scholarly journals Electrostatic Free Energy and Its Variations in Implicit Solvent Models

2008 ◽  
Vol 112 (10) ◽  
pp. 3058-3069 ◽  
Author(s):  
Jianwei Che ◽  
Joachim Dzubiella ◽  
Bo Li ◽  
J. Andrew McCammon
Keyword(s):  
Free Energy ◽  
Implicit Solvent ◽  
Solvent Models ◽  
Electrostatic Free Energy ◽  
Implicit Solvent Models

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.

Examining Electrostatic Influences on Base-Flipping: A Comparison of TIP3P and GB Solvent Models

2013 ◽  
Vol 13 (1) ◽  
pp. 223-237 ◽  
Author(s):  
Allyn R. Brice ◽  
Brian N. Dominy
Keyword(s):  
Free Energy ◽  
Base Pair ◽  
Umbrella Sampling ◽  
Water Molecules ◽  
Implicit Solvent ◽  
Interaction Energies ◽  
Base Flipping ◽  
Solvent Models ◽  
Explicit Water ◽  
Implicit Solvent Models

AbstractRecently, it was demonstrated that implicit solvent models were capable of generating stable B-form DNA structures. Specifically, generalized Born (GB) implicit solvent models have improved regarding the solvation of conformational sampling of DNA [1,2]. Here, we examine the performance of the GBSW and GBMV models in CHARMM for characterizing base flipping free energy profiles of undamaged and damaged DNA bases. Umbrella sampling of the base flipping process was performed for the bases cytosine, uracil and xanthine. The umbrella sampling simulations were carried-out with both explicit (TIP3P) and implicit (GB) solvent in order to establish the impact of the solvent model on base flipping. Overall, base flipping potential of mean force (PMF) profiles generated with GB solvent resulted in a greater free energy difference of flipping than profiles generated with TIP3P. One of the significant differences between implicit and explicit solvent models is the approximation of solute-solvent interactions in implicit solvent models. We calculated electrostatic interaction energies between explicit water molecules and the base targeted for flipping. These interaction energies were calculated over the base flipping reaction coordinate to illustrate the stabilizing effect of the explicit water molecules on the flipped-out state. It is known that nucleic base pair hydrogen bonds also influenced the free energy of flipping since these favorable interactions must be broken in order for a base to flip-out of the helix. The Watson-Crick base pair hydrogen bond fractions were calculated over the umbrella sampling simulation windows in order to determine the effect of base pair interactions on the base flipping free energy. It is shown that interaction energies between the flipping base and explicit water molecules are responsible for the lower base flipping free energy difference in the explicit solvent PMF profiles.

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.

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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