Quantum Monte Carlo Methods Describe Noncovalent Interactions with Subchemical Accuracy

Dubecký, Matúš; Jurečka, Petr; Derian, René; Hobza, Pavel; Otyepka, Michal; Mitáš, Luboš

doi:10.1021/ct4006739

Cited by 90 publications

(186 citation statements)

References 50 publications

(110 reference statements)

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“…The discovery of its ability to attain ∼0.2 kcal/mol accuracy in case of noncovalent interactions as reported in the current work represents an important advance. The favourable performance of the simplified scheme also directly confirms the previous observation that the fixed-node error cancellation is the main reason for the success of the one-determinant FN-DMC in weakly bound noncovalent complexes 26 .…”

Section: Introductionsupporting

confidence: 84%

“…Tab. 1) 26 if required, as already mentioned, nevertheless here we are interested in a computationally less expensive computations -2tJ scheme. The remaining 2tJ values differ by no more than 0.1 kcal/mol from the CCSD(T)/CBS reference.…”

Section: Benchmarksmentioning

confidence: 99%

“…Second, the finite FN error of Ψ T used in DMC is expected to cancel out in energy differences nearly exactly [23][24][25][26] , because the nodes in the region of the molecule A are essentially unchanged by the presence of the weakly interacting molecule B and vice-versa. This trend has been qualitatively confirmed by a direct inspection of nodal surfaces 26 . For these reasons, FN-DMC based on single-determinant trial functions (containing e.g.…”

Section: Introductionmentioning

confidence: 99%

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Quantum Monte Carlo for noncovalent interactions: an efficient protocol attaining benchmark accuracy

Dubecký

Derian

Jurečka

et al. 2014

Phys. Chem. Chem. Phys.

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Reliable theoretical predictions of noncovalent interaction energies, which are important e.g. in drug-design and hydrogenstorage applications, belong to longstanding challenges of contemporary quantum chemistry. In this respect, the fixed-node diffusion Monte Carlo (FN-DMC) is a promising alternative to the commonly used "gold standard" coupled-cluster CCSD(T)/CBS method for its benchmark accuracy and favourable scaling, in contrast to other correlated wave function approaches. This work is focused on the analysis of protocols and possible tradeoffs for FN-DMC estimations of noncovalent interaction energies and proposes an efficient yet accurate computational protocol using simplified explicit correlation terms with a favorable O(N 3 ) scaling. It achieves an excellent agreement (mean unsigned error ∼0.2 kcal/mol) with respect to the CCSD(T)/CBS data on a number of complexes, including benzene/hydrogen, T-shape benzene dimer, stacked adenine-thymine and a set of small noncovalent complexes A24. The high accuracy and reduced computational costs predestinate the reported protocol for practical interaction energy calculations of large noncovalent complexes, where the CCSD(T)/CBS is prohibitively expensive.

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Section: Introductionsupporting

confidence: 84%

Section: Benchmarksmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Quantum Monte Carlo for noncovalent interactions: an efficient protocol attaining benchmark accuracy

Dubecký

Derian

Jurečka

et al. 2014

Phys. Chem. Chem. Phys.

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“…47,[51][52][53][54] Modern massively parallel computers have expanded the applicability of QMC methods not only to larger molecular systems but also to periodic systems because of their high parallel efficiency. 55,56 One of the most practical QMC methods, fixed-node diffusion Monte Carlo (FN-DMC), has been applied to noncovalent molecular systems and demonstrated to have an accuracy comparable to CCSD(T).…”

Section: Introductionmentioning

confidence: 99%

“…55,56 One of the most practical QMC methods, fixed-node diffusion Monte Carlo (FN-DMC), has been applied to noncovalent molecular systems and demonstrated to have an accuracy comparable to CCSD(T). 47,[51][52][53][54] Since the accuracy of FN-DMC depends critically on the choice of trial nodal surface, one should take care when generating this surface. If one uses DFT, experience shows that the nodal structures generally depend on the functional employed, and many choices are available in the literature.…”

