Are Explicit Solvent Models More Accurate than Implicit Solvent Models? A Case Study on the Menschutkin Reaction

2019 ◽  
Vol 123 (26) ◽  
pp. 5580-5589 ◽  
Author(s):  
Junbo Chen ◽  
Yihan Shao ◽  
Junming Ho
Keyword(s):  
Implicit Solvent ◽  
Solvent Models ◽  
Explicit Solvent ◽  
Implicit Solvent Models

scholarly journals Correction to Reconciling Work Functions and Adsorption Enthalpies for Implicit Solvent Models: A Pt (111)/Water Interface Case Study

2020 ◽  
Vol 16 (7) ◽  
pp. 4755-4755
Author(s):  
Gabriel Bramley ◽  
Manh-Thuong Nguyen ◽  
Vassiliki-Alexandra Glezakou ◽  
Roger Rousseau ◽  
Chris-Kriton Skylaris
Keyword(s):  
Implicit Solvent ◽  
Water Interface ◽  
Solvent Models ◽  
Work Functions ◽  
Implicit Solvent Models

scholarly journals Reconciling Work Functions and Adsorption Enthalpies for Implicit Solvent Models: A Pt (111)/Water Interface Case Study

2020 ◽  
Vol 16 (4) ◽  
pp. 2703-2715 ◽  
Author(s):  
Gabriel Bramley ◽  
Manh-Thuong Nguyen ◽  
Vassiliki-Alexandra Glezakou ◽  
Roger Rousseau ◽  
Chris-Kriton Skylaris
Keyword(s):  
Implicit Solvent ◽  
Water Interface ◽  
Solvent Models ◽  
Work Functions ◽  
Implicit Solvent Models

scholarly journals The validation of quantum chemical lipophilicity prediction of alcohols

2016 ◽  
Vol 9 (2) ◽  
pp. 89-94 ◽  
Author(s):  
Martin Michalík ◽  
Vladimír Lukeš
Keyword(s):  
Linear Correlation ◽  
Quantum Chemical ◽  
Partition Coefficients ◽  
The Other ◽  
Basis Set ◽  
Implicit Solvent ◽  
Solvent Models ◽  
Lipophilicity Prediction ◽  
Triple Zeta ◽  
Implicit Solvent Models

AbstractThe validation of octanol-water partition coefficients (logP) quantum chemical calculations is presented for 27 alkane alcohols. The chemical accuracy of predicted logPvalues was estimated for six DFT functionals (B3LYP, PBE0, M06-2X, ωB97X-D, B97-D3, M11) and three implicit solvent models. Triple-zeta basis set 6-311++G(d,p) was employed. The best linear correlation with the experimental logPvalues was achieved for the B3LYP and B97-D3 functionals combined with the SMD model. On the other hand, no linearity was found when IEF-PCM or C-PCM implicit models were employed.

Generalized Born implicit solvent models for small molecule hydration free energies

2017 ◽  
Vol 19 (2) ◽  
pp. 1677-1685 ◽  
Author(s):  
Martin Brieg ◽  
Julia Setzler ◽  
Steffen Albert ◽  
Wolfgang Wenzel
Keyword(s):  
Free Energy ◽  
Small Molecules ◽  
Implicit Solvent ◽  
Free Energies ◽  
Hydration Free Energy ◽  
Energy Estimation ◽  
Generalized Born ◽  
Solvent Models ◽  
Molecular Force ◽  
Implicit Solvent Models

Hydration free energy estimation of small molecules from all-atom simulations was widely investigated in recent years, as it provides an essential test of molecular force fields and our understanding of solvation effects.

Thermodynamics of Helix formation in small peptides of varying lengthin vacuo, implicit solvent and explicit solvent: Comparison between AMBER force fields

2019 ◽  
Vol 18 (03) ◽  
pp. 1950015
Author(s):  
Zhaoxi Sun ◽  
Xiaohui Wang
Keyword(s):  
Amino Acids ◽  
Free Energy ◽  
Hydrogen Bonds ◽  
Force Fields ◽  
Implicit Solvent ◽  
Conformational Ensemble ◽  
Helix Formation ◽  
Solvent Models ◽  
Explicit Solvent ◽  
Amber Force Fields

Helix formation is of great significance in protein folding. The helix-forming tendencies of amino acids are accumulated along the sequence to determine the helix-forming tendency of peptides. Computer simulation can be used to model this process in atomic details and give structural insights. In the current work, we employ equilibrate-state free energy simulation to systematically study the folding/unfolding thermodynamics of a series of mutated peptides. Two AMBER force fields including AMBER99SB and AMBER14SB are compared. The new 14SB force field uses refitted torsion parameters compared with 99SB and they share the same atomic charge scheme. We find that in vacuo the helix formation is mutation dependent, which reflects the different helix propensities of different amino acids. In general, there are helix formers, helix indifferent groups and helix breakers. The helical structure becomes more favored when the length of the sequence becomes longer, which arises from the formation of additional backbone hydrogen bonds in the lengthened sequence. Therefore, the helix indifferent groups and helix breakers will become helix formers in long sequences. Also, protonation-dependent helix formation is observed for ionizable groups. In 14SB, the helical structures are more stable than in 99SB and differences can be observed in their grouping schemes, especially in the helix indifferent group. In solvents, all mutations are helix indifferent due to protein–solvent interactions. The decrease in the number of backbone hydrogen bonds is the same with the increase in the number of protein–water hydrogen bonds. The 14SB in explicit solvent is able to capture the free energy minima in the helical state while 14SB in implicit solvent, 99SB in explicit solvent and 99SB in implicit solvent cannot. The helix propensities calculated under 14SB agree with the corresponding experimental values, while the 99SB results obviously deviate from the references. Hence, implicit solvent models are unable to correctly describe the thermodynamics even for the simple helix formation in isolated peptides. Well-developed force fields and explicit solvents are needed to correctly describe the protein dynamics. Aside from the free energy, differences in conformational ensemble under different force fields in different solvent models are observed. The numbers of hydrogen bonds formed under different force fields agree and they are mostly determined by the solvent model.

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