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Record W4238940041 · doi:10.26434/chemrxiv.10031789.v1

Alchemical Hydration Free Energy Calculations Using Molecular Dynamics with Explicit Polarization and Induced Polarity Decoupling: An OTFP Approach

2019· preprint· en· W4238940041 on OpenAlexaff
Braden Kelly, William Smith

Bibliographic record

VenueChemRxiv · 2019
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicSpectroscopy and Quantum Chemical Studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsPartial chargePolarization (electrochemistry)SolvationMolecular dynamicsDecoupling (probability)ChemistryCoulombMoleculeElectric potential energyMolecular physicsPhysicsChemical physicsStatistical physicsComputational chemistryEnergy (signal processing)Quantum mechanicsElectronPhysical chemistry

Abstract

fetched live from OpenAlex

We present an algorithm to calculate hydration free energies in explicit solvent that incorporates polarization of the solute molecule in conjunction with the use of a classical fixed--charge force field. The goal is to improve the accuracy over the alternative approach of developing a polarizable force field with adjustable parameters. We incorporate polarization by implementing on--the--fly periodic updating of the solute's partial charges during a standard molecular dynamics (MD) alchemical change simulation by the use of mixed QM/MM calculations. We decouple the polarizing solvent's electric field along with the normal MD solute Coulomb decoupling to calculate the free energy difference between an unpolarized solute in vacuum and a fully polarized solute in solution. This approach is in contrast to the common approach of GAFF, which calculates the difference between a solute in vacuum that is over--polarized by the use of fixed charges calculated using HF/6-31G*, and correspondingly under--polarized by the same partial charge set in the solution phase. We apply our methodology to a test set of 31 molecules, ranging from small polar to large drug--like molecules. We find that results using our method with Minimum Basis Iterative Stockholder (MBIS) charges and using RESP charges with B3LYP/cc-pVTZ are superior to results calculated using the current ``gold standard" AM1--BCC method. We show results using MBIS partial charges using B3LYP/cc-pVTZ and MP2/cc-pVTZ, RESP partial charges using B3LYP/cc-pVTZ and HF/6-31G*, and AM1-BCC partial charges. Our method using MBIS in conjunction with MP2/cc-pVTZ yields an AAD that is 2.91 kJ$\cdot$mol$^{-1}$ (0.70 kcal$\cdot$mol$^{-1}$) lower than that of AM1--BCC for our test set. AM1-BCC was within experimental uncertainty on 13 \% of the data, while our method using MP2 was within experimental uncertainty on 43 \% of the data. We conjecture that results can be further improved by using Lennard--Jones and torsional parameters that are fitted to the MBIS charge method and that using RESP with our method can be improved by using a higher level of theory than B3LYP, for instance MP2 or $\omega$B97X-D.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.264
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2019
Admission routes1
Has abstractyes

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