Section: Introductionmentioning

confidence: 99%

Diffusion Monte Carlo Study of Para-Diiodobenzene Polymorphism Revisited

Hongo

Watson

Iitaka

et al. 2015

J. Chem. Theory Comput.

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We revisit our investigation of the diffusion Monte Carlo (DMC) simulation of p-DIB molecular crystal polymorphism. [J. Phys. Chem. Lett. 2010Lett. , 1, 1789Lett. -1794 We perform, for the first time, a rigorous study of finite-size effects and choice of nodal surface on the prediction of polymorph stability in molecular crystals using fixed-node DMC. Our calculations are the largest which are currently feasible using the resources of the K computer and provide insights into the formidable challenge of predicting such properties from first principles. In particular, we show that finite-size effects can influence the trial nodal surface of a small (1×1×1) simulation cell considerably. We therefore repeated our DMC simulations with a 1×3×3 simulation cell, which is the largest such calculation to date. We used a DFT nodal surface generated with the PBE functional and we accumulated statistical samples with ∼ 6.4 × 10 5 core-hours for each polymorph. Our final results predict a polymorph stability consistent with experiment, but indicate that results in our previous paper were somewhat fortuitous.We analyze the finite-size errors using model periodic Coulomb (MPC) interactions and kinetic energy corrections, according to the CCMH scheme of Chiesa, Ceperley, Martin, and Holzmann. We investigate the dependence of the finite-size errors on different aspect ratios of the simulation cell (k-mesh convergence) in order to understand how to choose an appropriate ratio for the DMC calculations. Even in the most expensive simulations currently possible, we show that the finite size errors in the DMC total energies are far larger than the energy difference between the two polymorphs, although error cancellation means that the polymorph prediction is accurate. Finally, we found that the T -move scheme is essential for these massive DMC simulations in order to circumvent population explosions and large time-step biases.

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A Nexus between Theory and Experiment: Non‐Empirical Quantum Mechanical Computational Methodology Applied to Cucurbit[n]uril⋅Guest Binding Interactions

Hostaš

Sigwalt

Šekutor

et al. 2016

Chemistry A European J

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A training set of eleven X-ray structures determined for biomimetic complexes between cucurbit[n]uril (CB[7 or 8]) hosts and adamantane-/diamantane ammonium/aminium guests were studied with DFT-D3 quantum mechanical computational methods to afford ΔG binding energies. A novel feature of this work is that the fidelity of the BLYP-D3/def2-TZVPP choice of DFT functional was proven by comparison with more accurate methods. For the first time, the CB[n]⋅guest complex binding energy subcomponents [for example, ΔE , ΔE , ΔG , binding entropy (-TΔS), and induced fit E , E ] were calculated. Only a few weeks of computation time per complex were required by using this protocol. The deformation (stiffness) and solvation properties (with emphasis on cavity desolvation) of cucurbit[n]uril (n=5, 6, 7, 8) isolated host molecules were also explored by means of the DFT-D3 method. A high ρ =0.84 correlation coefficient between ΔG and ΔG was achieved without any scaling of the calculated terms (at 298 K). This linear dependence was utilized for ΔG predictions of new complexes. The nature of binding, including the role of high energy water molecules, was also studied. The utility of introduction of tethered [-(CH ) NH ] amino loops attached to N,N-dimethyl-adamantane-1-amine and N,N,N',N'-tetramethyl diamantane-4,9-diamine skeletons (both from an experimental and a theoretical perspective) is presented here as a promising tool for the achievement of new ultra-high binding guests to CB[7] hosts. Predictions of not yet measured equilibrium constants are presented herein.

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Quantum Monte Carlo Methods Describe Noncovalent Interactions with Subchemical Accuracy

Cited by 90 publications

References 50 publications

Quantum Monte Carlo for noncovalent interactions: an efficient protocol attaining benchmark accuracy

Quantum Monte Carlo for noncovalent interactions: an efficient protocol attaining benchmark accuracy

Diffusion Monte Carlo Study of Para-Diiodobenzene Polymorphism Revisited

A Nexus between Theory and Experiment: Non‐Empirical Quantum Mechanical Computational Methodology Applied to Cucurbit[n]uril⋅Guest Binding Interactions

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