ReviewMethods in molecular biology (Clifton, N.J.)2026
Quantum Chemistry in Drug Design: Applications, Challenges, and the Need for Speed.
Review in Methods in molecular biology (Clifton, N.J.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Quantum mechanics (QM) provides a rigorous framework for modeling molecular interactions, making it increasingly valuable in drug design. However, its broader adoption is limited by computational cost and scalability. This manuscript reviews key QM applications-torsional profiles, spectra prediction, reactivity analysis, and modeling of non-covalent interactions-highlighting their impact and limitations. A detailed in-house study compares multiple methods across 3000 drug-like fragments, illustrating the trade-off between speed and accuracy. While machine learning and hybrid approaches offer faster alternatives, they often fall short of density functional theory (DFT) precision. The manuscript also explores scaling strategies and the emerging role of quantum computing. To fully leverage QM in drug discovery, faster and more scalable methods are essential.
Indexed as
Identifiers
42604904What OpenQuestion holds
Registered trials
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.