scholarly journals GAFF/IPolQ-Mod+LJ-Fit: Optimized force field parameters for solvation free energy predictions

ADMET & DMPK ◽  
2020 ◽  
Author(s):  
Andreas Mecklenfeld ◽  
Gabriele Raabe
Keyword(s):  
Free Energy ◽  
Force Field ◽  
Fluid Phase ◽  
Solvation Free Energy ◽  
Rational Drug Design ◽  
Phase Behaviour ◽  
Liquid Density ◽  
Free Energies ◽  
Implicit Representation ◽  
Amber Force Field

<p class="ADMETabstracttext">Rational drug design featuring explicit solubility considerations can greatly benefit from molecular dynamics simulations, as they allow for the prediction of the Gibbs free energy of solvation and thus relative solubilities. In our previous work (A. Mecklenfeld, G. Raabe. J. Chem. Theory Comput. <strong>13 </strong>no. 12 (2017) 6266–6274), we have compared solvation free energy results obtained with the General Amber Force Field (GAFF) and its default restrained electrostatic potential (RESP) partial charges to those obtained by modified implicitly polarized charges (IPolQ-Mod) for an implicit representation of impactful polarization effects. In this work, we have adapted Lennard-Jones parameters for GAFF atom types in combination with IPolQ-Mod to further improve the accuracies of solvation free energy and liquid density predictions. We thereby focus on prominent atom types in common drugs. For the refitting, 357 respectively 384 systems were considered for free energies and densities and validation was performed for 142 free energies and 100 densities of binary mixtures. By the in-depth comparison of simulation results for default GAFF, GAFF with IPolQ-Mod and our new set of parameters, which we label GAFF/IPolQ-Mod+LJ-Fit, we can clearly highlight the improvements of our new model for the description of both relative solubilities and fluid phase behaviour.</p>

Large-Scale Free Energy Calculations on a Computational MOF Database: Toward Synthetic Likelihood Predictions

2020 ◽  
Author(s):  
Ryther Anderson ◽  
Diego Gómez-Gualdrón
Keyword(s):  
Free Energy ◽  
Force Field ◽  
Large Scale ◽  
Free Energy Calculations ◽  
Free Energies ◽  
Scale Free ◽  
Computational Screening ◽  
Synthetic Accessibility ◽  
Isomorphic Series ◽  
Metal Organic

Metal-organic frameworks (MOFs) have captivated the research community due to a modular crystal structure that is tailorable for many applications. However, with millions of possible MOFs to be considered, it is challenging to identify the ideal MOF for the application of choice. Although computational screening of MOF databases has provided a fast way to evaluate MOF properties, validation experiments on predicted “exceptional” MOFs are not common due to uncertainties on the synthetic likelihood of computationally constructed MOFs, hence hindering material discovery. Aiming to leverage the perspective provided by large datasets, here we created and screened a topologically diverse database of 8,500 MOFs to interrogate whether thermodynamic stability metrics such as free energy could be used to generally predict the synthetic likelihood of computationally constructed MOFs. To this end, we first evaluated the suitability of two methods and three force fields to calculate free energies in MOFs at large scale, settling on the Frenkel-Ladd path thermodynamic integration method and the UFF4MOF force field. Upon defining a relative free energy, Δ<sub>LM</sub>F<sub>FL</sub>, that corrects for some force field artifacts specific to MOF nodes, we found that previously synthesized MOFs tended to cluster in a region below Δ<sub>LM</sub>F<sub>FL</sub> = 4.4 kJ/mol per atom, suggesting a general first filter to discriminate between synthetically likely and unlikely MOFs. However, a second filter is needed when several MOF isomorphs are below the Δ<sub>LM</sub>F<sub>FL</sub> threshold. In 84% of the cases, the synthetically accessible MOF within an isomorphic series presented the lowest predicted free energy. The present; work suggests that crystal free energies could be key to understanding synthetic likelihood for MOFs in computational databases (and MOFs in general), and that the thermodynamics stability of the fully assembled MOF often determines synthetic accessibility.

