Evidence map›Paper›PMID 41081275›Full record

ArticleCommunications physics2025

Accurate quantum-centric simulations of intermolecular interactions.

Danil Kaliakin, Akhil Shajan, Fangchun Liang, Javier Robledo Moreno, Zhen Li, Abhishek Mitra, Mario Motta, Caleb Johnson, Abdullah Ash Saki, Susanta Das and 3 more

Abstract read
In one paragraph

Article in Communications physics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Quantum-Centric Alchemical Free Energy Calculations.Journal of chemical theory and computation · 2026
    Article
  2. Molecular Quantum Computations on a Protein.Journal of chemical theory and computation · 2026
    Article
  3. Article
  4. Review
  5. Article
  6. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Danil KaliakinCenter for Computational Life Sciences, Lerner Research Institute, The Cleveland Clinic, Cleveland, OH USA.
Akhil ShajanCenter for Computational Life Sciences, Lerner Research Institute, The Cleveland Clinic, Cleveland, OH USA.ORCID 0000-0001-8370-3382
Fangchun LiangCenter for Computational Life Sciences, Lerner Research Institute, The Cleveland Clinic, Cleveland, OH USA.
Javier Robledo MorenoIBM Quantum, IBM T.J. Watson Research Center, Yorktown Heights, NY USA.ORCID 0000-0001-6852-7296
Zhen LiCenter for Computational Life Sciences, Lerner Research Institute, The Cleveland Clinic, Cleveland, OH USA.
Abhishek MitraCenter for Computational Life Sciences, Lerner Research Institute, The Cleveland Clinic, Cleveland, OH USA.
Mario MottaIBM Quantum, IBM T.J. Watson Research Center, Yorktown Heights, NY USA.
Caleb JohnsonIBM Quantum, IBM T.J. Watson Research Center, Yorktown Heights, NY USA.ORCID 0009-0009-8757-4739
Abdullah Ash SakiIBM Quantum, IBM T.J. Watson Research Center, Yorktown Heights, NY USA.
Susanta DasCenter for Computational Life Sciences, Lerner Research Institute, The Cleveland Clinic, Cleveland, OH USA.
Iskandar SitdikovIBM Quantum, IBM T.J. Watson Research Center, Yorktown Heights, NY USA.
Antonio MezzacapoIBM Quantum, IBM T.J. Watson Research Center, Yorktown Heights, NY USA.
Kenneth M MerzCenter for Computational Life Sciences, Lerner Research Institute, The Cleveland Clinic, Cleveland, OH USA.ORCID 0000-0001-9139-5893

Funding

Modeling Transition Metal Ion Binding to ProteinsR01GM130641 · NIGMS · MICHIGAN STATE UNIVERSITY · PI KENNETH M. MERZ · 2019 to 2026
$2.5M
NIGMS NIH HHS R01 GM130641
6 · The paper itself

Abstract

Modelling and simulating non-covalent interactions is challenging, as they are inherently weak, dynamic, and system-specific. Common predictive methods often require trading the accuracy for reducing the otherwise cumbersome computational cost. To date, the most accurate approaches, achieving chemical accuracy, rely on quantum mechanical descriptions of non-covalent interactions, which limits their scalability. Whether quantum computing could overcome these limitations is still unclear, as such methods need to be redesigned for quantum hardware. Here, we take the first step in this direction by presenting quantum-centric simulations of non-covalent interactions using a supramolecular approach for binding energy calculations. We use a sample-based quantum diagonalization (SQD) approach to simulate the potential energy surfaces (PES) of the water and methane dimers, featuring hydrogen bond and dispersion interactions, respectively. We benchmark our quantum simulations (27- and 36-qubit circuits) against classical methods, registering deviations within 1.000 kcal/mol from the leading ones. Finally, we test the limits of the quantum methods for capturing dispersion interactions with an experiment on 54 qubits. Beyond reaching state-of-the-art accuracy, our work lays out a framework for electronic structure calculations of non-covalent interactions on quantum hardware.

Indexed as

Quantum chemistryQuantum mechanics

Identifiers

PMID41081275
PMCPMC12507674

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.