Evidence map›Paper›PMID 37184925›Full record

ArticleJournal of chemical information and modeling2023

MassCCS: A High-Performance Collision Cross-Section Software for Large Macromolecular Assemblies.

Samuel Cajahuaringa, Daniel L Z Caetano, Leandro N Zanotto, Guido Araujo, Munir S Skaf

Abstract read
In one paragraph

Article in Journal of chemical information and modeling, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Samuel CajahuaringaInstitute of Computing, University of Campinas, Campinas, São Paulo 13083-852, Brazil.
Daniel L Z CaetanoCenter for Computing in Engineering & Sciences, University of Campinas, Campinas, São Paulo 13083-861, Brazil.ORCID 0000-0002-0476-3115
Leandro N ZanottoInstitute of Computing, University of Campinas, Campinas, São Paulo 13083-852, Brazil.
Guido AraujoInstitute of Computing, University of Campinas, Campinas, São Paulo 13083-852, Brazil.
Munir S SkafCenter for Computing in Engineering & Sciences, University of Campinas, Campinas, São Paulo 13083-861, Brazil.ORCID 0000-0001-7485-1228

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ion mobility mass spectrometry (IM-MS) techniques have become highly valued as a tool for structural characterization of biomolecular systems since they yield accurate measurements of the rotationally averaged collision cross-section (CCS) against a buffer gas. Despite its enormous potential, IM-MS data interpretation is often challenging due to the conformational isomerism of metabolites, lipids, proteins, and other biomolecules in the gas phase. Therefore, reliable and fast CCS calculations are needed to help interpret IM-MS data. In this work, we present MassCCS, a parallelized open-source code for computing CCS of molecules ranging from small organic compounds to massive protein assemblies at the trajectory method level of description using atomic and molecular buffer gas particles. The performance of the code is comparable to other available software for small molecules and proteins but is significantly faster for larger macromolecular assemblies. We performed extensive tests regarding accuracy, performance, and scalability with system size and number of CPU cores. MassCCS has proven highly accurate and efficient, with execution times under a few minutes, even for large (84.87 MDa) virus capsid assemblies with very modest computational resources. MassCCS is freely available at https://github.com/cces-cepid/massccs.

Indexed as

ProteinsSoftwareMass SpectrometryOrganic ChemicalsOrganic ChemicalsProteins

Identifiers

PMID37184925
PMCPMC10269586

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.