Large-Scale Free Energy Calculations on a Computational MOF Database: Toward Synthetic Likelihood Predictions

2020 ◽  
Author(s):  
Ryther Anderson ◽  
Diego Gómez-Gualdrón
Keyword(s):  
Free Energy ◽  
Force Field ◽  
Large Scale ◽  
Free Energy Calculations ◽  
Free Energies ◽  
Scale Free ◽  
Computational Screening ◽  
Synthetic Accessibility ◽  
Isomorphic Series ◽  
Metal Organic

Metal-organic frameworks (MOFs) have captivated the research community due to a modular crystal structure that is tailorable for many applications. However, with millions of possible MOFs to be considered, it is challenging to identify the ideal MOF for the application of choice. Although computational screening of MOF databases has provided a fast way to evaluate MOF properties, validation experiments on predicted “exceptional” MOFs are not common due to uncertainties on the synthetic likelihood of computationally constructed MOFs, hence hindering material discovery. Aiming to leverage the perspective provided by large datasets, here we created and screened a topologically diverse database of 8,500 MOFs to interrogate whether thermodynamic stability metrics such as free energy could be used to generally predict the synthetic likelihood of computationally constructed MOFs. To this end, we first evaluated the suitability of two methods and three force fields to calculate free energies in MOFs at large scale, settling on the Frenkel-Ladd path thermodynamic integration method and the UFF4MOF force field. Upon defining a relative free energy, Δ<sub>LM</sub>F<sub>FL</sub>, that corrects for some force field artifacts specific to MOF nodes, we found that previously synthesized MOFs tended to cluster in a region below Δ<sub>LM</sub>F<sub>FL</sub> = 4.4 kJ/mol per atom, suggesting a general first filter to discriminate between synthetically likely and unlikely MOFs. However, a second filter is needed when several MOF isomorphs are below the Δ<sub>LM</sub>F<sub>FL</sub> threshold. In 84% of the cases, the synthetically accessible MOF within an isomorphic series presented the lowest predicted free energy. The present; work suggests that crystal free energies could be key to understanding synthetic likelihood for MOFs in computational databases (and MOFs in general), and that the thermodynamics stability of the fully assembled MOF often determines synthetic accessibility.

Prediction of Solvation Free Energies with Thermodynamic Integration Using the General Amber Force Field

2014 ◽  
Vol 10 (8) ◽  
pp. 3570-3577 ◽  
Author(s):  
Silvia A. Martins ◽  
Sergio F. Sousa ◽  
Maria João Ramos ◽  
Pedro A. Fernandes
Keyword(s):  
Force Field ◽  
Thermodynamic Integration ◽  
Free Energies ◽  
Amber Force Field ◽  
Solvation Free Energies

Protein Structure Prediction with a Combined Solvation Free Energy-Molecular Mechanics Force Field

1993 ◽  
Vol 10 (2-6) ◽  
pp. 121-149 ◽  
Author(s):  
Celia A. Schiffer ◽  
James W. Caldwell ◽  
Peter A. Kollman ◽  
Robert M. Stroud
Keyword(s):  
Free Energy ◽  
Protein Structure ◽  
Force Field ◽  
Molecular Mechanics ◽  
Protein Structure Prediction ◽  
Structure Prediction ◽  
Solvation Free Energy

scholarly journals Chemically Interpretable Graph Interaction Network for Prediction of Pharmacokinetic Properties of Drug-Like Molecules

2020 ◽  
Vol 34 (01) ◽  
pp. 873-880 ◽  
Author(s):  
Yashaswi Pathak ◽  
Siddhartha Laghuvarapu ◽  
Sarvesh Mehta ◽  
U. Deva Priyakumar
Keyword(s):  
Neural Network ◽  
Free Energy ◽  
Message Passing ◽  
Solvation Free Energy ◽  
The Body ◽  
Free Energies ◽  
Pharmacokinetic Properties ◽  
Interaction Map ◽  
Solvent Molecules ◽  
Solvation Free Energies

Solubility of drug molecules is related to pharmacokinetic properties such as absorption and distribution, which affects the amount of drug that is available in the body for its action. Computational or experimental evaluation of solvation free energies of drug-like molecules/solute that quantify solubilities is an arduous task and hence development of reliable computationally tractable models is sought after in drug discovery tasks in pharmaceutical industry. Here, we report a novel method based on graph neural network to predict solvation free energies. Previous studies considered only the solute for solvation free energy prediction and ignored the nature of the solvent, limiting their practical applicability. The proposed model is an end-to-end framework comprising three phases namely, message passing, interaction and prediction phases. In the first phase, message passing neural network was used to compute inter-atomic interaction within both solute and solvent molecules represented as molecular graphs. In the interaction phase, features from the preceding step is used to calculate a solute-solvent interaction map, since the solvation free energy depends on how (un)favorable the solute and solvent molecules interact with each other. The calculated interaction map that captures the solute-solvent interactions along with the features from the message passing phase is used to predict the solvation free energies in the final phase. The model predicts solvation free energies involving a large number of solvents with high accuracy. We also show that the interaction map captures the electronic and steric factors that govern the solubility of drug-like molecules and hence is chemically interpretable.

