Evidence map›Paper›PMID 40097270›Full record

ArticleBioinformatics (Oxford, England)2025

VisionMol: a novel virtual reality tool for protein molecular structure visualization and manipulation.

Xin Wang, Yicheng Zhuang, Wenrui Liang, Haoyang Wen, Zhencong Cai, Yujia He, Yuxi Su, Wei Qin, Yuanzhe Cai, Lixin Liang and 1 more

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 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

11 authors.

Xin WangCollege of Big Data and Internet, Shenzhen Technology University, Shenzhen 518118, China.ORCID 0000-0001-8866-5223
Yicheng ZhuangCollege of Big Data and Internet, Shenzhen Technology University, Shenzhen 518118, China.
Wenrui LiangCollege of Big Data and Internet, Shenzhen Technology University, Shenzhen 518118, China.
Haoyang WenCollege of Big Data and Internet, Shenzhen Technology University, Shenzhen 518118, China.
Zhencong CaiCollege of Big Data and Internet, Shenzhen Technology University, Shenzhen 518118, China.
Yujia HeCollege of Big Data and Internet, Shenzhen Technology University, Shenzhen 518118, China.
Yuxi SuCollege of Big Data and Internet, Shenzhen Technology University, Shenzhen 518118, China.
Wei QinCollege of Big Data and Internet, Shenzhen Technology University, Shenzhen 518118, China.ORCID 0009-0004-2107-7530
Yuanzhe CaiCollege of Big Data and Internet, Shenzhen Technology University, Shenzhen 518118, China.ORCID 0000-0002-1449-625X
Lixin LiangCollege of Big Data and Internet, Shenzhen Technology University, Shenzhen 518118, China.
Bingding HuangCollege of Big Data and Internet, Shenzhen Technology University, Shenzhen 518118, China.ORCID 0000-0002-4748-2882

Funding

Educational Commission of Guangdong Province of China 2022ZDJS113
6 · The paper itself

Abstract

MOTIVATION &

resultsVirtual reality (VR) technology holds significant potential for applications in biomedicine, particularly in the visualization and manipulation of protein molecular structures. To facilitate the study of protein molecules and enable the state-of-the-art VR hardware, we developed a novel VR software named VisionMol, which allows users to engage in immersive exploration and analysis of 3D molecular structures using a range of VR platforms (such as Rhino X Pro, Meta's Oculus Quest Pro/3) as well as personal computers. Built on the Unity engine and programmed using C#, VisionMol incorporates custom scripts to enable a variety of molecular operations. Users can rotate, scale, and translate molecular models using gestures, controllers, or other input devices. Furthermore, VisionMol offers rich visualization and interactive features, including multi-model molecular display, distance measurement between molecular components, and molecular alignment and docking. SUMMARY: These capabilities facilitate a more intuitive understanding of molecular interactions and chemical properties. The real-time interactive effects and clear visual representations allow users to delve deeper into the relationships between molecular structures and their properties, thereby accelerating research progress and promoting scientific discovery. We believe that this VR-based protein molecule analysis has significant application value in several fields, including biomedicine, life science education, drug design and optimization, biotechnology, and engineering applications. AVAILABILITY AND IMPLEMENTATION: The code is at https://github.com/WangLabforComputationalBiology/VisionMol. The v1.1 code (for Oculus Quest) could also be found at https://doi.org/10.5281/zenodo.14705790. The v1.0 code (for Rhino X Pro) could also be found at https://doi.org/10.5281/zenodo.14865216. Detailed documentation could be found at https://visionmol.surge.sh/#/en-us/README.

Indexed as

ProteinsSoftwareVirtual RealityModels, MolecularMolecular Docking SimulationProtein ConformationUser-Computer InterfaceProteins

Identifiers

PMID40097270
PMCPMC11947413

What OpenQuestion holds

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LicenceCC BY
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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.