Interactions between large molecules pose a puzzle for reference quantum mechanical methods

Al-Hamdani, Yasmine S.; Nagy, Péter R.; Zen, Andrea; Barton, Dennis L.; Kállay, Mihály; Brandenburg, Jan Gerit; Tkatchenko, Alexandre

doi:10.1038/s41467-021-24119-3

Cited by 86 publications

(130 citation statements)

References 101 publications

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“…Recently, discrepancies of 1–2 kcal/mol between CCSD(T)/CBS and quantum Monte Carlo (QMC) benchmarks have been noted for two of the L7 complexes. , Our comparisons employ recent CCSD(T)/CBS benchmarks, where sensitivity to numerical thresholds was considered carefully. For the cases in question, QMC interaction energies are smaller than the CCSD(T)/CBS values, whereas MP2-based methods consistently overestimate E int .…”

Section: Alternative Descriptions Of Dispersionmentioning

confidence: 99%

Predicting and Understanding Non-Covalent Interactions Using Novel Forms of Symmetry-Adapted Perturbation Theory

2021

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Metrics & MoreArticle Recommendations CONSPECTUS: Although sometimes derided as "weak" interactions, non-covalent forces play a critical role in ligand binding and crystal packing and in determining the conformational landscape of flexible molecules. Symmetry-adapted perturbation theory (SAPT) provides a framework for accurate ab initio calculation of intermolecular interactions and furnishes a natural decomposition of the interaction energy into physically meaningful components: semiclassical electrostatics (rigorously obtained from monomer charge densities), Pauli or steric repulsion, induction (including both polarization and charge transfer), and dispersion. This decomposition helps to foster deeper understanding of non-covalent interactions and can be used to construct transferable, physics-based force fields. Separability of the SAPT interaction energy also provides the flexibility to construct composite methods, a feature that we exploit to improve the description of dispersion interactions. These are challenging to describe accurately because they arise from nonlocal electron correlation effects that appear for the first time at second order in perturbation theory but are not quantitatively described at that level.As with all quantum-chemical methods, a major limitation of SAPT is nonlinear scaling of the computational cost with respect to system size. This cost can be significantly mitigated using "SAPT0(KS)", which incorporates monomer electron correlation by means of Kohn−Sham (KS) molecular orbitals from density functional theory (DFT), as well as by an "extended" theory called XSAPT, developed by the authors. XSAPT generalizes traditional dimer SAPT to many-body systems, so that a ligand−protein interaction (for example) can be separated into contributions from individual amino acids, reducing the cost of the calculation below that of even supramolecular DFT while retaining the accuracy of high-level ab initio quantum chemistry. This Account provides an overview of the SAPT0(KS) approach and the XSAPT family of methods. Several low-cost variants are described that provide accuracy approaching that of the best ab initio benchmarks yet are affordable enough to tackle ligand−protein binding and sizable host−guest complexes. These variants include SAPT+aiD, which uses ab initio atom−atom dispersion potentials ("+aiD") in place of second-order SAPT dispersion, and also SAPT+MBD, which incorporates many-body dispersion (MBD) effects that are important in the description of nanoscale materials. Applications to drug binding highlight the size-extensive nature of dispersion, which is not a weak interaction in large systems. Other applications highlight how a physics-based analysis can sometimes upend conventional wisdom regarding intermolecular forces. In particular, careful reconsideration of π−π interactions makes clear that the quadrupolar electrostatics (or "Hunter−Sanders") model of π−π stacking should be replaced by a "van der Waals model" in which conformational preferences arise from a competition bet...

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Section: Alternative Descriptions Of Dispersionmentioning

confidence: 99%

Predicting and Understanding Non-Covalent Interactions Using Novel Forms of Symmetry-Adapted Perturbation Theory

2021

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“…Even at the state-of-the-art quantum-mechanical level, recent work showed discrepancies between two approaches for large host–guest systems (132 atoms). 150 DFT approaches can produce good absolute and relative comparisons to experimental free association enthalpies for relatively small organic host–guest complexes. 151 However, quantitative insight from DFT still requires an expert touch, long compute times and some assumed conformational rigidity.…”

Section: Exploring Host–guest Systems and Confinement In Metal–organi...mentioning

confidence: 99%

Unlocking the computational design of metal–organic cages

Tarzia

Jelfs

2022

Chem. Commun.

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“…In addition to the total energy at the equilibrium configuration, binding energy is also of great interest when studying a benzene dimer [37,38,[41][42][43], and classical methods, such as CCSD(T) and MP2, can produce results agreeing with experimental data well. However, for neural-network based QMC, the binding energy calcula-tion is more subtle and challenging due to the lack of systematic error cancellation.…”

Section: Benzenementioning

confidence: 99%

Towards the ground state of molecules via diffusion Monte Carlo on neural networks

Ren¹,

Fu²,

Chen³

2022

Preprint

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Diffusion Monte Carlo (DMC) based on fixed-node approximation has enjoyed significant developments in the past decades and become one of the go-to methods when accurate ground state energy of molecules and materials is needed. The remaining bottleneck is the limitations of the inaccurate nodal structure, prohibiting more challenging electron correlation problems to be tackled with DMC. In this work, we apply the neural-network based trial wavefunction in fixed-node DMC, which allows accurate calculation of a broad range of atomic and molecular systems of different electronic characteristics. Our method is superior in both accuracy and efficiency compared to state-of-the-art neural network methods using variational Monte Carlo. Overall, this computational framework provides a new benchmark for accurate solution of correlated electronic wavefunction and also shed light on the chemical understanding of molecules.

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Interactions between large molecules pose a puzzle for reference quantum mechanical methods

Cited by 86 publications

References 101 publications

Predicting and Understanding Non-Covalent Interactions Using Novel Forms of Symmetry-Adapted Perturbation Theory

Predicting and Understanding Non-Covalent Interactions Using Novel Forms of Symmetry-Adapted Perturbation Theory

Unlocking the computational design of metal–organic cages

Towards the ground state of molecules via diffusion Monte Carlo on neural networks

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