scholarly journals Accurate Prediction of the Hydration Free Energies of 20 Salts through Adaptive Force Matching and the Proper Comparison with Experimental References

2017 ◽  
Vol 121 (27) ◽  
pp. 6637-6645 ◽  
Author(s):  
Jicun Li ◽  
Feng Wang
Keyword(s):  
Accurate Prediction ◽  
Free Energies ◽  
Force Matching ◽  
Proper Comparison

An Accurate Prediction of Hydration Free Energies by Combination of Molecular Integral Equations Theory with Structural Descriptors

2010 ◽  
Vol 114 (37) ◽  
pp. 12068-12079 ◽  
Author(s):  
Ekaterina L. Ratkova ◽  
Gennady N. Chuev ◽  
Volodymyr P. Sergiievskyi ◽  
Maxim V. Fedorov
Keyword(s):  
Integral Equations ◽  
Accurate Prediction ◽  
Free Energies ◽  
Molecular Integral ◽  
Structural Descriptors

Rapid and Accurate Prediction of Binding Free Energies for Saquinavir-Bound HIV-1 Proteases

2008 ◽  
Vol 130 (8) ◽  
pp. 2639-2648 ◽  
Author(s):  
Ileana Stoica ◽  
S. Kashif Sadiq ◽  
Peter V. Coveney
Keyword(s):  
Accurate Prediction ◽  
Free Energies ◽  
Hiv 1 ◽  
Binding Free Energies

scholarly journals Classical and QM/MM binding free energies : Making good use of force-matching

2021 ◽  
Author(s):  
Felix Aviat ◽  
Phillip Hudson ◽  
Ruben Meana-Paneda ◽  
Luke Warrensford ◽  
Benjamin Pollard ◽  
...  
Keyword(s):  
Use Of Force ◽  
Free Energies ◽  
Force Matching ◽  
Binding Free Energies

Understanding Conformational Entropy in Small Molecules

2020 ◽  
Author(s):  
Lucian Chan ◽  
Garrett Morris ◽  
Geoffrey Hutchison
Keyword(s):  
Small Molecules ◽  
Degrees Of Freedom ◽  
Absolute Error ◽  
Low Energy ◽  
Standard Entropy ◽  
Free Energies ◽  
Conformational Entropy ◽  
Wide Range ◽  
High Degree ◽  
Empirical Corrections

The calculation of the entropy of flexible molecules can be challenging, since the number of possible conformers grows exponentially with molecule size and many low-energy conformers may be thermally accessible. Different methods have been proposed to approximate the contribution of conformational entropy to the molecular standard entropy, including performing thermochemistry calculations with all possible stable conformations, and developing empirical corrections from experimental data. We have performed conformer sampling on over 120,000 small molecules generating some 12 million conformers, to develop models to predict conformational entropy across a wide range of molecules. Using insight into the nature of conformational disorder, our cross-validated physically-motivated statistical model can outperform common machine learning and deep learning methods, with a mean absolute error ≈4.8 J/mol•K, or under 0.4 kcal/mol at 300 K. Beyond predicting molecular entropies and free energies, the model implies a high degree of correlation between torsions in most molecules, often as- sumed to be independent. While individual dihedral rotations may have low energetic barriers, the shape and chemical functionality of most molecules necessarily correlate their torsional degrees of freedom, and hence restrict the number of low-energy conformations immensely. Our simple models capture these correlations, and advance our understanding of small molecule conformational entropy.

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