scholarly journals Non-equilibrium approach for binding free energies in cyclodextrins in SAMPL7: force fields and software

2020 ◽  
Author(s):  
Yuriy Khalak ◽  
Gary Tresadern ◽  
Bert L. de Groot ◽  
Vytautas Gapsys
Keyword(s):  
Free Energy ◽  
Force Field ◽  
Force Fields ◽  
Simulation Software ◽  
Energy Estimates ◽  
Energy Calculation ◽  
Free Energies ◽  
Guest Molecules ◽  
Software Packages ◽  
Non Equilibrium

AbstractIn the current work we report on our participation in the SAMPL7 challenge calculating absolute free energies of the host–guest systems, where 2 guest molecules were probed against 9 hosts-cyclodextrin and its derivatives. Our submission was based on the non-equilibrium free energy calculation protocol utilizing an averaged consensus result from two force fields (GAFF and CGenFF). The submitted prediction achieved accuracy of $${1.38}\,\hbox {kcal}/\hbox {mol}$$ 1.38 kcal / mol in terms of the unsigned error averaged over the whole dataset. Subsequently, we further report on the underlying reasons for discrepancies between our calculations and another submission to the SAMPL7 challenge which employed a similar methodology, but disparate ligand and water force fields. As a result we have uncovered a number of issues in the dihedral parameter definition of the GAFF 2 force field. In addition, we identified particular cases in the molecular topologies where different software packages had a different interpretation of the same force field. This latter observation might be of particular relevance for systematic comparisons of molecular simulation software packages. The aforementioned factors have an influence on the final free energy estimates and need to be considered when performing alchemical calculations.

Prediction of Absolute Solvation Free Energies using Molecular Dynamics Free Energy Perturbation and the OPLS Force Field

2010 ◽  
Vol 6 (5) ◽  
pp. 1509-1519 ◽  
Author(s):  
Devleena Shivakumar ◽  
Joshua Williams ◽  
Yujie Wu ◽  
Wolfgang Damm ◽  
John Shelley ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Force Field ◽  
Free Energy Perturbation ◽  
Free Energies ◽  
Energy Perturbation ◽  
Solvation Free Energies

scholarly journals Optimized Halogen Atomic Radii for PBSA Calculations Using Off-Center Point-Charges

2021 ◽  
Author(s):  
Andreia Fortuna ◽  
Paulo J. Costa
Keyword(s):  
Force Field ◽  
Free Energies ◽  
Field Methods ◽  
Amber Force Field ◽  
Center Point ◽  
Common Strategy ◽  
Poisson Boltzmann ◽  
General Force ◽  
Solvation Free Energies ◽  
Atomic Radii

<div>In force field methods, the usage of off-center point-charges, also called extra-points (EPs), is a common strategy to tackle the anisotropy of the electrostatic potential of covalently-bonded halogens (X), thus allowing the description of halogen bonds (XBs) at the molecular mechanics / molecular dynamics (MM/MD) level. Diverse EP implementations exist in the literature differing on the charge sets and/or the X–EP distances. Poisson–Boltzmann and surface area (PBSA) calculations can be used to obtain solvation free energies (∆G solv ) of small molecules, often to compute binding free energies (∆G bind ) at the MM PBSA level. This method depends, among other parameters, on the empirical assignment of atomic radii (PB radii). Given the multiplicity of off-center point-charges models and the lack of specific PB radii for halogens compatible with such implementations, in this work we assessed the performance of PBSA calculations for the estimation of ∆G solv values in water (∆G hyd ), also conducting an optimization of the halogen PB radii (Cl, Br, and I) for each EP model. We not only expand the usage of EP models in the scope of the General AMBER Force Field (GAFF) but also provide the first optimized halogen PB radii in the context of the CHARMM General Force Field (CGenFF), thus contributing to improving the description of halogenated compounds in PBSA calculations.</div>

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