
Benoît Roux ◽  
...  
Keyword(s):  
Free Energy ◽  
Molecular Simulation ◽  
Simulation Software ◽  
Free Energy Calculations ◽  
Free Energies ◽  
Small Organic Molecules ◽  
Energy Calculations ◽  
Alchemical Free Energy ◽  
Attention To Detail ◽  
Alchemical Free Energy Calculations

<div> <div> <div> <p>Alchemical free energy calculations are an increasingly important modern simulation technique. Contemporary molecular simulation software such as AMBER, CHARMM, GROMACS and SOMD include support for the method. Implementation details vary among those codes but users expect reliability and reproducibility, i.e. for a given molec- ular model and set of forcefield parameters, comparable free energy should be obtained within statistical bounds regardless of the code used. Relative alchemical free energy (RAFE) simulation is increasingly used to support molecule discovery projects, yet the reproducibility of the methodology has been less well tested than its absolute counter- part. Here we present RAFE calculations of hydration free energies for a set of small organic molecules and demonstrate that free energies can be reproduced to within about 0.2 kcal/mol with aforementioned codes. Achieving this level of reproducibility requires considerable attention to detail and package–specific simulation protocols, and no uni- versally applicable protocol emerges. The benchmarks and protocols reported here should be useful for the community to validate new and future versions of software for free energy calculations.</p></div></div></div>

scholarly journals Challenges of the Use of Atomistic Simulations to Predict Solubilities of Drug-like Molecules

2018 ◽  
Author(s):  
Guilherme Duarte Ramos Matos ◽  
David Mobley
Keyword(s):  
Free Energy ◽  
Chemical Potential ◽  
Computational Cost ◽  
Physical Property ◽  
Energy Model ◽  
Free Energy Calculations ◽  
Limiting Factor ◽  
Solubility Prediction ◽  
Energy Calculations ◽  
Chemical Potentials

<div><b>Background.</b></div><div>Solubility is a physical property of extreme importance to the Pharmaceutical industry whose prediction for potential drugs has so far been a hard task.</div><div>We attempted to predict the solubility of acetylsalicylic acid (ASA) by estimating absolute chemical potentials of its most stable polymorph and of solutions with different concentrations of the drug molecule.</div><div><br></div><div><b>Methods.</b></div><div>Chemical potentials were estimated from all-atom molecular dynamics simulations. </div><div>We used the Einstein Molecule Method to predict the absolute chemical potential of the solid and solvation free energy calculations to predict the excess chemical potentials of the liquid phase systems.</div><div><br></div><div><b>Results.</b></div><div>Reliable estimations of the chemical potentials for the solid and for a single ASA molecule using the Einstein Molecule Method required an extremely large number of intermediate states for the free energy calculations, meaning that the calculations were extremely demanding computationally.</div><div>Despite the computational cost, however, the computed value did not agree well with experiment, potentially due to limitations with the underlying energy model.</div><div>Perhaps better values could be obtained with a better energy model; however, it seems likely computational cost may remain a limiting factor for use of this particular approach to solubility estimation. </div><div><br></div><div><b>Conclusions.</b></div><div>Solubility prediction of drug-like solids still is a challenge on the computational side, and it appears that both the underlying energy model and the computational approach applied may need improvement before the approach is suitable for routine use.</div>

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