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Record W1995818918 · doi:10.1021/ct9000922

Semiempirical Quantum Chemical PM6 Method Augmented by Dispersion and H-Bonding Correction Terms Reliably Describes Various Types of Noncovalent Complexes

2009· article· en· W1995818918 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Chemical Theory and Computation · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA and Nucleic Acid Chemistry
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBenchmark (surveying)Quantum chemicalBasis setParametrization (atmospheric modeling)Dispersion (optics)Set (abstract data type)London dispersion forceNon-covalent interactionsFunction (biology)Base (topology)Basis (linear algebra)Computational chemistryMatching (statistics)Quantum chemistryChemistryMolecular physicsMoleculePhysicsComputer scienceMathematicsQuantum mechanicsMathematical analysisDensity functional theoryStatisticsHydrogen bondGeometryvan der Waals force

Abstract

fetched live from OpenAlex

Because of its construction and parametrization for more than 80 elements, the semiempirical quantum chemical PM6 method is superior to other similar methods. Despite its advantages, however, the PM6 method fails for the description of noncovalent interactions, specifically the dispersion energy and H-bonding. Upon inclusion of correction terms for dispersion and H-bonding, the performance of the method was found to be dramatically improved. The former correction included two parameters in the damping function that were parametrized to reproduce the benchmark interaction energies [CCSD(T)/complete basis set (CBS) limit] of the dispersion-bonded complexes from the S22 data set. The latter correction was parametrized on an extended set of H-bonded stabilization energies determined at the MP2/cc-pVTZ level. The resulting PM6-DH method was tested on the S22 data set, for which chemical accuracy (error < 1 kcal/mol) was achieved, and also on the JSCH2005 set, for which significant improvement over the original PM6 method was also obtained. Implementation of analytical gradients allows very efficient geometry optimization, which, for all complexes, provides better agreement with the benchmark data. Excellent results were also achieved for small peptides, and here again, chemical accuracy was obtained (i.e., the error with respect to CCSD(T)/CBS results was smaller than 1 kcal/mol). The performance of the technique was finally demonstrated on extended complexes, namely, the porphine dimer and various graphene models with DNA bases and base pairs, where the PM6-DH stabilization energies agree very well with available benchmark data obtained with DFT-D, SCS-MP2, and MP2.5 methods. The PM6-DH calculations are very efficient and can be routinely applied for systems of up to 1000 atoms. For nonaromatic systems, the use of a linear scaling version of the SCF procedure based on localized orbitals speeds up the method significantly and allows one to investigate systems with several thousand atoms. The method can thus replace force fields, which face basic problems for the description of quantum effects, in many applications.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.413

Codex and Gemma teacher scores by category

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

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 head0.007
GPT teacher head0.277
Teacher spread0.270 · 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