Evidence map›Paper›PMID 40777795›Full record

ReviewFundamental research2025

En route for molecular dynamics simulation of a living cell.

Yibo Wang, Cong Zhang, Ke Tang, Xiaohui Wang

Abstract readReview
In one paragraph

Review in Fundamental research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Yibo WangLaboratory of Chemical Biology, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin 130022, China.
Cong ZhangLaboratory of Chemical Biology, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin 130022, China.
Ke TangGuangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation, Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China.
Xiaohui WangLaboratory of Chemical Biology, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin 130022, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Creating an in silico all-atom whole-cell model for molecular dynamics (MD) simulation is one of the best ways to quantitatively understand the basic structure and function of cells in terms of the laws of physics and chemistry. The heavy use of graphics processing units (GPUs), the exponential growth of supercomputing power, and the emergence of MD simulation-specific supercomputers lay the groundwork for the MD simulation of molecular machinery. Moreover, the involvement of artificial intelligence (AI) will not only improve the accuracy of the simulation but also significantly accelerate the sampling efficiency. However, several underlying critical puzzles prevent in silico all-atom whole-cell modeling, which is the holy grail of MD simulation. From this perspective, we briefly reviewed the accomplishments of present techniques and hardware as well as provided insight to address the challenge of MD simulation of a living cell. With the rapid advancements in computational hardware, AI, and experimental cell biology, it would be possible to achieve this overarching goal.

Indexed as

All-atom whole-cell modelingArtificial IntelligenceKineticsMolecular dynamics simulationThermodynamics

Identifiers

PMID40777795
PMCPMC12327817

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.