Evaluations of the Absolute and Relative Free Energies for Antidepressant Binding to the Amino Acid Membrane Transporter LeuT with Free Energy Simulations

2010 ◽  
Vol 6 (6) ◽  
pp. 1900-1914 ◽  
Author(s):  
Chunfeng Zhao ◽  
David A. Caplan ◽  
Sergei Yu. Noskov
Keyword(s):  
Free Energy ◽  
Amino Acid ◽  
Membrane Transporter ◽  
Free Energies ◽  
The Absolute ◽  
Energy Simulations

Specific amino acid recognition by aspartyl-tRNA synthetase studied by free energy simulations 1 1A. R. Fersht

1998 ◽  
Vol 275 (5) ◽  
pp. 823-846 ◽  
Author(s):  
Georgios Archontis ◽  
Thomas Simonson ◽  
Dino Moras ◽  
Martin Karplus
Keyword(s):  
Free Energy ◽  
Amino Acid ◽  
Trna Synthetase ◽  
Specific Amino Acid ◽  
Energy Simulations ◽  
Amino Acid Recognition

scholarly journals The Good, the Bad, and the Ugly: “HiPen”, a New Dataset for Validating (S)QM/MM Free Energy Simulations

Molecules ◽  
2019 ◽  
Vol 24 (4) ◽  
pp. 681 ◽  
Author(s):  
Fiona Kearns ◽  
Luke Warrensford ◽  
Stefan Boresch ◽  
H. Woodcock
Keyword(s):  
Free Energy ◽  
Gas Phase ◽  
Convergence Criteria ◽  
Free Energies ◽  
Acceptance Ratio ◽  
Current State ◽  
Energy Perturbation ◽  
Energy Simulations ◽  
Molecular Description ◽  
Bennett’S Acceptance Ratio

Indirect (S)QM/MM free energy simulations (FES) are vital to efficiently incorporating sufficient sampling and accurate (QM) energetic evaluations when estimating free energies of practical/experimental interest. Connecting between levels of theory, i.e., calculating Δ A l o w → h i g h , remains to be the most challenging step within an indirect FES protocol. To improve calculations of Δ A l o w → h i g h , we must: (1) compare the performance of all FES methods currently available; and (2) compile and maintain datasets of Δ A l o w → h i g h calculated for a wide-variety of molecules so that future practitioners may replicate or improve upon the current state-of-the-art. Towards these two aims, we introduce a new dataset, “HiPen”, which tabulates Δ A g a s M M → 3 o b (the free energy associated with switching from an M M to an S C C − D F T B molecular description using the 3ob parameter set in gas phase), calculated for 22 drug-like small molecules. We compare the calculation of this value using free energy perturbation, Bennett’s acceptance ratio, Jarzynski’s equation, and Crooks’ equation. We also predict the reliability of each calculated Δ A g a s M M → 3 o b by evaluating several convergence criteria including sample size hysteresis, overlap statistics, and bias metric ( Π ). Within the total dataset, three distinct categories of molecules emerge: the “good” molecules, for which we can obtain converged Δ A g a s M M → 3 o b using Jarzynski’s equation; “bad” molecules which require Crooks’ equation to obtain a converged Δ A g a s M M → 3 o b ; and “ugly” molecules for which we cannot obtain reliably converged Δ A g a s M M → 3 o b with either Jarzynski’s or Crooks’ equations. We discuss, in depth, results from several example molecules in each of these categories and describe how dihedral discrepancies between levels of theory cause convergence failures even for these gas phase free energy simulations.

scholarly journals Comparing alchemical and physical pathway methods for computing the absolute binding free energy of charged ligands

2018 ◽  
Vol 20 (25) ◽  
pp. 17081-17092 ◽  
Author(s):  
Nanjie Deng ◽  
Di Cui ◽  
Bin W. Zhang ◽  
Junchao Xia ◽  
Jeffrey Cruz ◽  
...  
Keyword(s):  
Free Energy ◽  
Binding Free Energy ◽  
Potential Of Mean Force ◽  
Free Energies ◽  
Decoupling Method ◽  
The Absolute ◽  
Absolute Binding Free Energy ◽  
Binding Free Energies ◽  
Charged Ligands

We compare the performance of the potential of mean force (PMF) method and double decoupling method (DDM) for computing absolute binding free energies for charged ligands.

Reactivity differences between haemoglobins. II. Electrostatic contribution to the free energy and enthalpy of ionization of methaemoglobins

1964 ◽  
Vol 277 (1370) ◽  
pp. 414-422 ◽  
Keyword(s):  
Free Energy ◽  
Amino Acid ◽  
Amino Acid Composition ◽  
Acid Composition ◽  
Linear Relation ◽  
Electrostatic Interactions ◽  
Free Energies ◽  
Reactive Site ◽  
Electrostatic Contribution ◽  
Enthalpy Of Ionization

It was concluded in part I that the differences between the free energies, enthalpies, and entropies of ionization of methaem oglobins A, S , and C are the result of different electrostatic interactions between the protein and the reactive site, and that this arises because of the small differences in their amino acid composition. In this paper the electrostatic contribution to the differences in the free energies of ionizations are calculated, using as a basis for calculation Kirkwood’s model for a protein. These calculations show that the observed differences in free energies may be accounted for quantitatively by the different electrostatic interactions between the protein and reactive site for the three methaemoglobins. The linear relation between Δ H ° and T Δ S °, reported in part I, is also shown to be the consequence of the electrostatic origin of the differences between these quantities. Other abnormal haemoglobins are considered in the light of the conclusions reached in this paper, and predictions are made concerning the thermodynamics of ionizations of their met forms.

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